Podcasts about Drug discovery

Virtual cell models promise faster, cheaper early-stage drug discovery. However, the industry still lacks a shared way to judge which of these models can actually be trusted on a given problem.   In this episode, Kristóf Szalay, CTO and Co-Founder of Turbine, and Gerold Csendes, Scientist at Turbine, set out what virtual cell models can and can't do today, in conversation with host Marilie Fouché. They cover why benchmarking remains fragmented across the field, how pharma teams build confidence in a model before trusting it with real R&D decisions, and how compressing the feedback loop between experiments can cut months out of the discovery process.   This episode is sponsored by Turbine.   Emerj works with a select group of AI vendors to reach Fortune 500 decision makers through research, media, and direct access. If you want to be considered, download our media kit at emerj.com/AD1

Good morning from Pharma Daily: the podcast that brings you the most important developments in the pharmaceutical and biotech world. Today, we're diving into a landscape marked by remarkable scientific breakthroughs, strategic alliances, and regulatory milestones that are shaping the future of healthcare. Novo Nordisk is making waves with its new partnership with Amazon Web Services, utilizing artificial intelligence to accelerate drug discovery for chronic diseases. By integrating cloud computing and machine learning models, this collaboration highlights the increasing role of digital transformation in drug development. Novo Nordisk's commitment to innovation is further underscored by the launch of a new London Innovation Hub, enhancing research capabilities in the UK and demonstrating how technology can streamline the development of novel therapeutics. In clinical trial news, Silence Therapeutics has achieved a significant milestone with its investigational therapy Divesiran. This small interfering RNA therapeutic met primary endpoints in a Phase 2 trial for polycythemia vera, highlighting the potential of RNA-based therapies in treating complex blood disorders. Meanwhile, AbCellera's monoclonal antibody therapy ABCL635 has shown promising Phase 2 data for alleviating menopause-related hot flashes, surpassing existing treatments and underscoring the potential of targeted biologics in women's health. Regulatory achievements are further advancing personalized medicine. LabCorp received FDA approval for its PGDx elio tissue complete CDx companion diagnostic for BRAF-mutant advanced melanoma. This tool is pivotal for identifying patients who could benefit from targeted therapies, enhancing precision medicine approaches in cancer treatment. Similarly, AstraZeneca's Calquence and Enhertu have received notable endorsements, reinforcing the critical role of regulatory bodies in facilitating access to innovative treatments. The industry's business landscape is vibrant with strategic partnerships and acquisitions aimed at advancing therapeutic pipelines. Sobi's $580 million deal with Innate Pharma to advance lacutamab through Phase III lymphoma trials underscores how combining expertise can accelerate drug development and commercialization efforts. Financially, companies like Denali Therapeutics are surpassing revenue expectations with products like their enzyme replacement therapy Avlayah for Hunter syndrome, while fundraising activities are empowering biopharmaceutical companies to drive forward pain and oncology initiatives. Despite these advances, challenges persist. Sionna Therapeutics' recent clinical setback in cystic fibrosis reinforces Vertex Pharmaceuticals' dominance in CFTR modulator therapies. Additionally, Tenax Therapeutics encountered disappointment with TNX-103 failing to meet primary endpoints in a Phase 3 trial for pulmonary hypertension associated with heart failure. Manufacturing capabilities are also a focal point as Bristol Myers Squibb plans a substantial investment in Houston, reflecting an industry trend towards expanding infrastructure to meet demand and ensure supply chain resilience. However, compliance remains critical, as seen with Scholar Rock's decision to drop Novo Nordisk's Catalent facility following an FDA inspection. In contrast to setbacks, some companies are achieving breakthroughs. Jazz Pharmaceuticals' acquisition of Actio Biosciences aims to enhance their epilepsy treatment portfolio by integrating clinical-stage assets into its pipeline—a strategic move reflecting ongoing consolidation within the industry. The promise of genetic-targeted therapies is vividly illustrated by Biogen's ALS treatment Qalsody, marking a major scientific breakthrough as the first FDA-approved drug targeting a genetic cause of ALS. Patients have reported symptom stabilization and improvement—a significant advancement given ALS's progressive nature. Meanwhile, psychedelics are emerging as transformative agents in psychiatric medicine. As traditional medications often fall short, psychedelics offer hope for innovative mental health therapies supported by growing clinical and policy backing. However, navigating regulatory landscapes remains challenging. The FDA's recent actions illustrate ongoing struggles to balance innovation with oversight amidst leadership transitions. Real-world evidence is increasingly influencing regulatory decisions—reshaping how companies approach market access strategies by integrating patient experiences into evidence-based decision-making. In oncology, Replimune's melanoma drug has finally earned FDA approval after previous setbacks—a testament to persistence and the potential impact of innovative cancer therapies on patient outcomes. These developments underscore a dynamic pharmaceutical and biotech industry where breakthrough technologies like genetic-targeted therapies and psychedelics promise transformative impacts on patient care. Yet, they also highlight the complexities of bringing these innovations to market amidst stringent regulatory standards and competitive pressures. As we continue to track these stories, one thing is clear: the relentless pursuit of novel treatments remains at the forefront of advancing global healthcare.Support the show

Takeda is entering one of the most pivotal moments in its 245-year history, with a late-stage pipeline poised to transform patient outcomes across three therapeutic areas. Chief Scientific Officer Chris Arendt goes Inside the ICE House to discuss the science behind drug candidates targeting narcolepsy, polycythemia vera, and psoriasis. He explores how AI and computational technologies are reshaping drug discovery and why building the right data foundation is critical to supercharging Takeda's R&D engine.

Vin Singh, Founder, Chairman, and CEO of Bullfrog AI, is applying proprietary AI technology to drug development, with a focus on drug target discovery and phase three clinical trials. The company's platform is derived from the Johns Hopkins University Applied Physics Lab and is designed to pinpoint drug targets, identify the root causes of disease, and match patients to appropriate treatments based on genetic profiles. Bullfrog AI aims to reduce clinical trial timelines, improve success rates, identify more accurate biomarkers, and improve patient outcomes. Vin explains, "We are in the AI innovator category, and we're applying our proprietary platform to the challenges that exist in the world of drug development for pharmaceutical and biotech companies. Primarily our focus is on the first and the last stage of that process. So the first stage is what you call drug target discovery. So when you take a medication, it targets something in your body. So we're trying to identify novel targets that we believe are the root cause of certain diseases. And then we are also focused on the final stage, which is phase three clinical trials. That's where we have our experience. And that's obviously a very critical and pivotal point in the process and the final stage of a long 10- to 15-year, one- to two-billion-dollar drug development process."   "You need to have the right tool for a certain problem and then data, and they go together. I think on the data side, getting access to rich, deep data sets is critical. And fortunately, the cost to generate that type of data has come down pretty significantly over the past, say, 10 years. So now, for example, we have a project where we have brain data, and it's the type of data where you can really make discoveries and insights and so forth. And so that's a really critical part of this process. The other part is: what tool do you have, and what problem are you trying to solve? Our technology is unique. I'd say most companies use technology that comes from NVIDIA and AWS. So they're all kind of using the same tools from the same toolbox." "Our technology comes from Johns Hopkins University Applied Physics Lab, which is a world-renowned institution. We have IP around our platform, and we've continued to innovate over the years. It definitely has unique capabilities, and it is specifically designed for the types of problems that exist in drug development." #BullFrogAI $BFRG, #AI, #AIinBiotech, #MachineLearning, #DrugDevelopment #AIinHealthcare #PrecisionMedicine #Neuropsychiatry #Oncology #DigitalHealth #ClinicalTrials #Biomarkers #bfLEAP bullfrogai.com Download the transcript here

Vin Singh, Founder, Chairman, and CEO of Bullfrog AI, is applying proprietary AI technology to drug development, with a focus on drug target discovery and phase three clinical trials. The company's platform is derived from the Johns Hopkins University Applied Physics Lab and is designed to pinpoint drug targets, identify the root causes of disease, and match patients to appropriate treatments based on genetic profiles. Bullfrog AI aims to reduce clinical trial timelines, improve success rates, identify more accurate biomarkers, and improve patient outcomes. Vin explains, "We are in the AI innovator category, and we're applying our proprietary platform to the challenges that exist in the world of drug development for pharmaceutical and biotech companies. Primarily our focus is on the first and the last stage of that process. So the first stage is what you call drug target discovery. So when you take a medication, it targets something in your body. So we're trying to identify novel targets that we believe are the root cause of certain diseases. And then we are also focused on the final stage, which is phase three clinical trials. That's where we have our experience. And that's obviously a very critical and pivotal point in the process and the final stage of a long 10- to 15-year, one- to two-billion-dollar drug development process."   "You need to have the right tool for a certain problem and then data, and they go together. I think on the data side, getting access to rich, deep data sets is critical. And fortunately, the cost to generate that type of data has come down pretty significantly over the past, say, 10 years. So now, for example, we have a project where we have brain data, and it's the type of data where you can really make discoveries and insights and so forth. And so that's a really critical part of this process. The other part is: what tool do you have, and what problem are you trying to solve? Our technology is unique. I'd say most companies use technology that comes from NVIDIA and AWS. So they're all kind of using the same tools from the same toolbox." "Our technology comes from Johns Hopkins University Applied Physics Lab, which is a world-renowned institution. We have IP around our platform, and we've continued to innovate over the years. It definitely has unique capabilities, and it is specifically designed for the types of problems that exist in drug development." #BullFrogAI $BFRG, #AI, #AIinBiotech, #MachineLearning, #DrugDevelopment #AIinHealthcare #PrecisionMedicine #Neuropsychiatry #Oncology #DigitalHealth #ClinicalTrials #Biomarkers #bfLEAP bullfrogai.com Listen to the podcast here

