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4 episodes with gene sequencing
4 episodes with gene sequencing
2 episodes with gene sequencing
4 episodes with gene sequencing
2 episodes with gene sequencing
4 episodes with gene sequencing
2 episodes with gene sequencing
2 episodes with gene sequencing
4 episodes with gene sequencing
GUEST: https://mycota.com/ MENTIONS: https://www.mycoportal.org/portal/taxa/index.php?taxon=274169 https://www.inaturalist.org/ http://ww.calalive.org/ MUSHROOM HOUR: https://welcometomushroomhour.com https://instagram.com/welcome_to_mushroom_hour https://tiktok.com/@welcome_to_mushroom_hour Show Music courtesy of the one and only Chris Peck: https://peckthetowncrier.bandcamp.com/ TOPICS COVERED: Passion for Mushroom Cultivation Wild Mushroom Identification DNA barcoding vs. Whole Genome Sequencing Sanger Sequencing & Nanopore Sequencing DNA Sequencing Process from Specimen to Final DataAI & Algorithms Interpreting Genetic Data Creating Foundational Data Sets Unidentified Fungi All Around Us Expanding from Indiana Across North America Genetic Data Making Better Field Mycologists What is a “Species”? The Species Problem in Medicinal Mushroom Research Becoming a Contributor to Mycota Labs Projects Bioinformatics & Scaling Biodiversity Studies
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body, but how do these cells know what to do? Researchers at UC San Diego and Hebrew University of Jerusalem share an intercontinental effort working to determine just that. Alon Goren and Itamar Simon discuss some of the work they are doing to learn more about the human body beyond the cellular level. [Health and Medicine] [Science] [Show ID: 40516]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body, but how do these cells know what to do? Researchers at UC San Diego and Hebrew University of Jerusalem share an intercontinental effort working to determine just that. Alon Goren and Itamar Simon discuss some of the work they are doing to learn more about the human body beyond the cellular level. [Health and Medicine] [Science] [Show ID: 40516]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body, but how do these cells know what to do? Researchers at UC San Diego and Hebrew University of Jerusalem share an intercontinental effort working to determine just that. Alon Goren and Itamar Simon discuss some of the work they are doing to learn more about the human body beyond the cellular level. [Health and Medicine] [Science] [Show ID: 40516]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body, but how do these cells know what to do? Researchers at UC San Diego and Hebrew University of Jerusalem share an intercontinental effort working to determine just that. Alon Goren and Itamar Simon discuss some of the work they are doing to learn more about the human body beyond the cellular level. [Health and Medicine] [Science] [Show ID: 40516]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body, but how do these cells know what to do? Researchers at UC San Diego and Hebrew University of Jerusalem share an intercontinental effort working to determine just that. Alon Goren and Itamar Simon discuss some of the work they are doing to learn more about the human body beyond the cellular level. [Health and Medicine] [Science] [Show ID: 40516]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body, but how do these cells know what to do? Researchers at UC San Diego and Hebrew University of Jerusalem share an intercontinental effort working to determine just that. Alon Goren and Itamar Simon discuss some of the work they are doing to learn more about the human body beyond the cellular level. [Health and Medicine] [Science] [Show ID: 40516]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body, but how do these cells know what to do? Researchers at UC San Diego and Hebrew University of Jerusalem share an intercontinental effort working to determine just that. Alon Goren and Itamar Simon discuss some of the work they are doing to learn more about the human body beyond the cellular level. [Health and Medicine] [Science] [Show ID: 40516]
In this episode we speak with Wenqing (Sienna) Zhang (MPH '17), a trailblazer in public health and global healthcare innovation. Sienna shares how her passion for medical technology led her from studying pharmaceutical sciences to pursuing a master's in biostatistics and epidemiology at NYU. She recounts pivotal experiences, including internships at Pfizer and the NYC Department of Health, her role at Medtronic's first innovation accelerator in China, and her current work at Illumina, where she is driving advancements in gene sequencing worldwide. A Forbes 30 Under 30 honoree, Sienna offers candid insights into her cross-cultural career, her strategies for connecting innovation with business, and how she overcame challenges to lead in multinational settings. To learn more about the NYU School of Global Public Health, and how our innovative programs are training the next generation of public health leaders, visit http://www.publichealth.nyu.edu.
Dr. Gary Pusateri M.D., is trying something a little out of the ordinary. Himself and business partners have founded a company called Dream Genomics - it's a company that is interested in using gene sequencing to allow early detection of human diseases. He is also a hunter, and was approached by friends and colleagues and was asked the question if you can do it for humans could you do it for animals - i.e, can you use blood to detect the early signs of animal based diseases like Chronic Wasting Disease (CWD)? This conversation dives into that possibility and more. Support our newest Conservation Club Members! Outdoor Solutions: https://outdoorsolutionscorp.com/ Greater Kuduland Safaris: https://www.greaterkudulandsafaris.com/ Clean Eatz: https://cleaneatz.com/ See more from Blood Origins: https://bit.ly/BloodOrigins_Subscribe Music: Migration by Ian Post (Winter Solstice), licensed through artlist.io Podcast is brought to you by: Bushnell: https://www.bushnell.com Learn more about your ad choices. Visit megaphone.fm/adchoices
Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]
Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]
Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]
Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]
Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]
Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]
Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]
Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]
Mark McDonough, the CEO of ChromaCode, is leveraging high-definition PCR testing to overcome the limitations of conventional PCR to identify biomarkers of infectious diseases and cancer. While gene sequencing can provide valuable information, it requires more tissue, is expensive, and requires at least a week for analysis. Using HDPCR, ChromaCode has developed a lung cancer assay that looks at nine genes and 15 biomarkers, requiring less tissue, performed at a lower cost, and provides results quickly. This approach, built on a cloud-supported multiplexing platform, provides flexibility to explore other areas in oncology and transplants, looking at multiple targets per sample. Mark explains, "With PCR today, assays look at particular biomarkers on a gene-by-gene basis. So those can be effective in lung cancer, for example, if you know you're just looking for EGFR as a biomarker or if you're looking at KRAS or ALK, a different mutation. But the problem is it's not very comprehensive, and you need a lot of tissue. So, PCR falls short because it's limited in scalability and requires a lot of tissue." "Why this is important for the patient in terms of patient empowerment and lung cancer is when a patient gets their result back from ChromaCode and their provider using ChromaCode technology, they also are more than likely having an immunochemistry test called PD-L1 run. They're trying to determine if there is a targeted therapy, or is it best to put a patient on immunotherapy, or is there a combination of immunotherapy and chemo?" "Having all that answer back in one to two days, as opposed to knowing what you'll get back from immunochemistry in a day and then waiting two weeks for sequencing, can be very problematic. So, we feel like we're meeting that open opportunity where sequencing is too slow and too expensive, requiring too much tissue, and PCR just isn't comprehensive enough and is very much trial and error on a one-by-one basis with our technology." #ChromaCode #HDPCR #Diagnostics #ChromaCodeCloud #Genomics #LungCancer #GeneSequencing chromacode.com Download the transcript here
Mark McDonough, the CEO of ChromaCode, is leveraging high-definition PCR testing to overcome the limitations of conventional PCR to identify biomarkers of infectious diseases and cancer. While gene sequencing can provide valuable information, it requires more tissue, is expensive, and requires at least a week for analysis. Using HDPCR, ChromaCode has developed a lung cancer assay that looks at nine genes and 15 biomarkers, requiring less tissue, performed at a lower cost, and provides results quickly. This approach, built on a cloud-supported multiplexing platform, provides flexibility to explore other areas in oncology and transplants, looking at multiple targets per sample. Mark explains, "With PCR today, assays look at particular biomarkers on a gene-by-gene basis. So those can be effective in lung cancer, for example, if you know you're just looking for EGFR as a biomarker or if you're looking at KRAS or ALK, a different mutation. But the problem is it's not very comprehensive, and you need a lot of tissue. So, PCR falls short because it's limited in scalability and requires a lot of tissue." "Why this is important for the patient in terms of patient empowerment and lung cancer is when a patient gets their result back from ChromaCode and their provider using ChromaCode technology, they also are more than likely having an immunochemistry test called PD-L1 run. They're trying to determine if there is a targeted therapy, or is it best to put a patient on immunotherapy, or is there a combination of immunotherapy and chemo?" "Having all that answer back in one to two days, as opposed to knowing what you'll get back from immunochemistry in a day and then waiting two weeks for sequencing, can be very problematic. So, we feel like we're meeting that open opportunity where sequencing is too slow and too expensive, requiring too much tissue, and PCR just isn't comprehensive enough and is very much trial and error on a one-by-one basis with our technology." #ChromaCode #HDPCR #Diagnostics #ChromaCodeCloud #Genomics #LungCancer #GeneSequencing chromacode.com Listen to the podcast here
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body. From the skin to the brain, muscles to blood, and everything in between, these countless cells collaborate harmoniously to keep us alive and well, but how do these cells know what to do? When a cell divides, how does it know that it's exact counterpart should do the same thing as the original. Researchers at the Goren Lab at UC San Diego are working to determine just that. They discuss some of the work they are doing to learn more about the human body beyond the cellular level [Health and Medicine] [Science] [Show ID: 38259]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body. From the skin to the brain, muscles to blood, and everything in between, these countless cells collaborate harmoniously to keep us alive and well, but how do these cells know what to do? When a cell divides, how does it know that it's exact counterpart should do the same thing as the original. Researchers at the Goren Lab at UC San Diego are working to determine just that. They discuss some of the work they are doing to learn more about the human body beyond the cellular level [Health and Medicine] [Science] [Show ID: 38259]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body. From the skin to the brain, muscles to blood, and everything in between, these countless cells collaborate harmoniously to keep us alive and well, but how do these cells know what to do? When a cell divides, how does it know that it's exact counterpart should do the same thing as the original. Researchers at the Goren Lab at UC San Diego are working to determine just that. They discuss some of the work they are doing to learn more about the human body beyond the cellular level [Health and Medicine] [Science] [Show ID: 38259]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body. From the skin to the brain, muscles to blood, and everything in between, these countless cells collaborate harmoniously to keep us alive and well, but how do these cells know what to do? When a cell divides, how does it know that it's exact counterpart should do the same thing as the original. Researchers at the Goren Lab at UC San Diego are working to determine just that. They discuss some of the work they are doing to learn more about the human body beyond the cellular level [Health and Medicine] [Science] [Show ID: 38259]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body. From the skin to the brain, muscles to blood, and everything in between, these countless cells collaborate harmoniously to keep us alive and well, but how do these cells know what to do? When a cell divides, how does it know that it's exact counterpart should do the same thing as the original. Researchers at the Goren Lab at UC San Diego are working to determine just that. They discuss some of the work they are doing to learn more about the human body beyond the cellular level [Health and Medicine] [Science] [Show ID: 38259]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body. From the skin to the brain, muscles to blood, and everything in between, these countless cells collaborate harmoniously to keep us alive and well, but how do these cells know what to do? When a cell divides, how does it know that it's exact counterpart should do the same thing as the original. Researchers at the Goren Lab at UC San Diego are working to determine just that. They discuss some of the work they are doing to learn more about the human body beyond the cellular level [Health and Medicine] [Science] [Show ID: 38259]
The human body is made up of billions of cells. These cells are the basic building blocks of life, and they work together to form tissues, organs, and systems that enable our body to function and carry out various activities. Each cell has its own specific function and role in maintaining the overall health and functionality of the body. From the skin to the brain, muscles to blood, and everything in between, these countless cells collaborate harmoniously to keep us alive and well, but how do these cells know what to do? When a cell divides, how does it know that it's exact counterpart should do the same thing as the original. Researchers at the Goren Lab at UC San Diego are working to determine just that. They discuss some of the work they are doing to learn more about the human body beyond the cellular level [Health and Medicine] [Science] [Show ID: 38259]
In a wide-ranging conversation, Leo Laporte talks with Dr. George Church about the history and future of genome sequencing. Dr. Church explains why he is very excited about how they made an organism resistant to all viruses- both known and unknown. They also talk about: How Dr. Church made sequencing affordable (from $3BN to $600) Where are we on sequencing the entire human genome, and why would we even want to? How close are we to reversing aging? Should we use gene therapy to double the human lifespan? Why genetically engineering cold-resistant elephants could be important for climate change, and what about ultimately bringing back the Mammoth? He explains the difference between the hype and reality of CRISPR sequencing, synthesis, and delivery What are the privacy concerns about companies sharing your genome? They discuss the controversy and benefit of reconstructing old viruses like the 1918 flu and even inventing new viruses. Dr. Church is a professor of genetics at Harvard Medical School and a pioneer in personal genetics. He is credited with developing the first methods for sequencing the first genome and also the CRISPR technology. He created several companies, including Nebula Genomics and Veritas Genetics. Host: Leo Laporte Guest: Dr. George Church Download or subscribe to this show at https://twit.tv/shows/triangulation.
In a wide-ranging conversation, Leo Laporte talks with Dr. George Church about the history and future of genome sequencing. Dr. Church explains why he is very excited about how they made an organism resistant to all viruses- both known and unknown. They also talk about: How Dr. Church made sequencing affordable (from $3BN to $600) Where are we on sequencing the entire human genome, and why would we even want to? How close are we to reversing aging? Should we use gene therapy to double the human lifespan? Why genetically engineering cold-resistant elephants could be important for climate change, and what about ultimately bringing back the Mammoth? He explains the difference between the hype and reality of CRISPR sequencing, synthesis, and delivery What are the privacy concerns about companies sharing your genome? They discuss the controversy and benefit of reconstructing old viruses like the 1918 flu and even inventing new viruses. Dr. Church is a professor of genetics at Harvard Medical School and a pioneer in personal genetics. He is credited with developing the first methods for sequencing the first genome and also the CRISPR technology. He created several companies, including Nebula Genomics and Veritas Genetics. Host: Leo Laporte Guest: Dr. George Church Download or subscribe to this show at https://twit.tv/shows/twit-events. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit
In a wide-ranging conversation, Leo Laporte talks with Dr. George Church about the history and future of genome sequencing. Dr. Church explains why he is very excited about how they made an organism resistant to all viruses- both known and unknown. They also talk about: How Dr. Church made sequencing affordable (from $3BN to $600) Where are we on sequencing the entire human genome, and why would we even want to? How close are we to reversing aging? Should we use gene therapy to double the human lifespan? Why genetically engineering cold-resistant elephants could be important for climate change, and what about ultimately bringing back the Mammoth? He explains the difference between the hype and reality of CRISPR sequencing, synthesis, and delivery What are the privacy concerns about companies sharing your genome? They discuss the controversy and benefit of reconstructing old viruses like the 1918 flu and even inventing new viruses. Dr. Church is a professor of genetics at Harvard Medical School and a pioneer in personal genetics. He is credited with developing the first methods for sequencing the first genome and also the CRISPR technology. He created several companies, including Nebula Genomics and Veritas Genetics. Host: Leo Laporte Guest: Dr. George Church Download or subscribe to this show at https://twit.tv/shows/triangulation.