Good morning from Pharma Daily: the podcast that brings you the most important developments in the pharmaceutical and biotech world. Today, we delve into the intricate web of scientific advancements, regulatory updates, and strategic maneuvers shaping the industry. Let's begin with Eli Lilly's impressive financial performance, clocking a record-breaking $23 billion in revenue for Q2 2023. This achievement, driven by the success of Mounjaro and Zepbound in metabolic diseases, underscores the competitive landscape of therapies targeting chronic conditions. However, the slower launch of Foundayo highlights ongoing challenges. Meanwhile, competition in obesity treatments is intensifying as Novo Nordisk's Wegovy continues to dominate despite new entrants like Eli Lilly's Foundayo. This scenario reflects growing patient preference for oral medications over injectables. Gilead Sciences' HIV prevention franchise has exceeded $1 billion in quarterly sales, reflecting an increasing reliance on effective small molecule therapies for infectious diseases. Gilead also remains a focal point with its HIV pre-exposure prophylaxis franchise reaching sales milestones amid legal victories defending their tenofovir-based treatments. These legal precedents could influence future innovation policies across the industry. Artificial intelligence continues to make waves in drug discovery and clinical trials. Icon's partnership with Anthropic aims to integrate AI capabilities to accelerate drug development timelines. Similarly, Phylo and Chugai Pharmaceutical are collaborating to optimize drug discovery workflows using advanced AI platforms. These collaborations highlight a strategic move towards enhancing efficiency in drug development processes. In oncology, Amplia Therapeutics and Eli Lilly are evaluating a combination therapy for non-small cell lung cancer, while Evexta Bio and Roche are exploring a joint study for metastatic breast cancer. These partnerships underscore the industry's focus on combination therapies and precision medicine to improve cancer treatment outcomes. Additionally, AstraZeneca's partnership with CSPC Pharmaceutical to enhance biologics manufacturing in China signifies the importance of localized production capabilities. On the regulatory front, Arrowhead Pharmaceuticals' acquisition of an FDA rare pediatric disease priority review voucher for Plozasiran represents a commitment to addressing unmet needs in rare diseases. This voucher could expedite new drug applications, potentially bringing life-saving treatments to patients more quickly. Despite these advancements, challenges persist. Novo Nordisk's Cagrisema failed to achieve its primary endpoint in a Phase 3 trial for type 2 diabetes, highlighting the complexities of developing combination therapies for metabolic disorders. Similarly, Eli Lilly's discontinuation of its Phase 1/2 trial for GBA1 gene therapy reflects the hurdles faced in advancing gene therapies. Looking at industry dynamics, Amgen's decision to discontinue its early-stage obesity drug signifies a strategic shift towards focusing on more promising pipeline candidates like Maritide. This move aligns with broader trends prioritizing candidates with significant potential impact on patient care. Amgen's 'Repatha' is experiencing renewed interest due to positive cardiovascular risk reduction data, showcasing how robust clinical results can rejuvenate existing products. In regulatory news, Merck's 'Lipfendra' has been spotlighted by the FDA as part of its Complex New Product Validation pilot program. This positions Lipfendra as a potential game-changer in the PCSK9 inhibitor category. Lastly, financial maneuvers such as Attovia Therapeutics' $289 million IPO and Expedition Therapeutics' $115 million Series B funding highlight investor confidence in novel therapeutic areas like dermatological and respiratory treatments. The pharmaceutical landscape remains dynamic with Johnson & Johnson investing heavily in gene therapy ventures like Sail Biomedicines for CAR-T therapies. Meanwhile, regulatory challenges persist as seen with Capricor's cell therapy setback due to statistical complexities during FDA reviews. Despite setbacks faced by some companies, innovations continue to thrive. The launch of personalized genetic therapy centers signals a shift towards individualized medicine while research into safer CAR-T therapies progresses. In conclusion, these developments reflect an industry driven by innovation amidst regulatory challenges and strategic adjustments. As companies navigate this evolving landscape, their decisions will shape future healthcare innovations and patient care outcomes. Thank you for joining us on Pharma Daily; stay tuned for more insights from the world of pharmaceuticals and biotech.Support the show

Send us Fan MailWhat happens when you step back from individual biotech companies and look at the entire industry?Today's guest has spent decades connecting biotech CEOs, investors, pharmaceutical leaders, and innovators from around the world - giving her a rare front-row seat to the trends shaping the future of medicine. From AI and TechBio to venture capital, partnering, and breakthrough therapies, we're exploring where biotech is really headed next.Sara Jane Demy is the Founder and CEO of Demy-Colton ( https://demy-colton.com/ ), one of the most influential organizations in life sciences events and ecosystem connectivity.For more than two decades, Sara has operated at the intersection of biotech innovation, venture capital, and pharma partnering - first at the Biotechnology Innovation Organization (BIO), where she helped launch major industry conferences including BIO CEO & Investor Conference, BIO Investor Forum, BIO Asia, and helped develop the partnering systems now widely used across the industry.Sara later founded Demy-Colton, which runs major industry convenings such as Biotech Showcase, BioFuture, and the Global Biotech CEO Summit - bringing together thousands of CEOs, investors, and BD leaders across the global biotech ecosystem.What makes Sara particularly unique is that she doesn't sit inside a single company or investment fund - she sits across the entire system. She has a rare, real-time view of how biotech narratives, capital flows, and strategic priorities are shifting across hundreds of companies and investors at once.And that's what we're going to explore today: not one company, but the state of biotech itself - what's changing, what's breaking, and what's emerging next.#Biotech #HealthcareInnovation #Pharma #DrugDiscovery #Biotechnology #ArtificialIntelligence #TechBio #PrecisionMedicine #LifeSciences #Innovation #MedicalResearch #FutureOfMedicine #Healthcare #Science #ProgressPotentialPossibilitiesSupport the show

*Content Warning: This episode includes discussions of trauma, loss, and near‑death experiences. Please take care while listening, and reach out to a mental health professional or someone you trust if these topics become overwhelming.* Listen to the next episode of our podcast, Under the Surface. In episode 17, Building Collaborative Drug Discovery Tools, we feature an in-depth interview with Barry Bunin, CEO of Collaborative Drug Discovery, about his journey from chemist to entrepreneur. He shares how his background and desire to make a difference have shaped his company's mission and technology. Here's what we discuss: Barry Bunin's background and what inspired his purpose How CDD started and became a leader in sharing science safely Why CDD Vault was built to keep research private, secure, and easy to use How teamwork and sharing data make drug discovery faster Finding the right balance between sharing and privacy How new tech like AI helps scientists work together Caring about people, having an impact, and doing good in science Barry's book shows the power of working together and being creative This episode brings together science, entrepreneurship, and the personal stories that inspire innovation. Listener discretion is advised. (03:00) Barry talks about starting out in science, wanting to make a difference, and how that shaped his work. (06:00) How Barry's personal experiences led to his book and his current journey. (06:33) Content Warning begins (07:10) Content Warning ends (10:00) Mixing hands-on chemistry with computer tools to get better results. (15:00) How Barry got interested in combining chemistry and technology early on. (20:00) Moving from lab work to starting software companies. (25:00) What CDD stands for: their values, company culture, and mission. (30:00) Working together in drug discovery, and how to keep things open but private. (33:24) Content Warning begins (37:33) Content Warning ends (35:00) Real stories from the field, and why being human matters in science. (40:00) Keeping data safe and models using tech like federated learning. (50:00) How Barry's book came together. (1:00:00) Looking ahead: AI, collaboration tools, and making a positive impact. (1:06:40) The "Deschenes Dilemma": What happens if you can't stop doing science? (1:08:00) Thinking about legacy, inspiring future generations, and making your mark. Resources & Links: Inside CDD Vault — A Different Kind of Silicon Valley Success Story: Behind the Code: The Human Side of Collaborative Drug Discovery (on Amazon) Collaborative Drug Discovery (CDD) The Human Side of Collaborative Drug Discovery How Do B2B Companies Hold Onto Their Purpose as They Grow? Connect with Barry Bunin: LinkedIn

Synopsis: The guest on today's podcast is a representative of Braidwell LP, a registered investment adviser. Braidwell invests on behalf of its clients and either holds, or may in the future hold, positions in the securities discussed. His statements are not intended to provide investment advice, discuss comprehensive investment risks, or constitute an offer to transact in any security. The information presented is for general information purposes only and will not be updated. For years, AI has promised to transform drug discovery—but why hasn't that promise translated into more approved medicines? In this episode of Biotech 2050, host Rahul Chaturvedi sits down with Nick Myerberg, Partner and Head of Artificial Intelligence and Technology at Braidwell, for an in-depth discussion on where AI in biotech has succeeded, where it has fallen short, and why the next generation of AI-native drug discovery may finally deliver breakthrough therapies. Nick traces the evolution of computational biology—from early mathematical models to AlphaFold and today's emerging agentic AI systems—and explains why proprietary data, scientific judgment, and tightly integrated laboratory feedback loops are becoming the real competitive advantage. He shares how Braidwell evaluates AI-first biotech companies, what separates lasting platforms from hype, and why the future belongs to organizations that redesign discovery around AI rather than simply adding AI to existing workflows. The conversation also explores autonomous laboratories, AI-designed medicines, the changing economics of biotech, and the evolving role of scientists in an era where human expertise and machine intelligence increasingly work side by side. Whether you're an investor, biotech founder, researcher, or AI enthusiast, this episode offers a thoughtful roadmap for understanding how artificial intelligence is reshaping the future of drug discovery. Biography: Nick Myerberg, Partner and Head of Artificial Intelligence and Technology, Braidwell Nick Myerberg is a Partner and Head of Artificial Intelligence and Technology at Braidwell, a life sciences investment firm dedicated to building and backing companies that transform human health. Working at the intersection of computation, biology, and capital allocation, Nick engineers systems that shape investment decisions and scientific discovery, and he invests in the scientists and founders forging AI-native approaches to biology. Before joining Braidwell, Nick built machine learning systems at Bridgewater Associates and at S&P Global's Kensho Technologies. He was also a founding volunteer at NeighborShare, a nonprofit that connects families in need with local donors. Nick was selected as a member of the inaugural 2026 cohort of the Aspen Institute's Technology Leaders Initiative, a fellowship within the Aspen Global Leadership Network bringing together senior leaders shaping the future of artificial intelligence and frontier technologies. Nick is broadly interested in how advances in computation reshape the pace and structure of scientific discovery, and in building the discovery infrastructure required to increase the world's scientific bandwidth. Nick earned a B.A. from Wesleyan University and later studied history and philosophy of science at the University of Cambridge.