In a wide-ranging conversation, Leo Laporte talks with Dr. George Church about the history and future of genome sequencing. Dr. Church explains why he is very excited about how they made an organism resistant to all viruses- both known and unknown. They also talk about: How Dr. Church made sequencing affordable (from $3BN to $600) Where are we on sequencing the entire human genome, and why would we even want to? How close are we to reversing aging? Should we use gene therapy to double the human lifespan? Why genetically engineering cold-resistant elephants could be important for climate change, and what about ultimately bringing back the Mammoth? He explains the difference between the hype and reality of CRISPR sequencing, synthesis, and delivery What are the privacy concerns about companies sharing your genome? They discuss the controversy and benefit of reconstructing old viruses like the 1918 flu and even inventing new viruses. Dr. Church is a professor of genetics at Harvard Medical School and a pioneer in personal genetics. He is credited with developing the first methods for sequencing the first genome and also the CRISPR technology. He created several companies, including Nebula Genomics and Veritas Genetics. Host: Leo Laporte Guest: Dr. George Church Download or subscribe to this show at https://twit.tv/shows/twit-events. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit
In a wide-ranging conversation, Leo Laporte talks with Dr. George Church about the history and future of genome sequencing. Dr. Church explains why he is very excited about how they made an organism resistant to all viruses- both known and unknown. They also talk about: How Dr. Church made sequencing affordable (from $3BN to $600) Where are we on sequencing the entire human genome, and why would we even want to? How close are we to reversing aging? Should we use gene therapy to double the human lifespan? Why genetically engineering cold-resistant elephants could be important for climate change, and what about ultimately bringing back the Mammoth? He explains the difference between the hype and reality of CRISPR sequencing, synthesis, and delivery What are the privacy concerns about companies sharing your genome? They discuss the controversy and benefit of reconstructing old viruses like the 1918 flu and even inventing new viruses. Dr. Church is a professor of genetics at Harvard Medical School and a pioneer in personal genetics. He is credited with developing the first methods for sequencing the first genome and also the CRISPR technology. He created several companies, including Nebula Genomics and Veritas Genetics. Host: Leo Laporte Guest: Dr. George Church Download or subscribe to this show at https://twit.tv/shows/twit-events. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit
In a wide-ranging conversation, Leo Laporte talks with Dr. George Church about the history and future of genome sequencing. Dr. Church explains why he is very excited about how they made an organism resistant to all viruses- both known and unknown. They also talk about: How Dr. Church made sequencing affordable (from $3BN to $600) Where are we on sequencing the entire human genome, and why would we even want to? How close are we to reversing aging? Should we use gene therapy to double the human lifespan? Why genetically engineering cold-resistant elephants could be important for climate change, and what about ultimately bringing back the Mammoth? He explains the difference between the hype and reality of CRISPR sequencing, synthesis, and delivery What are the privacy concerns about companies sharing your genome? They discuss the controversy and benefit of reconstructing old viruses like the 1918 flu and even inventing new viruses. Dr. Church is a professor of genetics at Harvard Medical School and a pioneer in personal genetics. He is credited with developing the first methods for sequencing the first genome and also the CRISPR technology. He created several companies, including Nebula Genomics and Veritas Genetics. Host: Leo Laporte Guest: Dr. George Church Download or subscribe to this show at https://twit.tv/shows/triangulation.
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
CARTA - Center for Academic Research and Training in Anthropogeny (Video)
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
Anthropogeny, has provided many new discoveries over the past decade, ranging from new fossil finds to ancient DNA data, including from extinct hominins. This CARTA symposium highlights where future efforts should be focused and what type of novel collaborations are most promising to improve our understanding of the human phenomenon. Evan Eichler talks about the discovery and resolution of genetic variation which is critical to understanding disease and evolution. The data suggests that large-scale genome structural variation continues to play a crucial role in the evolution of the human species.Daniel Geschwind discusses human cognition and how human brain evolution is particularly susceptible to disruption of neuropsychiatric disorders such as schizophrenia and autism spectrum disorder (ASD). Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Education] [Show ID: 38630]
The discovery and resolution of genetic variation is critical to understanding disease and evolution. Our most recent work sequences diverse human and nonhuman primate genomes using both ultra-long and high-fidelity long-read sequencing technologies. Advances in this area have made possible the first telomere-to-telomere assemblies of the human genome and much more complete chimp, gorilla and orangutan genomes providing new biological insights into regions typically excluded from human genetic and comparative studies. We have discovered mega basepairs of duplicated sequence and/or rapidly evolving sequence present in humans that are absent from other non-human primates. These changes have predisposed our species to recurrent rearrangements associated with disease but also have led to the emergence of new genes important in the expansion of the human frontal cortex of the brain. Our data suggest that large-scale genome structural variation has played and continues to play a crucial role in the evolution of the human species. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Show ID: 38297]
The discovery and resolution of genetic variation is critical to understanding disease and evolution. Our most recent work sequences diverse human and nonhuman primate genomes using both ultra-long and high-fidelity long-read sequencing technologies. Advances in this area have made possible the first telomere-to-telomere assemblies of the human genome and much more complete chimp, gorilla and orangutan genomes providing new biological insights into regions typically excluded from human genetic and comparative studies. We have discovered mega basepairs of duplicated sequence and/or rapidly evolving sequence present in humans that are absent from other non-human primates. These changes have predisposed our species to recurrent rearrangements associated with disease but also have led to the emergence of new genes important in the expansion of the human frontal cortex of the brain. Our data suggest that large-scale genome structural variation has played and continues to play a crucial role in the evolution of the human species. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Show ID: 38297]
The discovery and resolution of genetic variation is critical to understanding disease and evolution. Our most recent work sequences diverse human and nonhuman primate genomes using both ultra-long and high-fidelity long-read sequencing technologies. Advances in this area have made possible the first telomere-to-telomere assemblies of the human genome and much more complete chimp, gorilla and orangutan genomes providing new biological insights into regions typically excluded from human genetic and comparative studies. We have discovered mega basepairs of duplicated sequence and/or rapidly evolving sequence present in humans that are absent from other non-human primates. These changes have predisposed our species to recurrent rearrangements associated with disease but also have led to the emergence of new genes important in the expansion of the human frontal cortex of the brain. Our data suggest that large-scale genome structural variation has played and continues to play a crucial role in the evolution of the human species. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Show ID: 38297]
The discovery and resolution of genetic variation is critical to understanding disease and evolution. Our most recent work sequences diverse human and nonhuman primate genomes using both ultra-long and high-fidelity long-read sequencing technologies. Advances in this area have made possible the first telomere-to-telomere assemblies of the human genome and much more complete chimp, gorilla and orangutan genomes providing new biological insights into regions typically excluded from human genetic and comparative studies. We have discovered mega basepairs of duplicated sequence and/or rapidly evolving sequence present in humans that are absent from other non-human primates. These changes have predisposed our species to recurrent rearrangements associated with disease but also have led to the emergence of new genes important in the expansion of the human frontal cortex of the brain. Our data suggest that large-scale genome structural variation has played and continues to play a crucial role in the evolution of the human species. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Show ID: 38297]
The discovery and resolution of genetic variation is critical to understanding disease and evolution. Our most recent work sequences diverse human and nonhuman primate genomes using both ultra-long and high-fidelity long-read sequencing technologies. Advances in this area have made possible the first telomere-to-telomere assemblies of the human genome and much more complete chimp, gorilla and orangutan genomes providing new biological insights into regions typically excluded from human genetic and comparative studies. We have discovered mega basepairs of duplicated sequence and/or rapidly evolving sequence present in humans that are absent from other non-human primates. These changes have predisposed our species to recurrent rearrangements associated with disease but also have led to the emergence of new genes important in the expansion of the human frontal cortex of the brain. Our data suggest that large-scale genome structural variation has played and continues to play a crucial role in the evolution of the human species. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Show ID: 38297]
CARTA - Center for Academic Research and Training in Anthropogeny (Video)
The discovery and resolution of genetic variation is critical to understanding disease and evolution. Our most recent work sequences diverse human and nonhuman primate genomes using both ultra-long and high-fidelity long-read sequencing technologies. Advances in this area have made possible the first telomere-to-telomere assemblies of the human genome and much more complete chimp, gorilla and orangutan genomes providing new biological insights into regions typically excluded from human genetic and comparative studies. We have discovered mega basepairs of duplicated sequence and/or rapidly evolving sequence present in humans that are absent from other non-human primates. These changes have predisposed our species to recurrent rearrangements associated with disease but also have led to the emergence of new genes important in the expansion of the human frontal cortex of the brain. Our data suggest that large-scale genome structural variation has played and continues to play a crucial role in the evolution of the human species. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Show ID: 38297]
The discovery and resolution of genetic variation is critical to understanding disease and evolution. Our most recent work sequences diverse human and nonhuman primate genomes using both ultra-long and high-fidelity long-read sequencing technologies. Advances in this area have made possible the first telomere-to-telomere assemblies of the human genome and much more complete chimp, gorilla and orangutan genomes providing new biological insights into regions typically excluded from human genetic and comparative studies. We have discovered mega basepairs of duplicated sequence and/or rapidly evolving sequence present in humans that are absent from other non-human primates. These changes have predisposed our species to recurrent rearrangements associated with disease but also have led to the emergence of new genes important in the expansion of the human frontal cortex of the brain. Our data suggest that large-scale genome structural variation has played and continues to play a crucial role in the evolution of the human species. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Show ID: 38297]
The discovery and resolution of genetic variation is critical to understanding disease and evolution. Our most recent work sequences diverse human and nonhuman primate genomes using both ultra-long and high-fidelity long-read sequencing technologies. Advances in this area have made possible the first telomere-to-telomere assemblies of the human genome and much more complete chimp, gorilla and orangutan genomes providing new biological insights into regions typically excluded from human genetic and comparative studies. We have discovered mega basepairs of duplicated sequence and/or rapidly evolving sequence present in humans that are absent from other non-human primates. These changes have predisposed our species to recurrent rearrangements associated with disease but also have led to the emergence of new genes important in the expansion of the human frontal cortex of the brain. Our data suggest that large-scale genome structural variation has played and continues to play a crucial role in the evolution of the human species. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Show ID: 38297]
The discovery and resolution of genetic variation is critical to understanding disease and evolution. Our most recent work sequences diverse human and nonhuman primate genomes using both ultra-long and high-fidelity long-read sequencing technologies. Advances in this area have made possible the first telomere-to-telomere assemblies of the human genome and much more complete chimp, gorilla and orangutan genomes providing new biological insights into regions typically excluded from human genetic and comparative studies. We have discovered mega basepairs of duplicated sequence and/or rapidly evolving sequence present in humans that are absent from other non-human primates. These changes have predisposed our species to recurrent rearrangements associated with disease but also have led to the emergence of new genes important in the expansion of the human frontal cortex of the brain. Our data suggest that large-scale genome structural variation has played and continues to play a crucial role in the evolution of the human species. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Humanities] [Science] [Show ID: 38297]
That's Cool News | A weekly breakdown of positive Science & Tech news.
Show Notes: Google Fiber Revs Up Its Multi-Gig Speeds to 20Gbps in Newest Field Test | CNET (01:29) Google Fiber CEO Dinni Jain announced Tuesday via blog post that 20 gigs is coming, The company achieved a 20.2Gbps download speed in a field test in Kansas City Google Fiber currently offers two plan options: 1-gigabit download speeds for $70 per month and a 2-gig plan for $100 monthly. cheapest 2Gbps plan among major internet providers CNET reached out to a Google Fiber spokesperson, and was told that more information will be on the way in the coming weeks. No word yet on pricing or when to expect the plan to be available to customers. A 25Gbps speed tier from EPB costs around $1,500 per month According to Google Fiber's CEO this is just the beginning: “In the coming months, we'll have announcements to dramatically expand our multi-gigabit tiers. These will be critical milestones on our journey to 100 Gig symmetrical internet." NASA crashes DART spacecraft into asteroid in world's 1st planetary defense test | Space.com (06:45) For the first time in history, a spacecraft from Earth has crashed into an asteroid to test a way to save our planet from extinction. Spacecraft: NASA's Double Asteroid Rendezvous Test (DART) probe Asteroid: Dimorphos, 7 million miles (11 million kilometers) from Earth The goal of the mission was to change the orbit of the space rock around its larger asteroid parent Didymos . Trying to test if humanity could deflect a dangerous asteroid if one was headed for Earth. Elena Adams, DART's mission systems engineer, said that “our first planetary defense test was a success” The golf cart-sized DART (1,320 pounds) spacecraft slammed into the asteroid at 14,000 mph. Would be enough to move the 534-foot-wide (163 meters) Dimorphos a bit faster (10 minutes faster) in its orbit around its parent. Poses no risk of changing the binary system's orbit to come anywhere near Earth. The DART mission is the first demonstration of what NASA calls a "kinetic impactor" for planetary defense: crashing a spacecraft into an asteroid to change its orbit. Basic method to protect the Earth if a potentially dangerous asteroid were spotted five or 10 years before a prospective impact. Angela Stickle, the leader of DART's impact working group, said the team's simulations and models suggest the spacecraft would likely create a crater up to 65 feet (20 m) wide. Images Show Huge Plume of Debris as NASA Probe Smashes Asteroid A vast network of ground-based telescopes were trained on the event and will be following the binary Didymos-Dimorphos system over time to see how much faster Dimorphos is now moving in its orbit. The Era of Fast, Cheap Genome Sequencing Is Here | WIRED (13:35) At an industry event in San Diego today, genomics behemoth Illumina unveiled what it calls its fastest, most cost-efficient sequencing machines yet, the NovaSeq X series. Illumina controls around 80 percent of the DNA sequencing market globally The company believes its new technology will slash the cost to just $200 per human genome while providing a readout at twice the speed. Currently costs $600 for scientists to perform sequencing Sequence 20,000 genomes per year; its current machines can do about 7,500 Francis deSouza, Illumina's CEO, states: “As we look to the next decade, we believe we're entering the era of genomic medicine going mainstream. To do that requires the next generation of sequencers … We need price points to keep coming down to make genomic medicine and genomic tests available much more broadly.” Stacey Gabriel, chief genomics officer at the Broad Institute of MIT and Harvard, states they have been “waiting for this for a long time.” She continues to talk about the benefits of the new tech: “With greatly reduced costs and greatly increased speed of sequencing, we can sequence way more samples.” A major benefit of cheaper and more efficiency sequencing is increasing the diversity of genomic datasets. Different populations might have different disease-causing genetic variations that are more or less prevalent. Additionally, by sequencing more genes you can compare and contrast the genetic sequences of a healthy individual and a disordered individual. Allows researchers to see the nuances in their genetic makeup. Illumina's new system will cost around $1 million, about the same as its existing machines. The high price tag is a key reason they're not yet common in smaller labs and hospitals, or in rural regions. Startup Says It Can Store 100TB in Nintendo-Like Cartridges | Futurism (20:24) A startup called Folio Photonics is attempting to take over the archival storage market, one Nintendo-ish cartridge at a time. Storage types like tapes, and hard disks are favored by enterprise-scale archiving purposes. Folio claims to offer a cost-effective, incredibly high-performing optical alternative to tapes, hard disks, and DNA storage Just one of their oddly-shaped, multi-layered cartridges can allegedly fit 100 terabytes of data. 100,000 gigabytes, which is nearly three times the storage of the densest Blu-Ray disk CEO Steven Santamaria explains how their tech can hold this much data: “Traditional Blu-ray discs are three or four layers and have been for 20 years (the Archival disc achieves 6 layers by having 3-layers on both sides) ... Our first product will be 8 layers per side, meaning we will have a 16 layer double sided disc." Additionally, the company claims their storage device, unlike hard drive and tape storage, is "impervious" to electromagnetic disruption, damage from radiation or saltwater, and extreme temperatures We will end off with more of the CEO talking about the tech: “Our talented engineering team has pioneered a fresh approach to optical storage that overcomes historical constraints and puts unheard of cost, cybersecurity and sustainability benefits within reach … With these advantages, Folio Photonics is poised to reshape the trajectory of archive storage." Why United Airlines is betting $1 billion on flying cars | Emerging Tech Brew (25:12) Investors, startups, and aviation bigwigs have all put billions of dollars toward making that vision a reality with electric vertical takeoff and landing (eVTOL) ventures. United Airlines being one of them The company has been an investor in California-based Archer Aviation since the startup was preparing to go public via SPAC in 2021 and also reached a $1 billion deal to buy Archer's eVTOLs last February. An option to purchase an additional $500 million of aircraft. Archer is building a four-passenger electric aircraft and aims to get it certified by the FAA for use in the US by the end of 2024. This past September, United agreed to buy 200 eVTOL aircraft from Eve Air Mobility. Why are they doing this? Mike Leskinen, president of United Airlines Ventures, told Emerging Tech Brew: “It's about making our airline the airline that customers choose to fly … A) We want to innovate. And we want to provide that to our customers first B) We have the footprint—the geographic footprint—that makes us the right player C) It decarbonizes that trip to the airport. This is not taking regional aircraft out of the skies, but it is taking cars off the road, many of which will be burning gasoline” eVTOLs could change the way we travel in the long term, with the nearer-term use case of replacing helicopters and serving as a way to get from an urban center to an airport faster. CEO Leskinen talks on the pricing of these eVTOL rides: “They're going to be expensive at first … As you build this product, as you certify this product, there are going to be massive economies of scale. And the cost is going to come down rapidly, to the point where I see a world where—because you get so much more utility out of the aircraft—the cost is no more than using an Uber X. But initially it's going to look like an Uber Black.” The challenging part will be building the infrastructure for air taxis, the “vertiports, ” which could resemble helipads with charging stations.
You might be surprised to learn that data storage currently requires huge amounts of land and energy, and we're running out of both. In this episode, we speak with a small group of researchers who are working to revolutionize the way we store the massive amounts of data we produce every day. Their solution: use DNA.Speakers:Emily Leproust, Twist BioscienceJeff Nivala, University of WashingtonKyle Tomek, DNAli Technologies
Episode: 2934 Reading the Molecules of Life. Today, we read the molecules of life.
Genialis, led by CEO Rafael Rosengarten, is one of the companies working toward a future where there are no more one-size-fits-all drugs—where, instead, every patient gets matched with the best drug for them based on their disease subtype, as measured by gene-sequence and gene-expression data. Analyzing that data—what Rosengarten calls "computational precision medicine"—is already helping drug developers identify the patients who are most likely to respond to experimental medicines. Not long from now, the same technology could help doctors diagnose patients in the clinic, and/or feed back into drug discovery by providing more biological targets for biopharma companies to hit."Our commitment to biomarker-driven drug development is very principled," Rosengarten tells Harry. "There are some amazing drugs out there that, when they work, work miracles. But they don't work that often. Some work in maybe 15 percent of the patients or 20 percent. If you could tell which of those patients are going to respond, then at least the ones who aren't can seek other options, and we would know that we've got to develop [new] drugs for the others." Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.Full TranscriptHarry Glorikian: Hello. I'm Harry Glorikian. Welcome to The Harry Glorikian Show, the interview podcast that explores how technology is changing everything we know about healthcare.Artificial intelligence. Big data. Predictive analytics. In fields like these, breakthroughs are happening way faster than most people realize. If you want to be proactive about your own health and the health of your loved ones, you'll need to learn everything you can about how medicine is changing and how you can take advantage of all the new options.Explaining this approaching world is the mission of my new book, The Future You. And it's also our theme here on the show, where we bring you conversations with the innovators, caregivers, and patient advocates who are transforming the healthcare system and working to push it in positive directions.For most people, the genomics revolution still feels pretty distant, like something that's happening off in the ivory towers of big pharma companies or research universities.But say, heaven forbid, you get diagnosed with cancer next week. All of a sudden you're going to want to get very familiar with your own genome. Because thanks to the Human Genome Project and all the new tools for sequencing and analyzing genes, we know today that there are many different forms of cancer. And each one may respond to a different type of medicine. So before you and your doctor can decide which medicines will work best for you, you really need to know which genes and mutations you carry and how they're expressed in your cells.Drug companies need similar data when they're testing new drugs. Because if they happen to test a drug on a population of people who happen to have the wrong genes to respond to that drug, they could wind up throwing away a medicine that would work perfectly well on people who have the right genes.The problem is that all of this gene sequencing and expression testing generates incredible amounts of data. And doctors and hospitals and even big pharma companies aren't always set up to understand or analyze that data.My guest this week is the CEO of a company that's helping with that problem. His name is Rafael Rosengarten. And his company Genialis has built a software platform that organizes and analyzes data from high-throughput gene sequencing and RNA expression assays. We'll talk more about what all those terms mean. But what you need to know is that Genialis is one of the companies on the cutting edge of translating genetic data into actionable predictions. Those predictions are already helping biotech and pharma companies get drugs to market faster. And in the near future they could help doctors funnel patients toward the right treatments. I wrote a whole chapter on this stuff for my new book, The Future You. So it was really fun to talk it through all of it with Rafael. Here's our conversation.Harry Glorikian: Rafael, welcome to the show.Rafael Rosengarten: Thanks for having me, Harry.Harry Glorikian: For those listeners that don't have backgrounds in, say, computational biology or drug development, could you define a few terms that are probably going to come up later in our discussion? I mean, first, you know, maybe define next-generation sequencing or this term we call NGS. What is next-generation about?Rafael Rosengarten: Sure, I'd be happy to do that, let me start by just kind of saying what Genialis is with some jargon in the words, and then I'll define the jargon for you. Okay. So Genialis is computational precision medicine. So what that means is we're really interested in matching patients to therapies, right? And we use data about the molecular biology of patients' diseases to do that. And our favorite kind of data to work with come from next generation sequencing. So next generation sequencing, often abbreviated as NGS, although we've been doing that for 15 years now, we probably just need to call it this-generation sequencing, is a technology where you can get the genetic information of the entire, say, genome or the transcriptome, that's the expression [for] which genes are expressed, and you get literally every base pair off of a machine that reads the DNA or RNA from cells in our body. And with that information, you do some fancy computation that, frankly, a lot of that's now fairly commoditized. And it kind of maps all of the individual bits of data into what we think we know about the human genome. And so you can say, OK, we've got this much of this gene and that much of this gene or you can say, you know, Gene A has certain mutations and Gene B has other mutations. And so it allows you to ask whether whether they're mutations or changes in the amount of certain molecules and so forth. But you get to do it for all the genes and not only all the genes you can do it for, [but] for all the space in between the genes in the genome.Harry Glorikian: Yeah, I you know, it's funny because just the other day there was the announcement that we quote "actually finished" the entire genome, which I thought was an interesting announcement. One more definition. So this term RNAseq, right? So, you know, drawing the analogy of DNA and saying, OK, RNA is the next level. And why has that become so important now in drug discovery?Rafael Rosengarten: That's a great question, so again, for your listeners who may not live and breathe this stuff, there's a concept in in biology called the central dogma, and it kind of still holds. And the notion is that there are these different levels of organizations or different layers of the onion and peeling back the information that our cells use to conduct business. And the the core of this is DNA, and that's our genetic information that's encoded in our nucleus and it's passed down from parents to children. It's the heritable information, and I apologize to all my friends who do live and breathe this, who are going to call shenanigans on my definition of being overly simplistic. The next level is, as you described, is the RNA. And so RNA is actually a lot of things. But messenger RNAs are the transcription of the genes. So the DNA genes that hold our genetic information are converted through a molecular process into another kind of molecule. And that kind of molecule is RNA. It's chemically similar to DNA, but different, and that RNA tend to be in smaller pieces than the whole chromosomes, and they represent smaller pieces of genetic information, and they can vary widely from, say, one gene to the next in terms of how much RNA is made for that given gene.Rafael Rosengarten: And then just to fill out the picture a bit more, in principle, then, those RNA molecules get turned into protein, or they are the specific instructions to create proteins, and proteins then go do the work of the cell. What I just told you is mostly wrong, but it's sort of the framework that we think about. So the reason why RNA, the middle layer, is so interesting in drug discovery, and I'm going to add to that, in diagnostics world, is because it's a bit more, let's call it dynamic than the DNA level. So mutations sometimes are heritable and sometimes they arise de novo. But once they've arisen, they're kind of there and they go through from cell to cell, once the cells divide. And that's, you know, that's important and interesting and meaningful information, you can learn a lot about what genes are potentially druggable from that. But it doesn't tell you a whole lot about the state of tissue or the state of disease in this moment, right? It's kind of background information in a way. And so RNA is a bit more dynamic.Rafael Rosengarten: It changes. It can change on, you know, really rapid time scales, but certainly therapeutically relevant time scales. And so in some ways, it's a little bit closer to sort of what's happening now. Harry Glorikian: Right.Rafael Rosengarten: It's also just a different, it's a different class of information because there are these abundances, different genes at different levels. Those relative abundances have biological importance and sometimes therapeutic importance. A lot of cancers, for example, are bad for you. They are essentially dysregulation of gene expression, so they can arise from mutations or they can arise from events at the DNA level. But it's understanding how much of some species of gene is being expressed in the RNA that can be informative or potentially therapeutically actionable. And I'm going to shout out to my proteomics friends, the guys who study proteins. That may be even more therapeutically relevant in a sense, because most of our drugs actually target proteins. And that's quite the key of it. Except for gene therapy, which is a big deal, especially in the CRISPR era, we're not often targeting DNA with our drugs, right? Mostly, we're targeting proteins and occasionally we're targeting RNAs and less frequently we're targeting DNA. Again, all CRISPR bets aside, right?Harry Glorikian: Yeah. No, we did an episode with talking about CRISPR and, you know, amazing advancements happening there. But now, being from Applied Biosystems, I remember an entire room full of sequencers where we, I think they were like 600 or 800 we had running 24 hours a day at one point. Now I can do that on a desktop, right? But. There's a lot of data that comes off that. T hat's a challenge, I think, for people in drug development to manage that much data. You started at Baylor with a lot of your research. How did how did you personally encounter these challenges in your research?Rafael Rosengarten: I mean, it was very much this challenge that inspired us to start Genialis. So the conception story of Genialis is my co-founders and I, we really wanted to be able to do advanced cutting edge data science like machine learning, AI type stuff, which I'm sure we'll talk about at some point, in order to really bring kind of the next level of analytics to bear on biomedical problems. And what we realized is that's all well and good, but you can't do any of that stuff unless you get the data in a place where you can work on it. And I remember going to talk to one of the top researchers at all ofe Baylor College of Medicine. This person is top of her field, chair of department, et cetera, et cetera. And I asked her, How does your lab deal with your data retention and your data management, your data analysis? And she said, Glad you asked, this is such a big problem. We just had one of our postdocs leave, and he took his little thumb drives with him, and all of the data from all of his stuff was on those thumb drives. And now we can't reanalyze. I was like, You're kidding me! She said “We had to go and redownload download some of it that he had published and put online.” So, so even top researchers didn't have a clue how to do this. And this wasn't that long ago. I would say that drug companies by now are mostly more savvy and certainly the commercial sector for data