Send us Fan MailEvery year, nearly 700 million people around the world are infected by norovirus. Most people know it as a miserable few days of vomiting and diarrhea - but for transplant patients, cancer patients, and other immunocompromised individuals, it can become a chronic and potentially life-threatening infection. And despite decades of research, we still have no approved antiviral treatment. Today we're exploring the science behind the race to change that.James Sapirstein is Chief Executive Officer of Cocrystal Pharma ( https://www.cocrystalpharma.com/ ) and one of the biotechnology industry's most experienced commercialization executives.Throughout a career spanning more than four decades, James has participated in or led an extraordinary twenty-three pharmaceutical product launches while building and leading multiple biotechnology companies. He has served as CEO of Cocrystal Pharma, Contravir Pharmaceuticals, Tobira Therapeutics, First Wave BioPharma, and several other innovative life science organizations. Earlier in his career James held senior leadership roles at Bristol-Myers Squibb, Gilead Sciences, Serono Laboratories, Roche, and Eli Lilly, helping bring important therapies for infectious disease and other major conditions to patients around the world. Beyond industry, James has served on numerous biotechnology boards, including the Biotechnology Innovation Organization and BioNJ, making him one of the most respected leaders in the biotechnology ecosystem.James received a BS (Pharmacy) from Rutgers University and an MBA from Fairleigh Dickinson University.Dr. Sam Lee, Ph.D. is President and Chief Scientific Officer of Cocrystal Pharma. Dr. Lee has devoted more than twenty-five years to discovering next-generation antiviral medicines. Before joining Cocrystal, he led anti-infective drug discovery efforts at ICOS Corporation, where he pioneered the integration of protein crystallography and structure-based screening technologies into pharmaceutical research. His scientific work contributed to the development of PI3K delta inhibitors that ultimately led to an FDA-approved therapy. Dr. Lee earned his Ph.D. in Biological Sciences from the University of Notre Dame before completing postdoctoral research in viral biochemistry at Stanford University under renowned molecular biologist Dr. I. R. Lehman. His career has focused on understanding viruses at the atomic level to design highly targeted antiviral drugs capable of overcoming viral evolution and resistance.#Norovirus #AntiviralResearch #DrugDiscovery #Biotechnology #Biotech #PharmaInnovation #RNAViruses #ViralDiseases #InfectiousDisease #PublicHealth #StructureBasedDrugDiscovery #PrecisionMedicine #MedicinesOfTheFuture #FutureOfHealthcare #BiomedicalResearch #PharmaceuticalInnovation #ClinicalTrials #PandemicPreparedness #HealthcareInnovation #ScienceAndTechnology #ProgressPotentialAndPossibilities #PPPSupport the show

Send us Fan MailThis week on Just MS News, we lead with encouraging—but still early remyelination research.Scientists have identified an experimental small molecule that promoted oligodendrocyte development and remyelination in preclinical models. We explain how this candidate differs from PTD802, the remyelination therapy we recently covered as it prepared to enter human testing.We also look at:• Fampridine becoming routinely available through NHS England for eligible adults with MS-related walking difficulties• Evidence examining whether treatment escalation after clinically silent MRI lesions may reduce future relapse risk• New research exploring how anti-CD20 therapies may affect protective immune cells originating in the gut• A large U.S. analysis identifying racial, geographic and age-related disparities in MS-associated mortality• Two brothers continuing their remarkable marathon journey using an adaptive racing wheelchairARTICLES AND SOURCES1. A Novel Small Molecule Remyelination Therapy for Multiple Sclerosis   Source: npj Drug Discovery   https://www.nature.com/articles/s44386-026-00060-72. Thousands With MS to Get Fampridine on the NHS to Help Them Walk More Freely   Source: NHS England   https://www.england.nhs.uk/2026/07/thousands-ms-life-changing-drug-nhs-help-walk-more-freely/Clinical commissioning policy:https://www.england.nhs.uk/publication/clinical-commissioning-policy-prolonged-released-pr-fampridine-as-a-treatment-of-adults-with-multiple-sclerosis-and-associated-walking-impairment/3. Treatment Escalation After Clinically Silent MRI Lesions in Relapsing-Remitting Multiple Sclerosis   Source: Brain   https://academic.oup.com/brain/advance-article/doi/10.1093/brain/awag252/87413054. Anti-CD20 B-Cell Depletion Is Associated With Elevated Mucosal-Originating Circulating Immune Cells   Source: Science Translational Medicine   https://www.science.org/doi/10.1126/scitranslmed.aee15805. Racial and Ethnic Trends and Comorbidity Patterns in Multiple Sclerosis Mortality   Source: Neurology Open Access   https://www.neurology.org/doi/10.1212/WN9.00000000000001486. Man With MS Does Marathons With a Push From His Brother   Source: Deseret News   https://www.deseret.com/sports/2026/07/22/deseret-news-marathon-brian-danny-connolly-wheelchair-ms-people-with-disabilities/Just MS News provides accessible summaries of multiple sclerosis news and research. This episode is for informational purposes and should not replace guidance from your healthcare team.Visit Just Multiple Sclerosis:https://www.justmultiplesclerosis.comListen to the podcast:https://www.justmultiplesclerosis.com/podcast#MultipleSclerosis #MSNews #Remyelination #MSResearch #Fampridine #MultipleSclerosisResearchThe Just MS (Multiple Sclerosis) Show, w host Justin Loizos, is a podcast that connects, educates and tries to uplift others living with multiple sclerosis. It provides real-life stories, interviews, and information about DMTs (disease modification therapies) and updates on research developments.www.justmultiplesclerosis.com

Good morning from Pharma Daily: the podcast that brings you the most important developments in the pharmaceutical and biotech world. Recent advancements in these sectors highlight a fascinating intersection of technology and medicine, underscoring a push towards innovation that promises to reshape healthcare delivery. Bristol Myers Squibb has expanded its collaboration with NVIDIA, aiming to create what could become the most powerful AI infrastructure dedicated to life sciences. This partnership is set to harness artificial intelligence and machine learning technologies to revolutionize drug discovery and development. By enhancing data analysis and predictive modeling, this collaboration may lead to more efficient identification and validation of drug targets, reflecting a growing industry trend towards leveraging AI to streamline R&D processes. In infectious diseases, Gilead Sciences and Merck & Co. have reported promising phase 3 clinical trial results concerning their combination therapy for HIV treatment. This regimen, combining islatravir and lenacapavir, could become the first weekly oral medication for HIV, offering a significant improvement over daily treatments. Such developments not only promise enhanced patient adherence but also mark a pivotal step forward in long-term HIV management by potentially increasing quality of life for patients. Oncology diagnostics are also seeing significant strides as Tempus AI plans to acquire Personal Genome Diagnostics for $1.5 billion. This acquisition is poised to bolster Tempus's portfolio in cancer minimal residual disease diagnostics. The integration of capabilities from Personal Genome Diagnostics is expected to enhance precision oncology efforts, providing more comprehensive data for personalized cancer treatment plans. Regulatory updates bring more promising news with Takeda's dengue vaccine, Qdenga, securing approval in India. This live-attenuated vaccine targets all four serotypes of the dengue virus, representing a major advancement in regions burdened by dengue fever. Similarly, JCR Pharmaceuticals has received marketing authorization in the UAE for Izcargo, an enzyme replacement therapy that penetrates the blood-brain barrier to treat Hunter syndrome, showcasing innovations in treating rare genetic disorders. Strategic partnerships continue to be a focal point in industry growth. Menarini Asia-Pacific has joined forces with Pharmacosmos to commercialize Cosela across Asia-Pacific regions. Additionally, Halozyme Therapeutics has partnered with Incyte on subcutaneous formulations of a monoclonal antibody using their proprietary Enhaze technology, highlighting advancements in drug delivery systems. Financially, Novartis has shown resilience by returning to sales growth driven by products like Kisqali and Kesimpta amidst generic competition challenges. Meanwhile, Axiom Biosciences is gearing up for an IPO in Hong Kong, indicating a growing interest in stem cell therapies for neurological and rare diseases. Yet not all news has been positive. Novartis has discontinued its phase 2 radioligand therapy targeting gastrin-releasing peptide receptors due to underwhelming results in solid tumors. Agios Pharmaceuticals has similarly halted development of its pyruvate kinase activator for sickle cell disease following unsatisfactory phase 2 data. Legal battles continue as well, with Novo Nordisk suing Eli Lilly over GLP-1 agonists efficacy claims and Moderna locked in patent disputes with CureVac over COVID vaccine technologies. These stories reflect dynamic shifts emphasizing innovation through AI collaborations and novel therapeutic developments in HIV and oncology treatments. They also highlight strategic acquisitions enhancing diagnostic capabilities while revealing challenges such as competitive pressures and regulatory hurdles that companies must navigate. Turning our attention back to scientific breakthroughs, Jennifer Doudna's venture into AI-powered protein design underscores how artificial intelligence continues transforming biotechnology. Her exploration highlights AI's potential to accelerate drug discovery by enabling more precise targeting of disease-related proteins. Additionally, recent successes in personalized medicine include the establishment of a new center dedicated to genetic therapies. Spearheaded by leading scientists, this initiative aims at developing tailored treatments based on individual genetic profiles—advancing precision medicine and reducing adverse effects. In conclusion, these developments illustrate a vibrant landscape where scientific breakthroughs intersect with strategic business maneuvers. As companies navigate these complex waters—balancing innovation with regulatory scrutiny—they continue pushing boundaries that promise improved patient outcomes worldwide while reshaping future healthcare landscapes.Support the show