management tools is thriving, right? There are some really good commercial products.Rafael Rosengarten: Genialis has one. There's some others of note. And Big Pharma has invested a lot, obviously, in building in health solutions. But this creates another kind of complication, which is you get all these different solutions and they don't all talk to each other. Even having data on different clouds. Some people may use Amazon and others Google and others still, Microsoft. And those are the three majors. You know, those create silos in a way. So, so you know, the cloud has been super helpful. The advent of software purposely built for biological data management has been helpful. But, you know, there's still a lot of work to do. And I'm going to argue that the kind of next, let's not call it a frontier, but the next big challenge and the one that we encounter a lot, it's not even around the primary data. We're good now. We're good at sucking that off the machines and putting it in the cloud and organizing it and getting it processed really efficiently using distributed computation. Now the challenge is getting what we call the metadata, the annotations of where those data come from. Is it coming from patients and if so, what's the patient information associated with it? Is it an experiment? Getting those metadata consistently curated and attached and linked to the primary data is a big and very important challenge, and it's one that I think will be solved in a similar way through these software solutions. But it takes a lot of will and a lot of manual effort at this point.Harry Glorikian: Just to summarize, the software that you have is helping biologists and clinicians work with data without necessarily having to become a bioinformatician, if I had to frame it that way, is that is that a decent representation?Rafael Rosengarten: That is that's one of the softwares we have. So you're referencing Genialis Expressions, which was kind of our initial flagstone software. I'm excited, though, in November, at Biodata Basel, we launched our new software, our newest product, which is called Responder ID. And this is where our dreams of really applying machine learning and AI to these data have finally come to fruition. Responder ID is a software or really, it's a suite of technologies that we use on those clinical data and on those experimental data to actually extract knowledge and very specifically to figure out which patients are most likely to respond to certain therapies. And so the first piece of software is really the kind of about the data management. It's about getting data organized, getting it processed, all the best practices and efficiencies around that. And that was sort of, you know, I don't want to call it last year's problem because it's still a problem, but it was the first thing we did. It's where we started. And it's got some beautiful visualizations and it does let bench scientists like myself work with their own data. But the new stuff is where we're really bringing the application to bear on human health and on value propositions that I think really resonate with pharma, diagnostics, and other biotech and frankly, clinicians and and ultimately patients.Harry Glorikian: So, well, that's great, I mean, that transition to the new software, I must have missed that in when I was doing my research. I hadn't seen that yet, but what are some of the stories or anecdotes by customers that you can share? What have they been able to say, accomplish with it, so that we can put it into context for the listener?Rafael Rosengarten: Yeah. So you know, most of our customers are biotech drug companies and we help them solve a number of problems. But the key challenge is that drug development is just an incredibly risky and expensive and time consuming proposition. Most of our work's in the oncology space, not all of it, but it's a good place to make this example. The success rate of a drug that enters a Phase I clinical trial in the cancer space that actually makes it to market is something like three or four percent. It's dismal, and it's among the lowest of any therapeutic area. And there are any number of reasons for that. But the simplest, simplistic one is that biology is complicated and patients are diverse, right? Even within a single disease like, let's just say, breast cancer, there are at least four kinds of breast cancer. There are probably 40 kinds, and there are actually probably more than that. Each individual's disease is going to have its own unique flavors. And so what we allow a company to do, let's say a company that's developing a drug against, for example, breast cancer, is to really try to understand how many molecular types are we talking about, which ones are going to respond to our drug? And can we find those patients ahead of time? And what that lets them do is think about alternative and sort of novel and innovative strategies for designing clinical trials. It allows them, if they so desire, to think about partnering out on diagnostic development with third parties to actually create a diagnostic to go with their drug. That's not, obviously, necessary. You can you can build assays that you run in-house, but that's an alternative.Rafael Rosengarten: And to make it very concrete, we have one partner we work with a lot. A company called OncXerna Therapeutics. And with them, we've helped develop their first biomarker as part of their biomarker platform to the point not only of clinical trial assay, but also it's been licensed by Qiagen to be turned into a companion diagnostic for their lead drug and a research-use-only assay for scientists writ large around the world. And so, you know, this is a great success story. In about the course of two years, we went from taking a published academic signature, something in the literature—and by the way, there are about a million of these public academic signatures and there are only 46 approved companion diagnostics, so there's a big gulf between them—we went from an academic signature—and this was hand in glove work with them, so I don't want to take all the credit, but we certainly did a lot of the heavy lifting—and we built a category-defining first-of-its-class machine learning algorithm that learned a complex RNA-sequencing-based signature that predicts with uncanny ability patients that are going to respond to a wide array of drugs in a wide array of diseases. So it's pan-cancer, multi-modality, right? This is just it's an astonishing clinical advance, in my opinion, and it's something I'm clearly very proud of and willing to self-promote. But I do think it's an important advance, and I think it shows the power of both the Genialis philosophy around modeling biology and pairing patient biology with potential therapeutics, but also just what you can do if you're really thoughtful about getting the data in the right place, treating the data properly, and then using machine learning and some of these advanced algorithms to decipher.Harry Glorikian: Yeah, I mean, I think we're starting to get to that cusp of producing the data is getting faster, more cost effective. I mean, if Illumina actually gets down to, I think they, at the last JPMorgan, they said, we're trying to get it down to $60 for whole-genome. But at some point you're getting to numbers that are, I don't want to say a rounding error, but damn near close to that. And so the burden is going to fall on, how do I interpret all this data and what do I do next, right? What's actionable? I mean, I think the treating doctors are like, this is all great data, but tell me what to do, right? And it sounds like your new suite of software might be more applicable for a clinician or to to be communicated to a clinician, than just on the research side. So is is Genialis now moving beyond its original set of customers and moving more towards the clinical space?Rafael Rosengarten: I certainly think that's, on the horizon, that's something that we're contemplating. You know, the U.S. health system, well, systems, plural, is a complicated beast, right? And so there are certainly big companies that have products that are there for drug companies and products that are there for patients and products that are there for providers and so forth. And that makes sense. I think once you've got a wide enough kind of horizontal, you can stack all these verticals on top of each other. You know, hopefully we get big enough to do that ourselves. But you know, for the time being, we found this really, you know, this really great motion and success story working around certain therapeutic modalities for certain therapeutic opportunities. I actually think what may be the bigger prize is to take what we learn about disease biology from some of these diagnostic models and turn them on their head and say, OK, we've shown this model really captures patient biology and it works. And we know that because look, there are patients and they respond to the drug that we predicted they would. We've definitely cracked something there. Now let's take what we've learned about that patient biology and interrogate this model for new therapeutic opportunities. What about all the patients who don't respond to this drug? What will they respond to? The model still has them pegged as nonresponders. The model understands their biology. We just need to interrogate it for the next generation of therapies. And so I think this is where my vision of precision medicine maybe deviates. Diagnostics is an industry. Drug discovery are an industry. Those are separate companies. Those are separate industries. But to me, precision medicine shouldn't be this kind of linear thing where you start with the target, you end up with a drug and a diagnostic, and that's where it ends. It should be a circle. It should wrap around. And what we learn from patients should feed right into the next round of drug discovery, right? And so I'm interested in playing at that sort of fusion point where the where the ends of the string meet and form a circle. And so we're really interested in partnering and learning more about, for example, discovering new drugs to match the targets, right? And so I kind of see that as where a lot of Genialis's future focus is going to go. I'm not ruling out patient reporting software. I'm not ruling out more clinical products. That would be logical, but my real interest is thinking about helping the patients who just don't have therapeutic options today.[musical interlude]Harry Glorikian: Let's pause the conversation for a minute to talk about one small but important thing you can do, to help keep the podcast going. And that's to make it easier for other listeners discover the show by leaving a rating and a review on Apple Podcasts.All you have to do is open the Apple Podcasts app on your smartphone, search for The Harry Glorikian Show, and scroll down to the Ratings & Reviews section. Tap the stars to rate the show, and then tap the link that says Write a Review to leave your comments. It'll only take a minute, but you'll be doing us a huge favor.And one more thing. If you like the interviews we do here on the show I know you'll like my new book, The Future You: How Artificial Intelligence Can Help You Get Healthier, Stress Less, and Live Longer. It's a friendly and accessible tour of all the ways today's information technologies are helping us diagnose diseases faster, treat them more precisely, and create personalized diet and exercise programs to prevent them in the first place.The book is now available in Kindle format. Just go to Amazon and search for The Future You by Harry Glorikian.And now, back to the show.[musical interlude] Harry Glorikian: When I think about this and where we're going with this and the I hate saying it, butthe old dogmatic way of looking at it is very compartmentalized as we look at it in discrete pieces. And these data analytics platforms allow us to look at multifactorial, or almost turn the data into a living organism where we can look at it in multiple ways, and I think it's hard for people to get there mentally. I mean, sometimes, sometimes when I'm looking at something, I realize that my limitation is the information that I have about a particular area and that I need to learn something new to put another piece of the puzzle together. But I think this, let me do this and then let me do this and then let me do this. That's breaking down because of the data analytic capabilities that we're bringing to bear. Applying AI, machine learning, or in reality, sometimes just hard math, to solve certain problems, is opening up a wider aperture of how we would manage a patient and then treat them appropriately. And I think. Hell, I don't know, Rafael, I'm a little worried, I don't think the system is necessarily designed to absorb that next-gen opportunity, right? Because somebody will be like, OK, where do I get the information? Does that go in the EMR? I mean, wait, where is there a code that I can bill for it? I mean, there's these arcane roadblocks that are in the way that have nothing to do with, "I've got this model, and I'm telling you this will work on this patient," right?Rafael Rosengarten: Yeah, I don't know that I'm smart enough to know the solution to that. I will say that there are some really exciting newish young venture-backed upstarts that are interested in disrupting hospital systems, point of care, EHRs. All of that, is fair game, right? It is, as you described, it's just ripe for disruption because it's so, you know, it's so cobbled together, right? You know, I'm thinking about when my wife and I moved from Houston, Texas, to the Bay Area and then we got pregnant with our second child. We wanted to have all of our medical records from pregnancy number one sent from Texas Medical Center, which is one of the shining jewels of health care institutions, to John Muir Health System in the Bay Area, which, listen, they were changing out the wood panels from the 1970s during all of our doctors' visits. And literally, we asked the doctor if he could just print, print something for us. He said, No, I can't do that, but I could write it down on a sheet of paper for you. Like, you know, it's. But that's that's, you know, I agree with you. There are going to have to be changes top down, bottom up, and there's going to have to be hopefully support for this in the regulatory bodies, you know, at the governmental level. Rafael Rosengarten: Where I live and breathe, those is really kind of in a life sciences sector of the health care system. So again, we're interested in in drug development, we're interested in diagnostics, we're interested in drug discovery. And those themselves are kind of big things. So where I think about changes and regulatory and systemic stuff is more along, like, what is the FDA doing to to adopt or adapt to these kind of new technologies? What about standards like how are we thinking about data standards, model standards? Genialis is a founding member of and I'm on the board of directors of the Alliance for AI and Health Care. And this is a really exciting and rather amazing industry organization that was stood up at JP Morgan in 2019. And you know, we've got gosh, I don't know what the headcount, the member number now is, but over 50 member organizations, including the likes of Google and and Roche and bigs like that. Some of the more household names in the smaller biotech community like Recursion Pharma, In Silico Medicine, Valo Health, et cetera. And then and then companies like Genialis as well. Big academic centers. So we have a real great brain trust and we're interested in tackling, I'm going to call them, these hard, boring but incredibly important systemic questions around regulatory and standards and so forth. Health insurance, Medicare, all that stuff is a big fish, and we haven't, you know, we haven't set our hooks in it yet, but you know how hospitals bill and those kinds of codes, we'll have to have to revisit that at some point, for sure.Harry Glorikian: Yeah, I know that you're a member there and sort of interesting to hear why you got involved in how you see it working. So if you think about the standardization side of this, you know, what is what is the organization sort of advocating for? Because I totally agree with you, but at some point, I think you almost need to reach back towards, how is somebody doing an experiment to make sure that then the data comes out the other side in a standard way, right? Because I used to joke, which sample prep product are you working with? And I could tell you sort of what direction something is going to lean. And that that in and of itself is a problem. So how is AAIHC thinking about some of these problems, I don't know if there's a proposal. What have you guys proposed so far?Rafael Rosengarten: That's a great question. So we have workstreams around things like the FDA, working with the FDA to propose guidance for a good machine learning, practice guidance for software as a medical device, AI as part of software, as a medical device. So a lot of this, it's less concerned with can we rein in and constrain the experimental part? Because again, that's that's a huge world. And maybe it's not really where the constraints need to be. But rather can we come up with a common set of guidelines for how you evaluate the quality of a data set, right? Recognizing the data are going to come in a lot of shapes and sizes and flavors, and even two different RNA sequencing data sets that are produced on different machines or with different kits may have slightly different flavors or tints to them. That's fine so long as you have some guidelines for characterizing those differences, for appreciating those differences and then for knowing what to do with the data, given those potential differences. A lot of the concern around AI in a regulated setting is that, the whole promise of a machine learning approach is that it gets smarter the more data it sees, right? So these should be, these algorithms should evolve in a way they should be living and breathing. But if you have a regulated product that's to work on patients, it's got to work the same every time or, you know, can't get worse.Rafael Rosengarten: So this is, there's a tension here, but it's not unsolvable. It's not insurmountable. For example, you know, a regulated AI doesn't have to evolve in real time. It can be updated over time, right? Right. And it can be it can be locked and then operate, and then you can improve it and update it and redeploy and relock. So building the plans, what are the change plans? How do you demonstrate that the retraining or the improvements are actually improvements? These are the kinds of things that at least we can sink our teeth into today. And then we're also interested in the standards problem. I think the organization is not necessarily going to be dogmatic about recommending exactly what the standards are today, but what we're trying to catalyze those discussions, right? And we're trying to create frameworks where those discussions can actually lead to some actionable tools. And there are examples of organizations that have done this in other fields. So we do have some blueprints. But it's a lot of work. And frankly, that's the privilege of being in the organization. It gives you the opportunity to roll up your sleeves and build the industry of the future, to build the industry you want to operate in.Harry Glorikian: Yeah. And this has got to be in lockstep with the regulatory authorities and everything to make sure that everything is, everybody's on the same page so that when you come up with a golden solution, they're ready to accept it. Because we can't have, you download the latest software for your phone and then it breaks, right? That's not an acceptable update that you can do, right, and somebody has to release a patch to get it to fix. You know, that's that doesn't necessarily... I'm sure it happens in our world, but it's. It's really not what you'd like to see happen.Rafael Rosengarten: Yeah, yeah. You know, I can tell you from having had to invest in a lot of the kind of procedures around clinical reporting in software and so forth, and, working with some really top tier point of care software providers, it's not foolproof. But boy, there are a lot of hoops to jump through, right? Like things do get tested the whole way. And I would just, I would argue, although, you know, let me not be overly full of hubris, that there are plenty of other failure points that are a lot more likely to fail than the AI software that's predicting a biomarker not working in a particular instance, right? Given the room for error in things like biopsy collection and human handling. There's a lot of stuff upstream of that where human error is more likely to play a part. That that may or may not be sweet solace, right. That might not help you sleep at night. But I think that the regulated environment, especially around regulating computational tools, can be rather bulletproof.Rafael Rosengarten: So is there anything else going on that at Genialis that that we would want to know about that and directionally or what's next, that you can [share]?Harry Glorikian: Yeah, I mean, the exciting stuff is really twofold. It's, you know, just going deeper with our partners, right? So clinical development, as I mentioned, is is a long game. And you know, we like to start working before the drugs in the clinic, right? So these are meant to be long partnerships. And the other piece of this is we're doing a lot more internal R&D. A lot more internal R&D, a lot more work with our academic colleagues. And so we're really, really excited to just, you know, to innovate our way out of some of these hard problems.Harry Glorikian: Well, that's necessary in this field, right, you're always going to run into some, I like to call them speed bumps because I don't believe that they're like insurmountable problems, but they're speed bumps that you need to like innovate over or around.Rafael Rosengarten: Mm hmm. Yeah. So, you know, I want to give you something meaty like, you know what to look for from Genialis. So, sometime soon, my hope, knock on wood, is that we'll have first patients enrolled in clinical trials that are the biomarker I described to you earlier. This is the OncXerna trial. First patient enrolled, that's going to be super exciting. It's a Phase III trial and we're going to be stratifying patients with the biomarker. I mean, just the gratification of actually having our technology potentially impacting outcomes is huge. We've got a lot up our sleeves in terms of internal development improvements to Responder ID, but also, you know, some biomarker work we're kind of doing for ourselves, digging deeper into some pernicious problems in cancer that others haven't adequately addressed, in my opinion. And some some exciting partnerships, hopefully around, kind of…. we'll call them data partnerships. We talked a bit about just the scale of the data challenge, though, is it lives all over the place, right? And so there are different ways of getting your hands on it. And one of the ways a lot of companies have gone about is to become the testing companies, right? There are some giants out there that sequence literally millions of patients a year, and they've got big data warehouses, right? We haven't done that ourselves. And so we rely oncollaborations for a lot of our data. Not all of it, but we're building some of these collaborations, and I'm hoping we can talk more about that in future episodes or in other forums.Harry Glorikian: Just for a second, so people understand the magnitude. This Phase III trial, how many how many patients would you say are in it?Rafael Rosengarten: I need to be super careful not to misrepresent someone else's trial. It's going to be on the order of several hundred. You know, it's a properly powered Phase III and it's got two treatment arms. And so, you know, so it has to have quite a number of patients. And that's, you know, I would say that's a typical sized trial of for this stage in this kind of disease.Harry Glorikian: Yeah, I just want people listening to sort of get an idea of like, these technologies are, you know, can affect lots of people and then if that drug comes through and then the technology is utilized afterwards to sort of stratify people or the biomarkers, then there's an even larger population of people that then gets affected by the work that you guys are doing.Rafael Rosengarten: Yeah, yeah. I think that's right. And you know, in a way, you know, our commitment to the sort of biomarker driven, you know, drug development, it's very principled. It's based on this idea that patients deserve to have the best treatment option, right? And there are some amazing drugs out there that when they work, work miracles. But they don't work that often. Right? And some of these drugs have, you know, first line approvals in dozens of diseases. But again, in some of those diseases, they work for half the patients, and that's great. And that's probably how it should be. But in some, they only work in maybe 15 percent of the patients or 20 or whatever the threshold is, because they were better than the alternative, right? But if you could tell which of those patients are going to respond, then at least the ones who aren't can seek other options. Or you know that we've got to develop drugs for the others. So it's very principled, although it's complicated because from an economic standpoint, if you have the ability to sell your drug to everybody, of course you're going to do that.Harry Glorikian: Yeah, look, I drank that Kool-Aid. I mean, Jesus, 20 years ago, right? I mean, you know, why wouldn't you want...I mean, if you were a patient, you'd want the best drug you can get, right? Because the data says that you respond to this particular drug. It's getting the system to that point. And I have seen, I have had stories where the data said one thing. They put the patient on it. They looked like they were responding. A new trial opened up. And somebody suggested that they go on the new trial, even though the therapy was working. And they switched and the outcome was not positive. Right. And so it's one of those things of like, I don't understand. The data clearly pointed in a particular direction and you deviated from that, and that doesn't make any sense to me. As a science person is as well as an investor, if the data is showing something, you better respond to the data or you're not going to be happy with the outcome. It's just seeing that implemented in a way that makes it very actionable for everybody, and they embrace that. That's where I sometimes, I find, you know, the biggest problems. But I totally agree. I mean, I have a whole chapter in my new book about that whole dynamic of why you want the data, how the data impacts you as a patient. What are the sort of questions you should ask, et cetera, because if you don't have that information, you're making suboptimal decisions.Rafael Rosengarten: Yeah. No, and that's absolutely right, I think the point you make there is probably the key one, which is a lot of biotechs and companies like ours, we operate with kind of a world view of our own research and our customers'. But we have to remember that the reason we do this, the reason we get up every day and the reason we toil is it's because we can impact patient lives. And if you actually want to really foment that change, then that subset, that stakeholder, needs to be involved, right? A patient needs to understand what are my choices? And so if a patient comes into the clinic and has a grave illness and the doctor says, well, this is the approved drug, but there's a test that could tell you if there's something else. I mean, if I'm the patient, I want to take that test. I want to know what my options are. And I think that frankly, it's unrealistic to expect publicly traded companies to not try to maximize revenue. That's just kind of the system we live in. But it's also incumbent upon us to to engage patients, to help them understand what their options are, to engage physicians the same and to say, there are multiple approved drugs, maybe, or this is the one, but there are some investigational drugs that haven't been approved yet that may be better fits for your disease. Remember, your disease isn't necessarily the same as someone else who happens to have it in the same tissue. And so I think that's a big deal, and I do think that there are any number of exciting organizations that are really focused, doggedly focused on this point of patient engagement and especially patient engagement around data.Harry Glorikian: No, I mean, I always I tell every one of my guests, “Hurry up, go faster,” because I'm not getting any younger and theoretically like, you know, statistically, I could end up in that place. I want the best that I can get when I get there. So Rafael, I know it's getting late where you are. So really appreciate your time and the opportunity to talk about what you guys are doing and the impact that it's having on not just drug development, but downstream on patients.Rafael Rosengarten: Well, thank you, Harry, for having me, for giving me the opportunity. This has been a lot of fun to connect over this.Harry Glorikian: Excellent. Thank you. Harry Glorikian: That's it for this week's episode. You can find past episodes of The Harry Glorikian Show and the MoneyBall Medicine show at my website, glorikian.com, under the tab Podcasts.Don't forget to go to Apple Podcasts to leave a rating and review for the show.You can also find me on Twitter at hglorikian. And we always love it when listeners post about the show there, or on other social media. Thanks for listening, stay healthy, and be sure to tune in two weeks from now for our next interview.
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Rapid and cheap DNA sequencing technology can tell us a lot about which genes a patient is carrying around, but it can't tell us when and where the instructions in those genes get carried out inside cells. Resolve Biosciences—headed by this week's guest, Jason Gammack—aims to solve that problem by scaling up a form of intracellular imaging it calls molecular cartography.Gammack says the technology offers a high-resolution way to see the geography of gene transcription in single cells, that is, where specific messenger RNA molecules congregate once they’ve left the nucleus. The technology can trace up to 100 gene transcripts simultaneously. 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Resolve reportedly plans to launch its service commercially in the first half of 2021.Gammack joined the company from Inscripta, where he was chief commercial officer helping to sell the CRISPR-based Onyx gene-editing platform. Before that, he was at Qiagen, a German provider of assays for molecular diagnostics such as a Covid-19 antigen test, where he was vice president of life sciences. Please rate and review MoneyBall Medicine on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:• Launch the “Podcasts” app on your device. If you can’t find this app, swipe all the way to the left on your home screen until you’re on the Search page. Tap the search field at the top and type in “Podcasts.” Apple’s Podcasts app should show up in the search results.• Tap the Podcasts app icon, and after it opens, tap the Search field at the top, or the little magnifying glass icon in the lower right corner.• Type MoneyBall Medicine into the search field and press the Search button.• In the search results, click on the MoneyBall Medicine logo.• On the next page, scroll down until you see the Ratings & Reviews section. Below that, you’ll see five purple stars.• Tap the stars to rate the show.• Scroll down a little farther. You’ll see a purple link saying “Write a Review.”• On the next screen, you’ll see the stars again. You can tap them to leave a rating if you haven’t already.• In the Title field, type a summary for your review.• In the Review field, type your review.• When you’re finished, click Send.• That’s it, you’re done. Thanks!TRANSCRIPTHarry Glorikian: I’m Harry Glorikian, and this is MoneyBall Medicine, the interview podcast where we meet researchers, entrepreneurs, and physicians who are using the power of data to improve patient health and make healthcare delivery more efficient. You can think of each episode as a new chapter in the never-ending audio version of my 2017 book, “MoneyBall Medicine: Thriving in the New Data-Driven Healthcare Market.” If you like the show, please do us a favor and leave a rating and review at Apple Podcasts.Harry Glorikian: We’ve come a long way in the last 25 years in our ability to sequence the DNA of individual patients. We can even see which genes are being expressed as RNA, the instructions for making proteins. But after that there’s a big blind spot in our understanding, because it’s still hard to see exactly which RNA molecules inside our cells actually get translated into proteins, and just as important, when and where they get translated. The problem is that almost everything that’s interesting about human biology and human disease happens inside that blind spot.Resolve Biosciences in Germany is one of the new biopharmaceutical startups tackling that challenge. My guest this week is Jason Gammack, the CEO of Resolve, and he says the company has come up with a way to label multiple RNA molecules with probes that glow in different fluorescent colors. Resolve built software that can decode the color patterns to see where RNA transcripts gather in the cell and how they’re involved in cell development. That kind of location information that could eventually produce a better picture of how normal cells grow, and also how that growth becomes cancerous and maybe even what kinds of drugs could stop tumors before they kill their hosts. Gammack joined the company last year, around the same time the company announced a 25 million dollar funding round to help bring its so called “Molecular Cartography” technology to market.Here’s our conversation.Harry Glorikian: Jason, welcome to the show Jason Gammack: Harry, it's great to be here. Thank you. Harry Glorikian: It's been great talking to you and getting to know you. I feel like we should be doing this over a beer and we should be talking for hours. And my I'm sure, my 19 year old would be like, do you want to go to Germany? Let's go to Germany.Cause he loves coming there and having beers when, when when we've done it in the past Molecular cartography. I feel like, you know, Galileo is about to like, you know, step into this conversation with us, but for those people who don't, who aren't molecular biologists, it it'd be great. If you could sort of paint the bigger picture for us and, and help us understand what is, what is this concept of, I think spatial transcriptomics. I almost like stuttered on my words. And why is it important?Jason Gammack: Yeah. And so it's a great question Harry. And so again, thanks for the invite to join the the podcast. So context matters. Let's start with that statement, reading a book without understanding the context makes it difficult book to read.And if you think about our genome, the DNA that makes us similar and unique, it's a book. And right now we don't have full context of what that book is and Resolve Biosciences is a company, that's focused on creating tools to help give context to the genome. And so let me explain that a bit. So the central dogma of biology is DNA.Which is in your cells is made into RNA and that RNA is then translated into proteins and those proteins are in essence. What makes you, you, it's your muscle? It's your hair? It's your skin. It's your organ systems. It's a lot. And we understand the book pretty well from the letters, a C, G and T. And we've been in an exponential phase of learning as it pertains to the genome and companies such as aluminum.It's a San Diego based biotech company has created a technology that allows us to sequence the entire human genome. So every letter in your genome, We can do that now in a couple of days and for a couple of hundred dollars and we need to keep that in context, you know, the first genome took…Harry Glorikian: I remember yeah. Jason Gammack: 15 years and $7 billion to do it. As a matter of fact, you know, this is the anniversary of that event happening, right? Harry Glorikian: Yep. Jason Gammack: So we've really learned a lot about the core code of the genome. But the disease, chronic disease still exists in our population. And so we have to ask the question, what else do we need to understand? And we at Resolve believe that the next question is really to understand where different genetic events are occurring within a cell.The interesting thing. And the big question in biology is largely we all have the same DNA in our bodies. You know, humans are remarkably, remarkably homologous and the variation in humans is very, very low, but yet we have individuals who are six and a half feet tall. We have individuals that are four feet tall.We have individuals that way, you know, 250 pounds and we have individuals that weigh 90 pounds. And so why. And even more perplexing is we have diseases such as cancer, where two women, can you present with a very similar breast tumor one, or they both can be treated with a very similar treatment, identical drops, and one can go into complete remission and eventually be here and the other cannot and potentially die. Harry Glorikian: Right.Jason Gammack: And so the question is why does that happen? And that has to come down to a number of different variables that we can't yet measure. And so our belief at Resolve Biosciences is we are going to develop tools to help understand those differences. And that's really urgent.Harry Glorikian: So let's, I mean, I'm trying to paint a picture for people that are listening to this. Right? So I think of this as, cause I feel like I've been to at least part of this movie before, when I started in immunohistochemistry, where we could actually visualize, you know, rather than grinding up a bunch of cells and looking at the moles and, you know, in breast cancer, we were able to actually stain the cells with antibodies that would specifically show us, you know, different parts of a cell that were lighting up. And that was, you know, sort of a flat file way to look at it with a certain level of resolution. And you're, I think, zooming in to the molecular level now and taking it to a different resolution. Jason Gammack: Absolutely. So that's a, that's a great point. And let me build on that one just a bit. So immune histochemistry opened the books to understand different types of disease status, where you can start profiling cell types and understand where they are in the cell cycle, which can be indicators for physicians or the biologists to prescribe a particular therapeutic. Right. We take that even to another degree.I'll use an analogy. It's perhaps overused, but think about Google Maps. So Maps allows you to start at the continent or global level, and then focus in to this country. You focus it into a state, focus into a city, focus into a stream and even focusing. So our technology and the molecular cartography platform is similar in that we can take single cells or we can take tissues license and through our molecular biology approach, we can label individual RNA transference. So going back to that: DNA makes RNA makes protein. We can go in and identify specific RNA molecules, that code for a known protein. We can label those molecules and with high power microscopy and molecular biology and very importantly software, we can then identify and literally visualize individual RNA transcripts in the context of the cell and tissue.So now going back to that Google Maps analogy, we now have that woman who has the unfortunate breast tumor. We can put sections of that breast tumor on the slide. We can use our molecular cartography technology to be able to look at the gene expression patterns within that tumor. And those patterns can give insights to researchers and eventually to clinicians in how to affect and treat that disease state very, very possible.Harry Glorikian: So I, I, we're talking about essentially creating a three-dimensional map of the cells and which ones are lighting up, which ones are not lighting up, how they affect each other, basically intercommunication between these cells, Jason Gammack: And intra-communication inside the cell as well. Harry Glorikian: So, so. Where, where are you? How far are you in this? I guess is the first question. Jason Gammack: Yeah. Good question. So this journey didn't just start. And so this journey started in 2016. When we at a previous company thought about this challenge of spatial loud. Again, you know, we have sequence genomes, but yet cancer persists in the population. And we were asking questions.What's the next answer that needs to be brought to science. And so in 2016, we brought together a truly gifted group of scientists to come up with solutions, to be able to look at the spatial relationship of gene expression within