Send us Fan MailIf AI is already being used across the drug development pipeline, why hasn't its impact matched the investment?AI can help researchers review scientific literature, predict protein structures, prioritize molecules, assess toxicity, support clinical trials, and monitor adverse events. But access to better tools doesn't automatically create better drugs.In this episode, I speak with Thibault Geoui, Science CDO and host of the Tech & Drugs Podcast, about where AI is making a practical difference in drug discovery and development—and where the results remain limited. We map AI across the full drug development funnel, from basic research and target identification to preclinical testing, clinical trials, regulatory documentation, commercialization, and pharmacovigilance.We also discuss why digital-native tech-bio companies may be better positioned to benefit from AI than traditional pharmaceutical organizations. The difference isn't simply the model. It's how data, people, laboratory experiments, and AI tools are connected inside the workflow.For digital pathology professionals, the conversation becomes especially relevant when we examine AI-powered biomarker development, the role of pathology in pharmaceutical research, and the Roche–PathAI case discussed in the episode.And, of course, we talk about the problem every AI user eventually faces: an answer can look polished, specific, and completely convincing—and still be wrong.Episode Highlights00:00 — When convincing AI output creates more work Why AI can accelerate information generation while increasing the time required for review and verification.02:15 — From structural biology to science and technology leadership Thibault shares his background in X-ray crystallography, structural biology, scientific data, and digital product development.15:36 — Understanding the drug discovery and development funnel How thousands of potential compounds are narrowed down through discovery, preclinical research, clinical trials, and approval.20:00 — AI for scientific literature review How alerts, filtering, summarization, and information extraction can help researchers manage a rapidly growing scientific literature base.22:32 — AlphaFold and protein structure prediction What faster access to predicted protein structures changes for researchers—and why structural prediction alone doesn't solve drug discovery.24:13 — Searching an enormous chemical space How AI can help design and prioritize potential molecules for synthesis and experimental testing.25:50 — Predicting efficacy and toxicity Where AI supports preclinical research, why the models remain imperfect, and why experimental validation still matters.29:38 — Has AI changed drug development outcomes yet? A practical discussion about drug approval rates, AI investment, uneven returns, and the difference between deploying a tool and integrating it into a process.34:33 — Why traditional pharma struggles to scale AI Siloed data, legacy systems, organizational complexity, and the need to build reusable data workflows.37:57 — The “lab in the loop” model How tech-bio companies connect AI predictions with wet-lab experiments and feed the new data back into their models.44:37 — Can tech-bio companies shorten development timelines? How digital-native organizations are changing parts of the discovery and preclinical process.58:00 — AI, pharma, and digital pathology What the Roche–PathAI case discussed in the episode may indicate about the role of pathology data, biomarker discovery, and pharmaceutical workflows.01:06:17 — AI errors in regulated environments Why responsibility remains with the person or company submitting AI-assisted work, regardless of which tool produced it.01:17:37 — The growing cost of AI tools Subscriptions, token limits, model selection, AI orchestrators, and the need to use expensive tools more intentionally.01:27:50 — What successful AI adoption requires Starting with focused pilots, training scientists and technologists together, and treating implementation as organizational change.01:30:26 — The AI quirks that still frustrate users Hallucinated information, ignored writing instructions, stylistic habits, and poor awareness of time and context.The episode's timestamped themes and examples are documented in the supplied summary. The broader discussion covers AI from literature mining and molecular design through clinical development and post-market monitoring. Resources Mentioned Thibault Geoui's LinkedIn profile Tech & Drugs PodcastMIT NANDA study on generative AI implementation and return on investment Insilico Medicine as an example of a digital-native tech-bio company AI is already changing how scientific work gets done. The bigger question is whether organizations can redesign their workflows, train their teams, and maintain the human oversight needed to use it well.Listen to the full episode for a practical look at AI in drug discovery, drug development, and digital pathology.Support the showGet the "Digital Pathology 101" FREE E-book and join us!

Bet on informationIf test loss flatlines after 1.5B parameters while training loss continues to drop as you scale, that tells you that your model is limited by the amount of information in your data.Training on a single, smallish data set exposed an information gap: the 3.1B model falls off the scaling trend. Neither parameters nor compute will improve performance past this wall. For predicting changes to gene expression, you need more information rich data.This is what Chu and Bo's teams have done, and here is what ~30x the information buys you:Now we can scale with parameters and training compute! We don't know how much this effort costed, but we can guess that data collection experiments and infrastructure was a few tens of millions, and compute + headcount + research was a few million. The budget looks like a RL rollout budget, rather than a data rich pre-training one.We were lucky enough to have the two central figures in this story on our podcast. Taking the lead from Ci Chu and Bo Wang, Xaira Therapeutics is betting that information rich data is the key to AI-driven drug development. Chu was recently promoted to Chief Discovery Officer and Bo to Chief AI Scientist, underscoring just how strategic Xaira considers this bet.Reverse engineering the human cellIf you had to figure out how a human cell works, what would you do? A good place to start might be by documenting what genes are expressed (e.g. what RNA is floating around) in different kinds of cells, in different circumstances.That is CELLxGENE, a database of 168M cells built by Chan Zuckerberg Institute that maps each cell to a count of how many times 20K-30K genes were detected in that cell, plus detailed metadata about every cell. A ~4 trillion-entry matrix.If the Protein Data Bank (PDB) unlocked structural biology models (Boltz Episode, ESM/BioHub Episode), CELLxGENE has done the same thing for Virtual Cell models. Like PDB, CELLxGENE has inspired a zoo of AI models of RNA expression; so much so that RNA expression models have become synonymous with Virtual Cell models. Bo Wang built one of the most influential, scGPT, that became the starting point for Xaira's new model.RNA expression ≠ Virtual CellModels trained on CELLxGENE describe the relationship between cell types and cell states, but they are not good at predicting what will happen if we make changes to RNA expression. Changes in gene expression are highly correlated, and its is difficult (impossible) to figure out what causes what in most cases.If you could “turn the dial down” on one gene at a time, however, then you would be able to observe what is upstream and downstream of a given gene. You could tell if A → B & C or B → A & C or B → A, C → B → … If you did this for all of the genes, then maybe you could train a model that could predict what would happen to a cell if you change a gene (e.g. with a drug or a gene edit). Or maybe you could figure out the least invasive way to change a particular gene's expression.X-Atlas → X-CellThis is exactly what Chu and Bo's teams have done. The data set is called X-Atlas and the model is called X-Cell.In this episode, we discuss:* Why the team abandoned autoregression for diffusion* The CRISPR-based experiments that run millions of tests in parallel, and generate the raw data for X-Atlas and X-cell* Generalization to real lab experiments in real human cells* Beating the linear baseline that has outperformed previous models* Justifying a kitchen-sink of priors, and how that stacks up vs. data and architectureBo also shared with us some of the (major) advantages he has as an academic vs. industry leader, and how his labs keep up with the breakneck pace of AI innovation.Check out the full episode on YouTube, or your favorite podcasting platform! This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

Good morning from Pharma Daily: the podcast that brings you the most important developments in the pharmaceutical and biotech world. Today, we're navigating through a myriad of transformative advancements reshaping the industry. From artificial intelligence-driven research breakthroughs to strategic acquisitions in emerging therapeutic areas, these developments are setting new benchmarks in drug discovery and patient care. **Strategic Acquisitions and Expansions:** Samsung Biologics' recent proposal to acquire Swiss CDMO Polypeptide for $1.8 billion marks a significant expansion into peptide production, underscoring the growing therapeutic importance of peptides. Their specificity and efficacy make them particularly appealing for metabolic disorders such as obesity. This acquisition reflects a strategic move to capture emerging market opportunities as demand for innovative metabolic treatments rises. Eli Lilly's bold $2.8 billion acquisition of Atai-Beckley highlights the pharmaceutical industry's shifting focus towards psychedelics. As mental health disorders like depression and PTSD become more prominent, psychedelics hold great promise for new therapeutic approaches. This acquisition may pave the way for further research and acceptance of psychedelics within mainstream medicine, offering new hope for patients. Another notable development is Tempus' acquisition of Personalisis for $1.5 billion. This move strengthens Tempus' cancer treatment portfolio by leveraging genomics-driven insights, emphasizing precision medicine's critical role in oncology. **AI Integration and Technological Innovation:** Bristol Myers Squibb is doubling down on AI integration by expanding its collaboration with Nvidia to build what promises to be the most powerful AI supercomputer dedicated to life sciences. This development is pivotal as it signifies a deeper commitment to harnessing computational power in R&D. By accelerating drug discovery and optimizing clinical trial processes, AI stands to revolutionize how treatments are developed and tailored to individual patients. Overall, these developments indicate a dynamic phase characterized by technological innovation and strategic collaborations. The integration of AI into drug development processes stands out as a transformative force, promising enhanced efficiency and efficacy in bringing new treatments to market. **Regulatory Milestones and Clinical Trials:** In regulatory news, Takeda's Qdenga has achieved a milestone by becoming India's first approved dengue vaccine. This approval is crucial in addressing neglected tropical diseases, with significant implications for public health in regions where dengue is prevalent. By reducing dengue fever incidence, this vaccine could play a vital role in improving health outcomes in many tropical countries. Promising results have emerged from clinical trials across various therapeutic areas. 4D Molecular Therapeutics reported an 87% reduction in treatment burden for wet AMD using their gene therapy candidate 4D-150 in Phase 2b trials—demonstrating potential as a transformative approach with reduced intervention frequency. Latigo Biotherapeutics' Nav1.8 inhibitor LTG-001 outperformed Vicodin in Phase 2 trials for acute pain, offering a non-opioid alternative amidst the opioid crisis. Meanwhile, Regenxbio's five-year data on surabgene lomparvovec shows sustained efficacy in wet AMD and diabetic retinopathy—underscoring its potential as a long-term treatment option. **Financial Performance and IPO Activity:** Financially, Abbott exceeded expectations with strong sales from their device and diagnostic divisions, prompting an upward revision of their full-year profit forecast. This reflects sustained demand for innovative diagnostic solutions and medical devices—highlighting Abbott's strategic market positioning. The IPO landscape remains active with companies like Nuvox Therapeutics seeking to raise funds for advancing oxygen therapeutics targeting hypoxia-related diseases—showcasing renewed investor interest and confidence within biotech innovation. Latigo Biotherapeutics is preparing for an IPO to advance its pipeline, demonstrating a strategic response to the opioid crisis. By developing alternatives that minimize addiction risks while providing effective relief, Latigo underscores the industry's commitment to safer pain management solutions. Turning to clinical trials, Scribe Therapeutics plans a $96 million IPO to advance its CRISPR-based lipid-lowering therapies, marking significant interest in genetic solutions for cardiovascular diseases like hyperlipidemia. The precision offered by CRISPR technology could revolutionize treatment options for conditions contributing significantly to cardiovascular health burdens. **Geopolitical Influences:** Geopolitical factors are also influencing market dynamics, particularly in the UK biotech sector where IPO plans are being shaped by global uncertainties despite robust venture capital backing. This situation underscores the complex interplay between regional economic conditions and global investment trends in biotech innovation. As these trends continue unfolding across the industry landscape—from AI-driven research advancements to strategic acquisitions—the potential impact on patient care paradigms remains profound. These developments not only promise new possibilities within drug development but also influence broader healthcare delivery models aimed at improving patient outcomes globally.Support the show

In this episode of Data in Biotech, host Ross Katz sits down with Woody Sherman, Founder and Chief Innovation Officer at PsiThera, for a conversation on why AI can transform drug discovery's paperwork and code while barely touching the hardest part of the problem: the molecules themselves. Woody's career runs through physical chemistry at MIT; over a decade at Schrödinger building tools the industry still relies on; founding Silicon Therapeutics (where his team took a small molecule STING agonist from concept to clinic in roughly three years); scaling that platform after Roivant's acquisition; and now leading PsiThera's effort to build oral small molecules for immunology targets that today are only reachable with injectable biologics. The conversation digs into why large language models excel at automation, coding, and regulatory writing but hit a wall when the task is predicting how a molecule behaves, what "physical AI" actually means as a category distinct from both LLMs and traditional physics-based simulation, and why representing molecules as quantum mechanical objects rather than text strings or 2D graphs changes what's predictable.  Woody also walks through the STING program in detail, why the field's excitement over fast co-folding models like Boltz needs a strong dose of skepticism, and what it takes to build a database and team culture where chemists, biologists, and data scientists can actually understand each other. What you'll learn in this episode: >> Why the contradiction of "AI is transforming drug discovery" and "drugs still take a decade and billions of dollars" can both be true at once. >> How Silicon Therapeutics engineered a small molecule STING agonist to dimerize itself through a quantum mechanical interaction that had never been designed for before. >> What "physical AI" means as a new category built on embeddings from orbital-level, quantum mechanical representations of molecules, rather than language tokens or force-field simulations. >> Why molecular representation is the whole game: the limitations of SMILES strings and 2D graphs versus true 3D, quantum mechanical embeddings like PsiThera's Psiformer model >> Why a widely publicized claim of near-FEP-quality binding affinity at 1,000x the speed didn't hold up under scrutiny. >> How PsiThera captures not just simulation and wet lab data but human chemist judgment and reasoning as structured data, and why building a shared vocabulary across computational and experimental teams is as important as any model. Meet our guest: Woody Sherman, PhD, is Founder and Chief Innovation Officer at PsiThera, a biotechnology company designing oral small molecule drugs for immunology and inflammatory diseases, starting with the TNF superfamily. His career spans physical chemistry research at MIT, more than a decade at Schrödinger developing computational drug discovery tools, founding Silicon Therapeutics (acquired by Roivant), and leading the platform's evolution through PsiThera today. He has published more than 100 peer-reviewed papers spanning molecular dynamics, quantum mechanics, free energy simulations, and machine learning for drug design. Connect with Woody Sherman on LinkedIn: https://www.linkedin.com/in/woodysherman/ About the host: Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Ross Katz on LinkedIn: https://www.linkedin.com/in/b-ross-katz/ Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn. https://www.linkedin.com/company/corrdyn/

How is artificial intelligence transforming the way we discover life-saving drugs and scale healthcare startups? In this exclusive interview, industry leaders break down the real-world applications, challenges, and future of AI adoption in the life sciences sector. From cutting-edge generative AI models used in small-molecule discovery to the economic hurdles facing Canadian tech ecosystems, our panel delivers a masterclass on navigating the intersection of technology and human health. 

In March, China became the first country to approve an invasive brain-computer interface beyond clinical trials. The implant, called NEO, is now available to some patients with limb paralysis due to a spinal cord injury. Ira talks with Wired staff writer Emily Mullin about the significance of this milestone. Plus, brain implants aren't the only development: China's entire biotech industry has skyrocketed in recent years. A decade ago, about 8% of new drug molecules were discovered in China. Now it's over 40%. And more clinical trials are now being conducted there than in the U.S. or Europe. Ira talks with health policy researcher So-Yeon Kang, who's been following the Chinese pharma industry's meteoric rise. Guests: Emily Mullin is a staff writer at Wired.  Dr. So-Yeon Kang is an Assistant Professor of Health Management and Policy at Georgetown University.  Other episodes you may enjoy: Advances In Brain-Computer Interfaces For People With Paralysis How China Is Driving Down Electricity Costs With Renewables Transcripts for each episode are available within 1-3 days at sciencefriday.com. Subscribe to this podcast. Follow our show on Instagram, TikTok, Facebook, and Bluesky @scifri and sign up for our newsletters. Got a science question that's keeping you up at night? Call us: 877-472-4374 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The following article of the Health industry is: 'Why Data Alignment Is Critical for Drug Discovery' by Denise Ferreira, Regional Manager LatAm, CAS, a division of the American Chemical Society. 

#thismorning | #Bio2026: Where #Investors Meet #Drug #Discovery | Kate Strayer-Benton and Andrew R. Snyder, Phd., Monash University | #Tunein: broadcastretirementnetwork.com #Aging, #Finance, #Lifestyle, #Privacy, #Retirement, #wellness

July 1, 2026: Your daily rundown of health and wellness news, in under 5 minutes. Today's top stories: Life Time CEO Bahram Akradi calls GLP-1 threat "a wrong bet," positioning MIORA clinics as companion to treatment as research shows pairing exercise could prevent 50,000 cardiovascular events Oura joins research initiative providing biometric data to study veterans undergoing psychedelic therapies, adding continuous physiological context to mental healthcare Anthropic launches Claude Science and internal drug discovery program focused on neglected diseases, using AI directly rather than just selling tools to life sciences companies More from Fitt: Fitt Insider breaks down the convergence of fitness, wellness, and healthcare — and what it means for business, culture, and capital. Subscribe to our newsletter → insider.fitt.co/subscribe  Work with our recruiting firm → https://talent.fitt.co/ Follow us on Instagram → https://www.instagram.com/fittinsider/ Follow us on LinkedIn → linkedin.com/company/fittinsider  Reach out → insider@fitt.co 

In this episode, Ed is joined by Ben Taylor, Chief Financial Officer and President of Recursion UK, to discuss how AI is reshaping drug discovery, biotech, and the future of medicine. Ben explains how Recursion uses AI, lab automation, biological data, and machine learning to improve the way new medicines are discovered and developed. They explore why drug discovery has such a high failure rate, how AI can open up new areas of biology, and what this could mean for healthcare over the next decade.

In this episode of Data in Biotech, host Ross Katz sits down with Paul Finn, Chief Scientific Officer at Oxford Drug Design, for a conversation on what it actually takes to find a drug molecule that works not just on paper but also in the lab, in the cell, and, ultimately, in the clinic. Paul brings four decades of experience across what became GSK, Pfizer, and a series of Oxford-area spinouts and has shepherded a compound all the way to a marketed drug. That perspective gives him a particular kind of skepticism toward AI results that look too good to be true because he's done the work of checking whether they are. The conversation moves through synthesizability as a first-class constraint, why chemistry has proven so much harder for AI than biology, how 3D molecular representation gets closer to the physics that actually matters, and what rigorous multi-parameter optimization looks like when you're trying to kill cancer cells and drug-resistant bacteria at the same time. What you'll learn in this episode: >> Why synthesizability is chronically underestimated and why changing a single atom in a structure can take a molecule from trivially easy to make to practically impossible >> How Oxford Drug Design constrains the generative search to reaction schemes and purchasable building blocks, and why that chemical space is still so vast that novelty is not meaningfully sacrificed >> Why most generative AI models learn from a 2D string representation of a molecule; two steps removed from the 3D physics that govern how a drug actually binds to its target >> How Bayesian optimization over reagent space, rather than molecular space, allows an active learning loop to focus on the structural patterns associated with activity >> Why benchmarking complex models against simple ones is the discipline that exposes false correlations and why Paul and his co-authors were able to recover the Halicin result using methods decades older than deep learning >> What a pharma company should actually ask an AI drug discovery vendor before buying what they're selling Meet our guest: Paul Finn is Chief Scientific Officer at Oxford Drug Design, a computational drug discovery company with roots in Oxford's chemistry department. His career spans over 40 years of computational drug discovery, from early structure-activity modeling in the 1980s through to modern generative AI methods, with deep experience at what became GSK and Pfizer before moving into the Oxford spinout ecosystem. At Oxford Drug Design, Paul leads internal programs in oncology and antibacterial resistance, combining novel computational methods with a rigorous, synthesizability-first approach to multi-parameter optimization. Connect with Paul Finn on LinkedIn: https://uk.linkedin.com/in/paul-finn-2250616 About the host: Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Ross Katz on LinkedIn: https://www.linkedin.com/in/b-ross-katz/ Connect with us: Follow the podcast for more insightful discussions on the latest in biotech and data science.Subscribe and leave a review if you enjoyed this episode! Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn. https://www.linkedin.com/company/corrdyn/