cells and tissue. And since the 2016 inception of the project, we've now been able to take bench science and automate bench science to the point where we can now run hundreds of samples, looking at thousands of genes in a fully automated process. So you're building on this existing technique of single Mol, single molecule RNA for essence. Right. And so, and this is, I don't. No, it's nothing new, right?This is a technique that's been out there. I guess the question is, is what are the fundamental advances that resolve is bringing to the table or your version of. This, that that is uniquely powerful. Yeah. So so as you said, our technology is what's generally referred to as a single molecule FISH technology, fluorescent insight to hybridization, which means we label RNA with a four or four, and then we can image that RNA using high power optics.And so there are numerous approaches to look at labeling RNA and there are numerous challenges in doing that. We have come up with a novel. And of course, because we're a biotech company, a patented process,Harry Glorikian: Ha ha. Jason Gammack: We have a process that allows us to through combinatorial. Labeling of the RNA allows us to identify very diverse RNA. Because the challenge is, is that when you want to label something, you have to attach a protein to, and then the genome or the transcriptome, there's a lot of repetitive sequences that are similar and you need to be able to discern the difference between GNA and GB.And they could be very, very homologous or very, very similar. Our technology allows us to use small, but very different probes to tile across that, that target, that RNA of interest. And then by selectively colorizing and D colorizing, those proteins, we create an essence, a color pattern. And that color modernize image, and then we'll use software to deconvolute or decode those images.So we can then see individual transcripts within the cell. Harry Glorikian: It's funny. I feel like my, you know, history has a way of building on itself. I mean, I remember when we were doing DNA in situ hybridization and trying to convince people that this was going to be something and then. You know, molecular barcodes when I was at Applied Biosystems. So this is the culmination in a, in a sense, an advancement, obviously because of software and imaging and those sorts of things of this next stage of where this technology is taking us. Jason Gammack: Indeed, indeed. I think that's a great analogy. Right? Great example. And you see this kind of. You know, you see this, this trajectory of single cell biology and, you know, transcript elements is a great example of that.You know, we started with RNA, RNA, blondes doing what's called a Northern Burlington, you know, in grad school, we're doing Northern blots where we need to use it. The RNA within the Northern block, I still have all my fingers, even with all the isotope I used in grad school. And so you've gone from very crude techniques to a much more refined technique and Illumina through their next generation sequencing brought on an amazing technology called RNAseq or RNAC.Of course RNAC, kind of back to your earlier analogy is you grind everything up and then you read all of the transcripts. The problem is, is you don't know what transcript came from. Like you know, you just got this huge mess of transcripts and you've got to kind of say, well, this is a transcript that's associated with this gene and that genes associated with this kind of cell type.And then a couple of years ago, a company called 10X genomics came up to take single cells. So instead of had that, say that fruit smoothie with everything ground up, they took the piece of the fruit and just kind of laid them out of the line and what they oxalated the cells into a droplet. And then did the sequencing reaction in that droplet.You still have a kind of a mixed population there. And then through software, they would separate out the different stuff. We now take that to the next, next level where we just look at the fruit salad instead of that food smoothie or the windup fruits. We can now look at the fruit salad and we can say, Oh yeah, cantaloupe was touching an Apple, which is touching, you know, orange and orange are next to each other.The fruit salad falls apart really quickly. Going back to the analogy of breast cancer. When we have these interactions, these patients don't survive. So maybe we need to look differently at the drug that's targeting that interaction. So that's how we want to think about these problems. Now we can move them forward.Harry Glorikian: Well, like you said, I mean, context matters. Location matters, right? As, as a guy who's got IP and location-based services, location is a big deal, right? People don't realize everything revolves around location. At some point. And having context to, it really adds another dimensionality of information that all of a sudden your eyes open up to what could be going on or why something matters for sure.Jason Gammack: And this is, I mean, and again, I keep going back to the oncology use case, but you know, oncology is a blight that is all over the world and affects all human beings at some point. And the concept, you know, a tumor is not a homogeneous massive cells. You know, tumors are heterogeneous. The cells that are in the interior of the tumor are different than the cells on the exterior of the tumor, the blood vessels that innovate the tumor look different than blood vessels that are adjacent to the tumor.And we call this the tumor microenvironment. What is going on inside that too? And, you know, coming up with a drug that can just permeate the tumor and kill it from the inside outage, whether it's hypoxia and you started of, of oxygen. So it can no longer grow or maybe encapsulating the tumor. So they can't grow and dies outside in.We just don't have a lot of visibility right now to the genetics that's happening within that micro environment. And this is an area where molecular cartography just shines a spotlight onto that tumor microenvironment. Harry Glorikian: Well, I'm also thinking, as you get to know these different cell types in the call, it the color pattern that they're giving, you can almost create a fingerprint.Jason Gammack: Absolutely. Yep. And this is the thing about the molecular cartography platform. I mean when you think about kind of science and you look at the different areas of science on one side of the spectrum, you have the basic science research. This is the hypothesis formation. You just don't know what's going on and you have to do experiments and you're continuing to refine and develop a hypothesis on the opposite side of that.Spectrum is clinical testing. When you're looking for a yes, no, almost a binary type of answer. Right? And the stops between, there are areas such as translational research where you take your hypothesis and you refine it to a use case that's specific to a disease. Right. And then from your translational research, you move to clinical research where you're really applying the hypothesis of large populations.Harry Glorikian: Yeah. But, but let's, let's let's and maybe agree to disagree or just agree. But I remember that taking. Dog years, like in, in the old days. Right. And I feel like because of innovation, because of being able to do the analytics on technology, you know, on the, on the data that time is almost collapsing in on itself.Jason Gammack: It is. Harry Glorikian: You know there are advancements that seem to be, I'm having trouble keeping up with the literature. Jason Gammack: For sure. There's no question about it. There's no question about it. The rate of sensitivity innovation, you know, it's like Moore's law backwards, right? And mean just kind of continue to, just to, you know, keep, keep accelerating, accelerating, accelerating, and you know, tools.Again, going back to the next generation sequencing has provided so much data that we're still behind when the data backlog and understanding what exactly these data are going to say, but, you know, the iterative cycles are becoming faster cycles. As new tools come online. You can really test them and tweak and adjust your hypothesis at a scale that you haven't been able to do before.But at the end of the day, you still have to get a patient population and you have to get a patient population that all exhibits the same thing the time. Right. So there still is massive inefficiency within, within the discovery special drug discovery process. Technologies like molecular cartography can help again, collapse some of those inefficiencies as well.Harry Glorikian: Yeah. I mean, but if you think about like you know, at JP Morgan, they announced a Illumina announced, like we're going to take sequencing down to $60 is our goal, like at 60 bucks, it's a rounding her, like, why wouldn't you. Why wouldn't everybody like if you had, yeah. Jason Gammack: So Elaine Mardis, who is a true thought leader in the world of genomics, she previously was at Wash U. Really at the tip of the spear in cancer genetics. She said a statement once like, I still remember it, it makes me smile, you know, it might be the thousand dollar genome, but it's the a hundred thousand dollar analysis of that genome. Right. And so, so like we can… Harry Glorikian: I'm just looking at so many things right now from an analytics perspective that are even making that easier.Jason Gammack: Sure, no question. I mean, again, the machine learning is helping us sift through reams of data, understand what's not important and what is important. And with all of the data that's being generated, you have huge training sets, right? Massive training sets algorithms. And you've seen success in a lot of, a lot of areas. You know, look at companies like Flatiron and look at companies like Foundation Medicine, right. You know, I think that, that, you know, Foundation Medicine is a brilliant example of a big data analytics company, masquerading as an asset company, right? Harry Glorikian: Yeah. I mean, and it's the same thing I was talking to Joel Dudley over at Tempus and, you know, they're planning on being, not just having the most information across different methodologies, right. Transcriptome, methylation, et cetera, from every single sample. But yeah. They're also creating the piping to be the AWS so that why would you go any place else, but their platform. So they're not just giving you an answer. They're giving you a whole infrastructure, which is that doesn't sound like a typical biological company. It sounds like a tech company to a certain degree. Jason Gammack: Well, I mean, you know, the lines blur very, very quickly. You know, I look at, at what we are doing at Resolve Bio-sciences and I have as many computational scientists, informaticians bioinformaticians as I do wet lab biologists, because you use the overused analogy, you know, data's the new goal, right? Maybe they’re able to dig in and understand what's going on, but we need to also help our customers understand these complex data sets that we generate. Harry Glorikian: Yeah, go and try and explain that to all of our brethren. Jason, come on. I mean I mean, I was, I was on a call, you know, last night where, you know, everybody's deep into the biology. I'm like, I think you guys are missing this other thing. That's moving like a freight train, right. That that's changing. And the interesting part is, is when I'm interviewing people, is the data is highlighting some things where even the world expert goes, yeah, I would have never thought about that. I would've never looked at it that way had it not been highlighted to me by this system.Jason Gammack: Indeed. Indeed, indeed. You know, you're, you're describing you know, I love. When my customers see the data for the first time that comes off the molecular cartography platform. I really like to be with them. Unfortunately, coronavirus today, being with teams by prefer to be at home.Because most, everybody has a very, very similar response where you watch them and they have a hypothesis in their head and they're looking for the data that will be the hypothesis, right. Go to the image. You can see them scan the image, looking for something, and then almost uniformly. I hear this "huh." Just that little breath as they breathe in.And they're just like, Oh my gosh, there's an answer. And then we showed them some bioinformatic tools to start looking at the day, then in a different way. And then you see that kind of sit back and go, I get it. I get it. Harry Glorikian: Well, that's what I mean. It's funny because I was trying to write this book and I think I'm going to have to leave it to the, to the next one you know, before this third one or after this third one comes out is I think the whole paradigm because of the analytics we can do is being shifted in the reverse. In other words, it's almost like the machine should present something that then you can figure out where you should develop your hypothesis as opposed to develop the hypothesis, because there's just too much data to analyze. Right. Jason Gammack: I'm just smiling because I have, so I think about developing software and I've been developing software in life science for much of my career.You know, there's a couple of pillars that are important in my view, in software development and the features you bring into software. One of those pillars is transparency. You know, black boxes don't go far. And science scientists by definition are technologists. They want to understand the knobs and the dials that are under the hood, less than themselves, the advanced ones want to be.They just want to understand, you know, where are the limits? What are you calling? What are you not competent? But the other element, and this is an element where I think the industry has largely missed and you're hitting on Mike here is the concept of guiding. The concept of guiding the customer to insights and outcomes.And even if you're wrong and your guidance, you're stimulating that scientist to think because of that, that scientists may not have thought about that hypothesis or that answer. And so by proposing the next step by proposing how that hypothesis could be tweaked, you're stimulating thought that may not have previously existed.And I find this to be a very, very powerful tool. And this is where, you know, tools like artificial intelligence and machine learning are critically important because you need those non-biased systems to come in and start looking at the data and making calls. And then you use your bias system, the gray matter to judge those calls and challenge your thoughts. Harry Glorikian: Well , yeah, but that's not the way that we're taught. Right. We're supposed to go in with the answer, go in with the miraculous hypothesis of this is absolutely going to change. And I just find, you know, predicting the weather. I mean, there's just too many factors for any one human being to go like, you know, that's the trigger.Jason Gammack: Absolutely. Harry Glorikian: So let's get back to the, to the technology, like your technology. Like I think I remember reading, it's like a 0.27 micron resolution, which I think is if I read correctly 10 times higher than some of the competitors. How do you, how do you you can't tell me the secret sauce, but how do you get to that sort of resolution? It's gotta be a combination of hardware and software to a certain point. Jason Gammack: I mean, our, our resolution limit is the diffraction limit of light and the diffraction limit of light being again, we image individual RNA transfers. You know, these are very, very small, couple of hundred base pair, a couple hundred nucleotide pieces of genetic material.And so our resolution allows us to discriminate two dots, two different transcripts that are sitting close to each other at that 0.27 micron range, which again is the, the limit of light to be able to separate those two photons from themselves. And so we are pushing the absolute edge of optics, the ability to detect these events.There are other techniques that we're exploring that would allow us to even go beyond that like super resolution microscopy. But with that there's trade offs, of course, as you zoom in, you lose larger fields of view and you got to kind of manage that. And the analogy I use is squishy squishy on the one that pops up on the other and vice versa.Harry Glorikian: Yeah. You almost wish you could layer them on top of each other and create the zoom we were talking about with the Google map. Jason Gammack: Yeah, I mean, so, in essence,, that's what we do. So we, we take a slice or cells that are on a slide you know, and we image through that individual cell later. And we stopped at a very, very fine fence license.So, you know, when you fix the tissues of the slide, you're looking at micron thick tissue stacks on top of that. So yeah, you can, then you can actually see when we image the top of the face explore and kind of like, as you think about a basketball, right, as you slice through the basketball and we see the dock, when it's really small, we see the doc, if it gets larger than it meets its maximum, that goes back down to it's intimidating.Harry Glorikian: I always have a vision. When I, when I talk to people about these technologies that sort of create the maps is you know, wearing a VR lens and being able to like, look at it spatially, which would be I've. I've tried to encourage a couple of other people and some of the companies, you need to have some of your cause you might see something through that then you might not see through a normal methodology Jason Gammack: There's no question about it. And the other thing that we need to keep in mind and, you know, as a 50 year old scientist, it's difficult to always think about who my customers are, which are non 50 year old scientist or the postdocs and grad students that are going to become the next leaders in science.You know, everybody talks about digitization, you know, that's kind of granted that things are moving to digital. But we can't ignore macro trends such as augmented reality and virtual. Right. That's even, even me being a dinosaur, I've got an Oculus, of course I have a nine year old and 11 year old as well.I, at one point in my career, I worked for a company called Sigma Ulrich. Cigna is now owned by Merck. But Sigma Ulrich was a leading company in fine organics for industry, you know, high throughput, you know, synthesis of, of pharmaceutical compounds. And 20 years ago, you would walk into the chem informatics suite and you'd see people with these huge honk and goggles on, as they're looking at structure function, relationships, they've got molecules.How do you dock molecules on the proteins. Biology surprisingly hasn't kept up, you know, how many biological tools are using augmented reality, virtual reality, right? Harry Glorikian: No, I know. I mean, I've been, I've been attending and going to different talks from the tech world, right? The entertainment world. Right. And looking at the boundaries they're pushing, and then imagining that in our world, the opportunities are mindblowing.Jason Gammack: They are. Harry Glorikian: It's just our world doesn't think about it that way. Jason Gammack: But when we think about again, the molecular cartography platform, so, you know, why did we call them molecular cartographer? Right? The cartographers were the explorers of the new world. Yeah, they were the folks that went out and map the world so everybody could follow behind and find the riches, the land, the bounty, and so on.So when we think about how we want to build a map, if we really think about building a map for a single person, we're losing that race and tools like augmented reality and virtual reality have future in our technology. And Harry, and I see a day and not far away where not only will we be able to look at these beautiful images that we create in this three dimensional space where you can sit, put your goggles on and look around at your Sunstone, your restructuring yourselves, and see the transcripts.But more importantly, my collaborator in Zurich can join me on that journey. And we can collaborate, you know, virtually, but yet looking at a actual scientific experiment underway, you then take that to the next level and get into therapeutic approaches or clinical approaches where a pathologist and a general practitioner can explore the tumor biology of the patient.It is a complete paradigm destroying proposition.Harry Glorikian: Well, I'm also, I'm just thinking about man, if you put that into the