Check out the next episode of our podcast, Under the Surface. In episode 16, When Proteins Move: Woody Sherman on Computational Chemistry, Molecular Simulation, and the Future of AI in Drug Discovery, we chat with Woody Sherman, Founder and Chief Innovation Officer at PsiThera, and a longtime leader in computational chemistry, about how he went from studying quantum polymers to shaping modern tools like Induced Fit Docking.  Woody shares the moment that pulled him into protein simulations, his early exposure to AI at MIT, and how an internship at Biogen set him on the path to industry. He also reflects on his years at Schrödinger, building solutions, writing code, and learning how to solve real problems for scientists. Topics: How application scientists help connect research with real-world industry needs Woody's journey from university research to starting Silicon Therapeutics How tools like induced fit docking were created How drug discovery platforms have changed over time What's different between working in industry and in academia What's next for open molecular software and AI working together (02:05) Why mentorship matters for scientists (04:15) Woody's path through school and research (09:10) Shifting into custom molecular simulations (12:00) Going from the academic world to industry (15:00) Creating new tools for drug discovery at Schrodinger (22:10) Putting together a team of experts (26:15) Working together on drug design platforms (34:00) Leading application science teams around the world (41:45) Starting up Silicon Therapeutics (45:58) Progress in the development of the STING agonist medicine (49:00) Launching PsiThera (56:30) Focusing on inflammation and the immune system (60:15) Sharing science and data openly (69:00) How AI will shape the future of drug discovery (80:30) What Woody enjoys outside of work (82:20) Final thoughts and getting involved with the community Listener discretion is advised.  

Why This Episode MattersSabrina Maniscalco is one of the few people in quantum who has lived the full arc: two decades of academic work on open quantum systems and non-Markovian noise at Palermo, Turku, Edinburgh, and Helsinki, followed by founding Algorithmiq with three of her former researchers after an early Qiskit Camp. That trajectory matters now because Algorithmiq just had a landmark stretch — sole winner of the $2M Wellcome Leap Q4Bio prize for a quantum-enabled cancer drug discovery workflow, an €18M Series B, a global HQ move to Milan, and its Tensor Network Error Mitigation (TEM) function landing in IBM's Qiskit Functions catalog.If you're trying to make sense of where quantum software actually creates value before fault tolerance arrives — and what a credible "trajectory to advantage" looks like when paired with real clients in life sciences — this is a grounded, technically specific conversation with someone building it.EPISODE SPONSORThis episode is brought to you by Outshift, Cisco's incubation engine. The need for computational power is rapidly increasing in every sector. From drug discovery to material innovation to complex financial modeling, classical systems are reaching their absolute limits. It's time for a paradigm shift. The answer is a scalable quantum network, built on open standards and vendor-agnostic architecture. By uniting distributed quantum devices, you unlock limitless computational power.Learn more about the Cisco Universal Quantum Switch at Outshift.com.Go deeper with the blog post The switch that quantum networking has been waiting for.What We Get IntoWhy a background in open quantum systems and non-Markovian noise turned out to be unusually well-suited to running algorithms on noisy near-term hardwareThe actual science behind the Q4Bio winning workflow: simulating excited-state dynamics of a photosensitizer drug already in Phase II clinical trials, on up to 100 qubitsHow quantum-boosted DMRG works — and why it gives you a built-in benchmark against the best classical method via the bond dimensionThe tradeoff Sabrina would and wouldn't make between more qubits and lower noise, and why neutral atoms' slower sampling rates matter for chemistryWhy even fault-tolerant algorithms like quantum phase estimation still depend on getting state initialization and measurement rightAlgorithmiq's two-product structure: the Digital Quantum Interface (hardware-agnostic infrastructure) and the life sciences application frameworkHow methods built for chemistry are now opening doors into optimization and GenAI — and why that direction emerged from the work, not from a strategy deckWhat the move from Helsinki to Milan signals about the European quantum ecosystem and Algorithmiq's commercial scale-upHow an active learning pipeline is already proposing novel drug variants for synthesis in Prof. Sherri McFarland's labResources & LinksGuest & CompanyAlgorithmiq — The company Sabrina co-founded with Guillermo García-Pérez, Matteo Rossi, and Boris Sokolov; quantum software for life sciences and chemistry.Sabrina Maniscalco — University of Helsinki Research Portal — Publication record covering open quantum systems, non-Markovian dynamics, and quantum information.Sabrina Maniscalco — AI for Good Bio — Consolidated bio covering academic roles and advisory positions, including IQOQI Austria and CERN's Quantum Technology Initiative.The Q4Bio WinAlgorithmiq Wins $2M Wellcome Leap Q4Bio Prize — Company announcement detailing the photodynamic therapy workflow.Wellcome Leap — Q4Bio Prize Announcement — Funder's perspective on finalists and criteria.IBM Quantum Blog — Q4Bio Finalists — IBM's account of the workflow and quantum-classical integration.Funding & HQ MoveTech.eu — Algorithmiq's €18M Series B and Milan move — Coverage of Italy's largest quantum VC round to date.Quantum Computing Report — Algorithmiq Relocates to Milan — Strategic context including the Q4Bio win and IBM partnership.EU-Startups coverage — Investor lineup and Italy's National Quantum Strategy framing.Quantum Advantage & ToolingIBM Quantum Blog — The Dawn of Quantum Advantage — Includes Algorithmiq's TEM (Tensor Network Error Mitigation) function in the Qiskit Functions catalog.Algorithmiq & IBM Quantum Advantage Tracker — The heterogeneous materials experiment Algorithmiq and IBM put forward as a community benchmark.Silicon Republic interview with Sabrina — Useful prior context on her philosophy of using quantum to simulate quantum systems.Key Quotes & InsightsOn the foundation of the company's approach: "We learned very early what we thought were the bottlenecks of quantum computers — what you really need to worry about if you want to implement computation at scale." A direct line from Qiskit Camp Vermont to Algorithmiq's product strategy.On Q4Bio, in Sabrina's words: "This molecule is already in Phase II clinical trial. So it's not hydrogen. It's a real molecule." A useful counter to the common critique that quantum chemistry demos still live in toy-model land.On quantum-boosted DMRG (insight): In the worst case, the method matches the best classical technique; in the better case, it outperforms it — and the bond dimension tells you which regime you're in. Built-in benchmarking against the classical baseline.On the hardware tradeoff: Asked whether she'd prefer 100 higher-fidelity qubits or 200 noisier ones, Sabrina's answer is "it depends" — and the explanation about why neutral atoms' lower sampling rates limit chemistry use cases is one of the more concrete things you'll hear on platform tradeoffs.On strategy (insight): New verticals at Algorithmiq are ...

Good morning from Pharma Daily: the podcast that brings you the most important developments in the pharmaceutical and biotech world. Today, we delve into a series of significant advancements shaping the landscape of our industry. As technology continues to redefine traditional paradigms, the collaboration between Pfizer and Chai Discovery exemplifies this trend. By harnessing artificial intelligence, particularly through custom models like Chai-3, this partnership aims to revolutionize drug discovery. The integration of AI promises not only to accelerate the identification of biologics and antibodies but also to optimize resource allocation in research and development. Such technological integration could pave the way for an enhanced pipeline of innovative treatments, marking a transformative shift in how therapeutic candidates are developed. In the realm of regulatory developments, Lupin's Ranluspec has recently received FDA approval as an interchangeable biosimilar targeting VEGF-A for various retinal conditions. This move underscores the importance of biosimilars in providing cost-effective alternatives to expensive biologics, thereby expanding patient access to essential treatments for conditions like macular degeneration. Additionally, the MHRA's marketing authorization for Aujemflu, an adjuvanted trivalent influenza vaccine for adults aged 50 and over, reflects ongoing efforts to bolster protection against infectious diseases among vulnerable populations. Clinical trial advancements continue to highlight significant progress in therapeutic development. Otsuka Pharmaceuticals' Phase 3 data on Voyxact has shown promising stabilization of kidney function in patients with Immunoglobulin A nephropathy. This protein therapy targets autoimmune pathways, offering new hope for managing this chronic kidney condition. Similarly, Autobahn Therapeutics' Elunetirom has advanced to a pivotal trial following Phase 2 success in treating bipolar depression. This showcases the potential of small molecule therapies targeting thyroid hormone receptors. Meanwhile, Hikma Pharmaceuticals' victory in a landmark patent case regarding skinny labels marks an important development in pharmaceutical intellectual property rights. The unanimous Supreme Court ruling against Amarin supports the legitimacy of using skinny labels to market generic versions of drugs for non-patented indications. This decision could enhance market competition and drive down healthcare costs, setting a precedent for future intellectual property disputes. On the business front, strategic partnerships and mergers continue to shape industry dynamics. Gilead Sciences' acquisition of Ouro Medicines for $1.675 billion strengthens its autoimmune inflammation pipeline. This transaction exemplifies how major deals are reshaping therapeutic portfolios in response to growing demand for treatments targeting rare diseases. Financially, Solix Pharmaceuticals' success in raising $71 million to advance its siRNA pipeline across multiple therapeutic areas demonstrates investor confidence in RNA-based therapeutics as a promising frontier for innovative treatments. Conversely, challenges persist as evidenced by Takeda's $2.5 billion legal provision over an antitrust case related to Amitiza, underscoring ongoing financial risks associated with litigation in the pharmaceutical sector. Corporate restructuring also signals shifts within the industry landscape. Fulcrum Therapeutics' decision to lay off 85% of its workforce following the discontinuation of its sickle cell disease candidate highlights the volatility and high stakes inherent in drug development. Overall, these developments illustrate a dynamic landscape where scientific innovation is propelled by AI-driven approaches and strategic collaborations while regulatory victories and financial maneuvers shape market dynamics. These trends have profound implications for patient care by potentially accelerating the availability of novel therapies and fostering a competitive environment that drives down costs. As we look ahead, stakeholders must navigate these complexities effectively to harness opportunities and address challenges within this rapidly evolving industry landscape. The ability to adapt and capitalize on emerging trends will be crucial as these sectors continue to evolve, ultimately enhancing patient care and advancing therapeutic frontiers globally. Thank you for joining us today on Pharma Daily; stay tuned for more insights into the ever-changing world of pharmaceuticals and biotech.Support the show

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, podcast host and industry interviewer, is joined for a second time by Nandita Puri, PhD Researcher at Georgia Tech working at the intersection of bioinformatics and biochemistry. The conversation explores how AI is transforming drug discovery, accelerating hypothesis generation, reducing experimental costs, improving success rates, enabling rare disease research, and paving the way for virtual cell simulation. Key Takeaways AI Is Creating a New Drug Discovery Workflow: Puri describes a major transition from traditional laboratory-first research toward a hybrid approach combining computational and experimental science. Researchers can now use AI, machine learning, and pattern recognition to analyze massive biological datasets before conducting expensive laboratory work. According to Puri, "I see a healthy combination of 50% dry lab and wet-lab validation becoming the emerging standard." This shift allows scientists to move beyond manual analysis and leverage computational intelligence to generate stronger hypotheses, identify promising targets faster, and focus laboratory resources on the most promising opportunities. Higher Success Rates Mean Lower Costs and Less Waste: One of the most immediate benefits of AI in drug discovery is improved experimental efficiency. Puri notes that individual experiments can cost "$10,000-$12,000" and historically have carried significant failure risk. By consolidating fragmented datasets and identifying meaningful biological signals, AI helps researchers prioritize stronger hypotheses before entering the laboratory. Puri explained that some AI-assisted binder-development efforts achieved "40% 50% of success rate," compared with previous rates of "10% 5%." These improvements reduce wasted resources, shorten research timelines, and allow scientific teams to evaluate more potential treatments with the same budget. AI Is Unlocking Opportunities for Rare Disease Research: Rare diseases have historically faced funding and development challenges due to limited patient populations and expensive clinical validation requirements. Puri explains that AI is helping overcome these barriers by generating synthetic datasets, identifying hidden biological relationships, and revealing common signaling pathways between diseases. She notes that "AI is really, really helping rare disease industry to go forward." Visit Cloud Wars for more.

Drug discovery is already an incredibly difficult and tedious process, but what happens when there's little financial incentive to develop the medicine at all? On this exciting episode of Let's Talk Chemistry edited by Presley Vu, hosts Poorvi Iyer and Nina Deng talk with Dr. Michael Pollastri, senior vice provost and academic lead of the Roux Institute at Northeastern University. From his time as a bench chemist at Pfizer to his current role leading academic research on diseases affecting some of the world's most vulnerable populations, Dr. Pollastri discusses the realities of neglected diseases and the role academic labs play in addressing gaps in global healthcare research. We hope you enjoy!

Most people don't realize how broken drug discovery really is. According to Liran Belenzon, companies can spend seven years and hundreds of millions of dollars on a drug candidate—only to see it fail in human trials. In this episode, Liran explains why biology is one of the most complex systems humans have ever tried to understand and how AI can help researchers uncover patterns humans miss. The discussion explores why even small improvements in success rates could completely reshape healthcare outcomes worldwide. This episode is a powerful glimpse into the future of science and medicine. Learn more about your ad choices. Visit megaphone.fm/adchoices

Nicolai Tangen meets Pfizer CEO Albert Bourla for a wide-ranging conversation on leadership, science, and the future of global healthcare. Bourla reflects on leading Pfizer through the COVID-19 vaccine breakthrough and how it transformed the company. The discussion also dives into Pfizer's strategic shift toward innovative medicine, including major investments in oncology and obesity, and the high-stakes decisions behind multibillion-dollar acquisitions. Looking ahead, the conversation explores how artificial intelligence is set to transform drug discovery, clinical trials, and the broader healthcare system. Bourla offers a candid view on global competition, particularly the rapid rise of China in biotech, and what it will take for companies like Pfizer to stay ahead. Beyond business, Bourla opens up about leadership, how to build resilience, foster organizational confidence, and continuously evolve as a CEO. He also shares a deeply personal story about his mother, a Holocaust survivor, and how her perspective shaped his optimism and drive.In Good Company is hosted by Nicolai Tangen, CEO of Norges Bank Investment Management. New full episodes every Wednesday, and don't miss our Highlight episodes every Friday. The production team for this episode includes Isabelle Karlsson and PLAN-B's Niklas Figenschau Johansen, Sebastian Langvik-Hansen and Pål Huuse. Background research was conducted by Isabelle Karlsson. Watch the episode on YouTube: Norges Bank Investment Management - YouTubeWant to learn more about the fund? The fund | Norges Bank Investment Management (nbim.no)Follow Nicolai Tangen on LinkedIn: Nicolai Tangen | LinkedInFollow NBIM on LinkedIn: Norges Bank Investment Management: Administrator for bedriftsside | LinkedInFollow NBIM on Instagram: Explore Norges Bank Investment Management on Instagram Hosted on Acast. See acast.com/privacy for more information.

University of Utah chemist Matthew Sigman explains how machine learning is transforming drug discovery. By predicting how molecules form, especially their critical “handedness,” new tools can dramatically cut the time, cost, and trial-and-error required to develop life-saving medicines.

Jared Dashevsky, MD (Healthcare Huddle) and Ala Alenazi, PhD (Kinnevik) join Mustafa to discuss:The rise of the AI Broker (a middleman that's about to emerge)Palantir's £330M NHS break clauseOpenAI as pharma. We also discuss why drug discovery needs a "Human Genome Project 2.0"

Send us Fan MailIs the era of just managing Parkinson's symptoms finally coming to an end?In this clip from our episode “How AI Is Helping The Fight Against Parkinson's”, host David E. Williams and guest Gene Mack, CEO of Gain Therapeutics, share why the early signals from their lead drug candidate are too compelling to ignore.Listen to the full episode here

Send us Fan MailFor decades, Parkinson's patients have been offered only symptom management. No drug has ever slowed the disease itself. A small clinical stage biotech may be about to change that.Gene Mack, CEO, Gain Therapeutics joins host David E. Williams to discuss the science behind a potential first disease modifying therapy for Parkinson's, how AI is accelerating drug discovery, and what it takes to build a biotech in one of the toughest capital markets in years.

Invest Like the Best: Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- My guest today is Alex Karnal. Alex is the co-founder and managing partner of Braidwell, a life sciences investment firm he built after spending 15 years at Deerfield Management. The frame we use throughout the episode is the health stack. Alex talks about how most of the diseases that will claim most of our lives are already addressable with medicines that exist today. We work through the five layers of what a defensive health strategy looks like, why GLP-1 medicines represent the first commercial proof that people are ready to be proactive about their health, and why PCSK9 inhibitors may ultimately be the more important drug class even though they get far less attention. We also get into the science and business of drug discovery itself — why most of the published literature that AI companies are training on cannot be replicated, what it would mean to have a truly agentic scientific lab running 24 hours a day, and why Alex believes we are now on a deterministic curve toward scientific superintelligence in biology. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Visit ⁠vanta.com/invest⁠.  ----- ⁠WorkOS⁠ is a developer platform that enables SaaS companies to quickly add enterprise features to their applications. Visit⁠⁠ ⁠WorkOS.com⁠⁠⁠ to transform your application into an enterprise-ready solution in minutes, not months. ----- ⁠Rogo⁠ is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps: (00:00:00) Welcome to Invest Like the Best (00:02:29) Intro: Alex Karnal (00:03:15) State of the Union: GLP1s and Life Sciences (00:07:01) The Health Stack Framework (00:12:49) Breaking Down the 5 Defensive Layers (00:21:18) GLP-1: What's Driving the Inflection (00:28:28) Diet vs. Drugs: Is Food Enough? (00:31:15) Barriers to Access: Complexity, Cost & Compliance (00:35:04) PCSK9: The Closest Thing to a Free Lunch (00:44:10) Alzheimer's & Neurodegenerative Disease (00:46:59) Cancer: Early Detection & New Treatments (00:54:49) Body Imaging & Diagnostic Trade-offs (00:56:31) How Drugs Are Discovered (01:02:39) AI in Drug Discovery (01:10:57) The Automated Lab of the Future (01:13:05) Peptides & Citizen Pharmacology (01:16:45) Alex's Background (01:28:25) Braidwell's Investment Approach (01:30:39) The Kindest Thing