education system in a different way to have people look at this, right. As well as super-imposed tools from, you know, the artificial intelligence world to sort of highlight different things that the machine might be able to, that that now you're talking about really seeing where you could drive diagnosis treatment, therapy, you know making new drugs or for that matter. I mean, you know, we have these big projects. I talk about thetranscriptome and the genome, but we should have one around this cartography area, although I I'm sort of struggling to figure out whether how consistent the map would be. Jason Gammack: Well, I mean, so the point is we build maps of every tissue type and every disease state.And this is where, again, the ability to harm it's software to help us interpret those maps is going to be critically important. So one element where we use software in our, in our workflow and machine learning is in identifying cell types. And so, you know, most neurons look the same or have a similar phenotype to those neurons.Yeah, right now there's inefficiency in a lot of biology because in essence, we use channels to identify a cell type and that channel was then occupied, identifying the cell type. What if we could free that channel out to identify more, say disease, specific genes. And so to do that, we need to still be alive, identify the cell type.So we need to train algorithms to be able to look at tens of thousands, millions of slices of brain. To be able to identify the neurons, the different cells within the brain, so that when we put it into a wind storm, we don't have to use a channel to identify a neuron. We use all of our channels to identify disease, state genes, and then we use machine learning and envision learning to be able to overlay, okay, that's a neuron because it looks like this and we've got 57,000 data sets that support.Harry Glorikian: It feels like facial recognition in a crowd. Jason Gammack: Yeah. You know, it's it, it is. And then we take it to another level when we now start phenotyping disease States. So, you know, we've just finished an early access program with the molecular cartography platform. And we looked at, you know, a number of different disease States.One of them being Alzheimer's disease, that's a disease my grandmother passed away from. And I'll tell you, I think most people listening to the podcast. I've had someone in their life who impacted by Alzheimer's disease devastating disease that steals the person in front of you. And, you know, we have been able to make mouse models that have, you know, 10 cow tangles and amyloid plaques, and we can demonstrate Alzheimer's disease, but yet, you know, as well as I nearly every company that's been in the phase three clinical trial for Alzheimer's drug has failed. Harry Glorikian: Yes. Jason Gammack: You have to ask why is that happen? Right? What are we missing? Even within those trials, people are looking at different approaches to address that. And so we partnered with a major pharma company to use our technology, to look at amyloid plaques in a way they haven't been able to do before to look at an amyloid plaque. And then as a, as a temporal spatial approach, being able to identify a plaque and look at the cascading impacts of different genes that are expressed in proximity to the plaque itself.To say, you know, right now we have been focused on the plaque. Well, let's take that spirit further and let's focus on the micro environment around the plant and understand what is causing the plaque to grow. What are elements, what are genes that are in play that we could potentially target from the therapeutic area that we see high levels of expression.What happens if we turn that expression down? Can we get that plaque to stop growing. More importantly, it couldn't get that plaque to actually shrink in size. And so a lot of these really interesting questions that previously were difficult to ask and answer our cartography platform is now allowing some unique insights.And so it's a great study. We're writing a manuscript right now, and I look forward to being back on the podcast talking about, so.Harry Glorikian: That'll be great. I mean, I, you know, I, I have talked to some of those companies and I think one of the biggest problems is. You know, the guy that looks at images is used to looking at images, the person that works in the assets, it's hard to get them to come into a room. And I, and I've seen them in a room. They still don't do the interactive discussion. Right. They don't, they're not using the machine learning platforms that I've seen to really bring together the understanding, which would then go to being able to segment the population. Because I think half the failures are we might not be subsegment thinking the population in the right ways. Jason Gammack: I think that's spot on. I mean, the ability to phenotype the population appropriately because of phenotype is still usually determined by a person, you know, and that's a physician well-trained, but yet there's nuance and especially in diseases.Like Alzheimer's that are highly nuanced diseases in different States. And so I agree, and I made the comment earlier about, you still have to get the patient population to study and you have to make sure you can properly identify that population. Harry Glorikian: So let let's jump back here and switch to a different gear that the story of resolve the story of Qiagen, your personal story They're somehow all. Intertwined. I feel like we know a lot of the same people that caused this intertwining to happen, but, but you know, how, how did you between the startup and you becoming CEO because you were an instructor and I think that was a pretty good gig. So how did this, how did this come come about? Jason Gammack: Yeah, no. So it's a great question. So, you know, again, I was at Inscripta, it's a fantastic company and just amazingly talented people working on some really cool technology that is going to drive sustainability in a way. And so for me to leave that, obviously we have a pretty compelling opportunity here. And this story started back in 2016 at Qiagen, when we were looking at trying to come up with some really unique science to solve this spatial challenge. We brought together a team of brilliant scientists to in essence, their only job was to figure out how do we create tools that really at this phase spatial context that started in 2016, we worked together as a team to develop that technology.I stepped away for two years to go to Boulder, Colorado, and stand up and sprint. Back in 2020, a pair of shots, the former CEO of Cajun and Michael, the founder said we got a union, got opportunity to Jason to build something really special. And, you know, it was one of those things area where I remember, well, of course we were all locked in our basements during the 2020 time.And I remember having a conversation with parents walking upstairs to to talk to my wife, Adeline. I said, I think we're moving back to Germany, I think.Harry Glorikian: And she said?Jason Gammack: And she said, hell yeah, let's make that happen. And so it's you know, Germany is a very special place for, for my family. You know, we lived here for five years. The first time my children moved to Germany. We made the choice to live in Germany, like a German. We have amazing friends here and our children went to school, a great school here, public schools, and speak German like native Germans. Yeah, we really discovered the heart of a, an amazing country and just gracious people and great scientists. You know, we're starting something unique here. There aren't, there's a lot of startups in Germany. The German startup culture is a very different culture than in the United States.And as I say about a lot of things, If we could meet halfway and be the perfect world, you know, to give you an example of when we're raising money for Resolve, we'd speak to American investors and it would be don't. You need more money. And we'd speak to European investors and they'd say, why do you need so much?So if you could meet halfway, sometimes the overexuberance of just throwing money at problems versus the conservative. Well, you know, let's do this incrementally and so on. You know, when we started Resolve, we had a choice to make doing, bring the business to the United States or do we grow the business in Germany.And we had a lot of discussion around that. And you know, for me, it was a very obvious answer. The answer is we take advantage of both worlds. So in resolved bio-sciences our corporate headquarters is in Germany and our product development center of excellence is in Germany because it's thinking about what our core technology is.It's molecular biology cooked to automation and engineering with optics and software. So I think we can all agree that the best physicists and optical engineers in the world reside within 500 kilometers of where we are right now, here in Dusseldorf, Germany, just amazing talent and companies that have created huge industries, such as CISE and Leica and so on are all based in Germany. Right? And that goes to, you know, the German engineering, German physics optics itself. Great molecular biologists. We've got amazing academic centers across Europe and bull, so on and so forth that develop amazing molecular biologists. And when it comes to our computational abilities, that's a global skillset.I've got a great development in Eastern Europe. I've got great developers in Western Europe and great developers in the United States. We're opening our office in the United States and San Jose, California, and the Bay area. And one area where the us has excelled past Europe is the softer side of science.So the marketing, the commercialization, the brand development. So we're going to put our feet on both continents and really use those pillars of excellence. North America will be our commercial headquarters of our business, where our marketing and brand creation, outbound marketing content creation efforts are going to reside.And Europe will be our center of excellence for product innovation and product development. And so we're going to really be able to harness both, you know, amazing capabilities that each region brings to us. Harry Glorikian: Yeah. I, you know, whenever I'm talking to different companies and they're talking about where they're going to be geographically, I mean that, that people, people don't give that enough thought as much as they, I think they should, because there are cultural differences and that. Can really hurt you if you don't understand these little nuances. I mean, I can tell you the difference between being in Canada and being here big difference. Right. And people say, well, no, but it's right there. No, it's actually not right there. It might as well be in a different place. Jason Gammack: Yeah. You can work straight. Also the difference between being in Southern California in Northern Colorado. But it's very, very different. I've lived in San Diego and in the Bay area multiple times. And the difference between the regions are, this is significant. Yeah, no, I grew up, grew up in Northern California. And when I would say to someone, I was from California and they'd be like, Oh, you're from Southern California.I remember being like, no, absolutely not. Don't don't tell me that. Cause you know, you didn't Northern California had more of a. Well, when I was growing up a relaxed, you know, yet, you know, we want it to be ahead at least from an intellectual perspective, but. And now the Northern California has gotten a little arrogant thanks to tech, but you know, it is what it is.It's driven a just unbelievable amount of growth that tech has and unbelievable amounts of innovation has come from that region, which is why, you know, when we looked at. Where we wanted to open our us office. We were eventually the two narratives. We looked at Boston, Cambridge, and we looked at the mayor.I mean, those were the two areas that we honed in on and we made the decision to be in the San Jose, San Francisco area. You know, we know the market well, talent is amazing there. You know, Stanford, Berkeley, the universities there just contributed just an amazing amount of, of gifted computer scientists and developers and so on.You know, both cities would have been great. But California is where we will have our us operations. Well, when do you expect that to open? We hope to have that opening in April. That's our, that's our plan. Harry Glorikian: When do you guys launch, when is this gonna…Jason Gammack: Yeah. So, so, you know, within the life science tool space, there's a very say kind of common dissemination path for, for technology.So technology like ours, which is very complex and capital intensive. It starts with the company, refining that technology and then gain granted access to that technology too early access customers, usually key opinion leaders or thought leaders in particular fields. So we have just completed our early access program, or we had 15 institutions involved in that program.The focus of that program is really to understand the. Application space and how our customers are thinking about using the technology. The technology that point has exited product development. So we're not really still developing the product, finding and nudging and guiding the product in areas like software, or you never stopped developing software software where it's just a constant development.You know, we put a flag in the sand and say, this is where, what the software is going to start. And we do a lot of user acceptance testing and understand how the customers are going to use the software and then start dropping those features that we want to incorporate. Once you finished early access, usually what you then move to a dissemination approach, which is what we're in right now.And so for us, dissemination is twofold. Our product is largely data. I mean, that is our product. You know, a random molecular cartography generates four terabytes of data, which is a significant amount of data. And so we are launching a data as a service approach where we will run molecular cartography and our service lab had spoken in our North American facility expanding our European facility.And at the end of this year, our plan was to open a facility in Asia. So we can begin pushing our data to market because especially when it comes to things like software, we will never develop faster than the community will develop. And quite honestly, the community is going to bring ideas to us that we've never even thought of before, how to look at the data.So we are going to scale our services to provide more access to the technology. Early access is tough because you have to say no to customers. You have to say, yeah, we're oversubscribed. We can't take you in. We're not going to open up the phone with the brain. The second phone number dissemination strategy is we have a number of large advanced institutions that want the workflow deployed at their facilities.So major pharma that sees this as an amazing insight and a biomarker discovery and understanding, you know, how do they move the ball forward, even faster? Talk about collapsing those cycles. So we will be in the latter half of this year, deploying the technology at very advanced, very qualified customer sites.And then the last phase of dissemination is what I call the democratization phase, which is when we then kind of push the button and start pushing the platform onto benchtops. So it scientists at university scientists and non-profit research institutions and so on. And that will happen in, in the later months.Harry Glorikian: But you almost wished like… I've become a believer. And I know that this is, you know, sometimes it's a pipe dream, but you'd want this, all these images, like Google maps to at some point coalesce into one repository. Like I understand that everybody wants their own confidential information, but. We didn't build the human genome on confidential information. We, we sort of put it together and said, here's the genome, right? Otherwise, nothing we have right now would have, you know, been realized and everything is built on that, on what was done in those early years. I feel like what you're doing almost. If you're going to build a map, you need everybody mapping. And adding to the map so that everybody can then benefit from it in their own unique way. Jason Gammack: No question about it, you know, you and I are in violent agreement on that point. And so hence our urgency to get our data into the scientist's hands so that they can understand the value and the number of insights that come from the data.So there are a number of international consortium efforts on your way right now that are commonly referred to as cell Atlas efforts where they're is different cells. And so on. We want to put the cell Atlas three-dimensional context and you know, those are a couple of stories. And so, so we have a strategy to engage those organizations to be able to kind of say, okay, you're now not in the single cell sequencing.You're done single cell RNA seq now we need to take it to the next level, take that RNA seek data, which is the counting of the transcripts in a tune D kind of planar effect. Let's now blow that into a 3d effect. Let's correlate our visualization of the transcripts with the digital readouts of RNAC and this collaboration that I spoke of with this major pharma company in Alzheimer's.We did it in their Alzheimer's mouse mall. Where we correlated all of the single cell on a sick day that they'd been accumulated over the last five years and map that to three-dimensional spatial, single molecule fish data. And it was a beautiful study because we showed a correlation and R squared of 0.9, nine, seven to the RNA seek data to our visualization of the transcripts.And then we added the three-dimensional context, very importantly, at some cellular resolution where you can actually see structures within the cells. And so it was just this. Yeah, it was one of those kinds of moments where you get goosebumps and you're like, Holy smokes. This is real. I mean, we knew it was good, but this really showed how good it was.Harry Glorikian: Well, I'll look forward to that to that paper when you said it's, it's on its way for publication?Jason Gammack: We're reviewing the manuscript now. So it's an iterative process and it's a major pharma. So, you know, they're embargo mania.Harry Glorikian: Well, when it's out, you can, you can send me a copy, but Jason, it's been great to talk to you. I feel like we could talk. Knowing the last time we talked, we could probably talk for hours about these things. But I I'm sure that you'll, we'll have you back on the show when we get to the next iteration. You know, what we should do is we should, we should get Per to come on the show with us and, and, and do a three-way conversation because his perspectives are always insightful and unique.Jason Gammack: Indeed. He is a I've known Per for 20 years and the opportunity to join with pair and start this company. It was an amazing opportunity. Truly a thought leader and a visionary in the field. And we just had so much runway in front of us. We've got such an amazing team and the team is growing amazingly fast and it is truly an honor and a privilege to be working with them and bring this technology to market because we believe that this technology will absolutely have a positive impact on the human condition. There's no question about that. Harry Glorikian: Well, you know, I just, like I said, I'm reflecting on, you know, the, what immunohistochemistry opened up to us. And I still don't think it gets the credit that it deserves. Right. But I think now with the computational capabilities and the insights that that could provide, and then you can overlay other information onto that it's changing the con the context where the persistent identifier is the location, but then everything that's happening around it is what really puts it into context of what's happening in that cellular dynamic. So great talking to you and I look forward to keeping in touch. Jason Gammack: Absolutely. Thank you, Harry. Really appreciate it.Harry Glorikian:That’s it for this week’s show. We’ve made more than 50 episodes of MoneyBall Medicine, and you can find all of them at glorikian.com under the tab “Podcast.” You can follow me on Twitter at hglorikian. If you like the show, please do us a favor and leave a rating and review at Apple Podcasts. Thanks, and we’ll be back soon with our next interview.
What does it take to be an astronaut? Neil deGrasse Tyson, Gary O’Reilly, and Chuck Nice break down the physical effects of being in space and the results of the astronaut twins study with guests astronaut Scott Kelly and biophysicist Chris Mason. NOTE: StarTalk+ Patrons can watch or listen to this entire episode commercial-free here: https://www.startalkradio.net/show/the-right-stuff-with-astronaut-scott-kelly-and-dr-chris-mason/ Thanks to our Patrons Jamie Ferns, evan stegall, Payton Hawk, Farid El Nasire, Steve Lindauer, Austin Lawrence, Cory Farnum, Nathan Mills, Trumpet Wom', and Noah for supporting us this week. Photo Credit: NASA. See omnystudio.com/listener for privacy information.
Today on Mushroom Hour we are excited to have the chance to hear from our guest Christian Schwarz. Christian is a Research Associate at the Norris Center for Natural History and he is coauthor of "Mushrooms of the Redwood Coast" – the bible for California mushroom foraging. Christian Schwarz has been intrigued by fungi ever since he inherited his first mushroom guidebook from his brother. That guide turned out to be irrelevant to his area and so his first year of foraging was spent using just his own powers of observation. What can foraging for mushrooms without a guide bring to a forager's ability to develop their own libraries of sensory perception? As the author of Mushrooms of the Redwood Coast, we couldn't ask for a better guide to help us explore the mushrooms of California. Christian explains the foraging season, different bio-regions and the variety of fungi, including a plethora of endemic fungi that call California home. The book itself is one of the best resources available for mushroom hunters along California's coastline. What was the inspiration for the book and what was that journey like of cataloging 900+ types of mushrooms? And as someone who traveled throughout the state hunting mushrooms, what are some of Christian's favorite areas in California to mushroom hunt? The answer might not be what you expect. Christian may best be described as a "biodiversiphile" - someone who loves biodiversity in all of its forms. As he eloquently elucidates the future of fungal diversity research, it becomes clear that amateur naturalists and citizen scientists have a huge role to play in the raw data collection and cataloging of biodiversity. We'll learn about the "Taxanomic Triangle" and pick up invaluable tips on how amateurs can structure their observations to contribute the best data possible to be used in future biodiversity studies. What are the six pieces of information in the basic biodiversity suite on a given organism? What insights about evolutionary history are we gleaning based on the massive influx of biodiversity data gathering? Episode ResourcesChristian Schwarz IG: https://www.instagram.com/biodiversiphile/Mushrooms of Redwood Coast (Book): https://bookshop.org/books/mushrooms-of-the-redwood-coast-a-comprehensive-guide-to-the-fungi-of-coastal-northern-california/9781607748175Norris Center of Natural History: https://norriscenter.ucsc.edu/Amscope Microscope: https://www.amazon.com/s?k=amscope&ref=nb_sb_noss_2Southwestern Research Station: https://www.amnh.org/research/southwestern-research-stationCalifornia Channel Islands: https://en.wikipedia.org/wiki/Channel_Islands_(California)Santa Cruz Mycoflora: http://scmycoflora.org/Damon Tighe: https://www.instagram.com/damontighe/Leptonia Carnia: http://inaturalist.org/taxa/67387-Leptonia-carnea
Dr. C Explains how we figured out how to sequence DNA.
We got a Christmas present from listener Anna: a small plastic tube full of dead flies. They've recently been infesting the hospital where she works. She wants us to figure out what they are, and what caused the infestation. Can DNA crack the case? Plus, the return of Gins & Genes... Like this podcast? Please help us by supporting the Naked Scientists
We talk to a genetic testing company which may have cracked the code to digital privacy. Part 1: genes, eugenism, and the life-saving power of genomic sequencing. Part 2: genetic privacy, serial killers, and the holy grail of cryptography. FIND OUT MORE circagene.com Questions & comments? Email us at wcn@granttree.co.uk
Commentary by Dr. Valentin Fuster
Jeremy has a conversation with Matthew Putman, co founder and CEO of Nanotronics. Matthew shares the story of the health challenge that influenced the speed of development of his company and its focus on improving experience. They discuss the challenges we face environmentally and in our health systems. And their backgrounds as musicians serve as process reminders of the ways we experience our realities. Support the show (http://patreon.com/highwaytohealth)
In this episode, I dive into the complexities of healthcare screening of newborns. Then I take a winding path into the world of insect egg evolution. The connecting factor is … how our viewpoint affects what we focus on and what we see. I reference a few articles, which you might want to look up: The Promises and Pitfalls of Gene Sequencing for Newborns Insect Egg Size and Shape Evolve with Ecology but Not Developmental Rate The Biologist Using Insect Eggs to Overturn Evolutionary Doctrine An Interview with Cassandra Extavour Highlights include: 6:05 – “In our society, we are really uncomfortable with not knowing and, more specifically, not controlling where things are going.” 6:26 – “Screenings are a way to comfort ourselves … we feel if we can screen, we can reduce that (risk).” 7:58 – “I think our culture has gotten so risk-averse that I honestly think people have gotten lost in a swirl of fear without looking at it.” 8:44 – Agatha Christie’s airplane ride. 9:36 – “We have to think about what are we comfortable with as a community and how do we also allow for individuals to have different levels of personal comfort.” 14:57 – “(Cassandra Extavour) is not your typical traditional professor at Harvard. And I think there is an association there between an entirely different worldview that she has … and the fact that she could topple that preconceived idea (about insect egg evolution).” 15:20 – “We need all the different viewpoints. If we only have the same viewpoint, we are literally only looking at the same thing. We’re never going to see anything new.” 16:20 – “(Cassandra Extavour) is a person who has many worlds in her life and many different viewpoints. And I just think, what it took to bring in that different viewpoint. What if she hadn’t been raised as an outsider looking in? Would she have had the same viewpoint? And I think … no. I think because she was raised as an outsider to that traditional community, she had a different perspective that was essential to moving the science forward.” 16:55 – How much are we losing when we restrict the voices we listen to, to just the ones we’ve already heard. How much are we not going to be seeing by looking at only what we’ve always looked at?” 17:30 – Cassandra Extavour says in the article, “I didn’t even know that research was a profession. My parents didn’t go to college – this is a very esoteric profession practised by such a tiny fraction of the population, and unless you know someone in an academic workplace, it wouldn’t even occur to you that this kind of thing was happening.” 18:03 – “When we don’t reach out to include people, circumstances and structures block them.” 19:10 – “How are we limiting what we see by having preconceived notions of who will be a scientist and who won’t be?” Leading with Health is hosted by Jennifer Michelle. Jennifer has a Master’s in Public Health and Epidemiology and is a certified EMT. As President of Michelle Marketing Strategies, Jennifer specializes in healthcare marketing.
Peter is joined by Robert Hillier, Executive Chairman of Hillier Nurseries Ltd. Peter and Robert discuss the way that business has changed over the years, some of the notable events in it’s history and the responsibilities that come with such a large company. Elsewhere Peter gives us a report from the Chelsea Flower Show, tells us how and when to deal with weeds and explains Gene Sequencing (!) See acast.com/privacy for privacy and opt-out information.
Interview with Allison W. Kurian, M.D., M.Sc., author of Uptake, Results, and Outcomes of Germline Multiple-Gene Sequencing After Diagnosis of Breast Cancer
In this CAPcast, Dr. Matt Anderson discusses his work on new methods to sequence the genes encoding human leukocyte antigens, better known as “HLA.” Dr. Anderson is Vice President and Medical Director at the BloodCenter of Wisconsin, an Associate Investigator at the Blood Research Institute, and an Assistant Professor of Pathology at the Medical College of Wisconsin. He also currently serves on the Personalized Healthcare Committee of the CAP, and he’s written a short article summarizing some of his work on HLA genes that is posted in the Precision Medicine Resource Center on the CAP web site, http://capatholo.gy/2FIHjh7.
This week we delve into DNA and what it can tell us about our past, present and future. And, what happened when we decided to read the DNA sequence of a local sausage. Plus, in the news, what won Nobel Prizes, the world's largest HIV survey, and why doing exercise you don't like makes you more likely to binge on junk food. Like this podcast? Please help us by supporting the Naked Scientists
This week we delve into DNA and what it can tell us about our past, present and future. And, what happened when we decided to read the DNA sequence of a local sausage. Plus, in the news, what won Nobel Prizes, the world's largest HIV survey, and why doing exercise you don't like makes you more likely to binge on junk food. Like this podcast? Please help us by supporting the Naked Scientists
What surprises might you find lurking in your DNA, and can that information be used against you? Like this podcast? Please help us by supporting the Naked Scientists
What surprises might you find lurking in your DNA, and can that information be used against you? Like this podcast? Please help us by supporting the Naked Scientists
I spoke with Sandy Serkes, the co-founder, president, and CEO of Valora Technologies, a provider of document, data, and content analytics solutions for corporate, legal, and government clients worldwide. We discussed the genesis of Valora, why data mining has become such a hot topic, the art of “gene sequencing” a document to find key hidden details, and cost-efficient techniques for locating information. “Not knowing what data you are holding is a liability,” said Serkes.
I spoke with Sandy Serkes, the co-founder, president, and CEO of Valora Technologies, a provider of document, data, and content analytics solutions for corporate, legal, and government clients worldwide. We discussed the genesis of Valora, why data mining has become such a hot topic, the art of “gene sequencing” a document to find key hidden details, and cost-efficient techniques for locating information. “Not knowing what data you are holding is a liability,” said Serkes.
I spoke with Sandy Serkes, the co-founder, president, and CEO of Valora Technologies, a provider of document, data, and content analytics solutions for corporate, legal, and government clients worldwide. We discussed the genesis of Valora, why data mining has become such a hot topic, the art of “gene sequencing” a document to find key hidden details, and cost-efficient techniques for locating information. “Not knowing what data you are holding is a liability,” said Serkes.
I spoke with Sandy Serkes, the co-founder, president, and CEO of Valora Technologies, a provider of document, data, and content analytics solutions for corporate, legal, and government clients worldwide. We discussed the genesis of Valora, why data mining has become such a hot topic, the art of “gene sequencing” a document to find key hidden details, and cost-efficient techniques for locating information. “Not knowing what data you are holding is a liability,” said Serkes.
Dr John Mendelsohn discusses the goals of the Khalifa Institute for Personalized Medicine and their aim to set up a system that will allow for the analysis of every patient’s when standard therapy does not work. This analysis will result in the discovery of new genetic, RNA or protein abnormalities for potential targeted therapy. The MD Anderson Cancer Center Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy supports preclinical research and clinical trials where tumour biopsies are analysed for abnormal genes and gene products to promote the development of new targeted agents.
Next-generation genome analysis technology enables biologist Christopher Sullivan to study how viruses replicate and cause tumors in new ways. Sullivan is an assistant professor in Molecular Genetics and Microbiology. His lab studies how viruses interact with the host RNAi machineries to replicate, induce tumors, and cause pathogenesis.
Dr. Euan Ashley, assistant professor of cardiovascular medicine, discusses gene sequencing and the myriad of questions weʼre bound to ask as we enter the dawn of a new age in genomics. (May 25, 2010)
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