My guest today is Alex Karnal. Alex is the co-founder and managing partner of Braidwell, a life sciences investment firm he built after spending 15 years at Deerfield Management. The frame we use throughout the episode is the health stack. Alex talks about how most of the diseases that will claim most of our lives are already addressable with medicines that exist today. We work through the five layers of what a defensive health strategy looks like, why GLP-1 medicines represent the first commercial proof that people are ready to be proactive about their health, and why PCSK9 inhibitors may ultimately be the more important drug class even though they get far less attention. We also get into the science and business of drug discovery itself — why most of the published literature that AI companies are training on cannot be replicated, what it would mean to have a truly agentic scientific lab running 24 hours a day, and why Alex believes we are now on a deterministic curve toward scientific superintelligence in biology. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Visit ⁠vanta.com/invest⁠.  ----- ⁠WorkOS⁠ is a developer platform that enables SaaS companies to quickly add enterprise features to their applications. Visit⁠⁠ ⁠WorkOS.com⁠⁠⁠ to transform your application into an enterprise-ready solution in minutes, not months. ----- ⁠Rogo⁠ is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps: (00:00:00) Welcome to Invest Like the Best (00:02:29) Intro: Alex Karnal (00:03:15) State of the Union: GLP1s and Life Sciences (00:07:01) The Health Stack Framework (00:12:49) Breaking Down the 5 Defensive Layers (00:21:18) GLP-1: What's Driving the Inflection (00:28:28) Diet vs. Drugs: Is Food Enough? (00:31:15) Barriers to Access: Complexity, Cost & Compliance (00:35:04) PCSK9: The Closest Thing to a Free Lunch (00:44:10) Alzheimer's & Neurodegenerative Disease (00:46:59) Cancer: Early Detection & New Treatments (00:54:49) Body Imaging & Diagnostic Trade-offs (00:56:31) How Drugs Are Discovered (01:02:39) AI in Drug Discovery (01:10:57) The Automated Lab of the Future (01:13:05) Peptides & Citizen Pharmacology (01:16:45) Alex's Background (01:28:25) Braidwell's Investment Approach (01:30:39) The Kindest Thing

Good morning from Pharma Daily: the podcast that brings you the most important developments in the pharmaceutical and biotech world. Today, we're exploring a fascinating realm where technology and biology converge, starting with a deepening relationship between biopharma and artificial intelligence. Novartis CEO Vas Narasimhan's recent appointment to the board of AI company Anthropic signals the strategic integration of AI into drug discovery and development processes. This collaboration highlights a growing trend where pharmaceutical companies are increasingly leveraging AI to optimize clinical trials, streamline drug discovery, and personalize patient care strategies. Similarly, Novo Nordisk has announced a strategic partnership with OpenAI to integrate AI technologies across various facets of its operations, including drug discovery and manufacturing. By leveraging OpenAI's machine learning capabilities, Novo Nordisk aims to streamline research efforts and accelerate therapeutic identification—a collaboration reflecting AI's growing role as an essential tool for maintaining competitiveness in drug development. Additionally, Amazon Web Services' launch of the Amazon Bio Discovery AI tool marks another milestone. Designed to expedite antibody design and drug discovery processes, it provides researchers with robust AI-driven platforms enhancing therapeutic design speed and accuracy. The emphasis on monoclonal antibodies aligns with industry trends focusing on targeted therapies for diseases such as cancer. Meanwhile, Eli Lilly's new obesity treatment, Foundayo, has caught the FDA's attention due to potential safety concerns. Despite progressing with its launch, the FDA has requested additional safety information to address unexpected serious risks associated with the drug. This highlights the ongoing regulatory scrutiny that accompanies novel treatments, especially in areas like obesity where patient populations are large and diverse. In another strategic move, Eli Lilly's acquisition of Crossbridge Bio for up to $300 million aims to bolster its oncology pipeline with dual-payload antibody-drug conjugates (ADCs). This acquisition reflects a strategic move enhancing Eli Lilly's position in oncology by integrating cutting-edge ADC technologies known for delivering cytotoxic agents directly to cancer cells while minimizing off-target effects. On another front, Travere Therapeutics is mapping a pathway to a potential $3 billion opportunity in the U.S. market following significant approval for its treatment Filspari, targeted at rare kidney diseases. This approval underscores the increasing focus on rare diseases, which present lucrative opportunities for pharmaceutical companies due to significant unmet needs and often high-cost treatments. Astellas' manufacturing strategy underscores the importance of reliable supply as a critical bridge from research to patient care. Led by Chief Manufacturing Officer Rao Mantri, this strategy highlights how manufacturing excellence can significantly impact drug availability and patient outcomes. It emphasizes that production reliability is vital in ensuring groundbreaking research translates into accessible medical treatments. In contrast, a slowdown in IPOs has been noted amidst an aggressive merger and acquisition spree by major pharmaceutical companies. This consolidation trend reflects strategic shifts within the industry as companies seek to bolster pipelines through acquisitions rather than organic growth. Such dynamics indicate a strategic pivot as firms prioritize acquiring promising assets over developing them from scratch. Ionis Pharmaceuticals' recent win in a drug naming competition exemplifies the complexities involved in branding within the pharmaceutical sector. Crafting a drug name that is memorable yet distinctive involves balancing marketability with regulatory requirements—a reflection of the intSupport the show

In this episode, Frank and Candace sit down with computational chemist Mustafa Javaheri to explore how quantum insights are revolutionizing drug design. Together, they unpack the complex process of screening millions of compounds for drug discovery, discuss the unique advantages quantum computing brings to modeling biological systems, and address common misconceptions about the technology. From the challenges of building powerful quantum hardware to the interplay between AI and quantum chemistry, this conversation shines a light on the present realities and future possibilities at the cutting edge of science. Whether you're fascinated by the promise of faster drug discovery or simply curious about how quantum computers really work, this episode is packed with insights you won't want to miss.LinksMostafa's LinkedIn - https://www.linkedin.com/in/mostafa-javaheri-moghadam/Watch this show on YouTube - https://youtu.be/J0xbQzSoW-kTime Stamps00:00 Drug discovery using computational chemistry04:46 How quantum computers analyze proteins06:54 Comparing quantum and classical computers11:47 Current progress in quantum chemistry17:24 Using lasers and low temperatures19:03 How quantum computers process information24:30 Quantum mechanics in drug design28:22 Supportive mentors and new ideas32:16 Finding joy in problem-solving34:49 Importance of quality data in AI

Abbas Kazimi, CEO of Boston-based Nimbus Therapeutics, on computation and culture for drug discovery.

In this episode of Sounds of Science, Lauren and Matt Noonan share their powerful journey following their daughter Jane's diagnosis with Mowat-Wilson Syndrome. From unexpected medical challenges to finding community and launching their own nonprofit, the OURS Foundation, they discuss how advocacy, collaboration, and emerging research are shaping new hope for families living with rare diseases. Charles River | ASO Development Charles River | ASO Screening Services Charles River | Rare Disease Charles River | Rare Disease Research for Drug Development Mowat Wilson Foundation

In this episode of Data in Biotech, Ross Katz sits down with Robert Abel, Chief Scientific Officer of the Platform at Schrödinger, to explore how physics-based computational modeling is transforming drug discovery.  Robert unpacks why machine learning alone isn't enough to navigate the vast complexity of chemical space - an estimated at 10⁶⁰ possible drug-like molecules - and how integrating atomistic simulations with ML creates a more accurate, reliable, and scalable approach to identifying viable drug candidates. From free energy perturbation calculations to generative AI, Robert offers a rare inside look at how Schrödinger's technology platform is accelerating the path from target identification to clinical candidate and where the field is headed next. What you'll learn in this episode:  >> Why chemical space (~10⁶⁰ molecules) makes purely data-driven ML approaches fundamentally insufficient for drug discovery, and how physics-based sampling solves the training data problem >> How free energy perturbation (FEP) calculations enable quantitative prediction of protein-ligand binding affinities at near-experimental accuracy (~1.2 kcal/mol RMSE) >> How Schrödinger's active learning framework combines physics-based simulations and ML to triage billions of candidate molecules before committing to wet lab synthesis >> Why Schrödinger operates across three business lines; software licensing, collaborative programs, and proprietary drug discovery and how each strengthens the underlying technology platform >> Where the next frontiers lie: routine anti-target selectivity profiling, retrosynthetic AI integration, and the expanding role of generative ML in de novo molecular design Meet our guest: Robert Abel is Chief Scientific Officer, Platform at Schrödinger, where he helps lead the scientific direction behind computational approaches that support modern drug discovery and molecular design. With a PhD in Chemical Physics from Columbia University and a deep background in computational chemistry, he has held multiple senior science leadership roles at Schrödinger, guiding teams that build and scale scientific methods into production-grade platforms used across research and industry. Connect with Robert Abel on LinkedIn  About the host: Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Ross Katz on LinkedIn Connect with us: Follow the podcast for more insightful discussions on the latest in biotech and data science.Subscribe and leave a review if you enjoyed this episode! Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn.

This Week In Startups is made possible by:Luma AI - https://lumalabs.ai/twistEvery.io -  https://every.ioLemon.io - https://Lemon.io/twistPlaud - https://Plaud.ai/twistToday's show:What do drug discovery, the creator economy, and AI vision models have in common? In the case of Metanova, Bitcast, and Score, the answer is Bittensor. Yes, each of the three companies leverages the Bittensor network to get more work done, more quickly, in a completely decentralized fashion.Metanova uses its subnet to run developer competitions to find exciting molecular candidates, parsing through a mountain of possibilities to pluck out the most promising for further investigation.Bitcast uses its subnet to collect visibility demand from brands, which is served by video creators. The company is focused on the crypto niche to start, but will expand in time to other technology topics.Score uses its subnet to generate highly performant, specialized vision models, which it then sells to customers through a platform (Manako).In each case, the Bittensor's economic engine unlocks global creativity to tackle tasks that were previously time-consuming, fragmented, or expensive to complete. Let's see how quickly each company can scale and whether startups building on Bittensor can grow faster than their non-decentralized peers.Timestamps:0:00 Intro2:19 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at https://Plaud.ai/twist and use code TWIST for 10% off!3:40 What is Bittensor?7:22 Metanova Labs joins the show9:28 Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist17:16 How Metanova tackles the multi-billion dollar cost of drug discovery20:48 Every.io - For all of your incorporation, banking, payroll, benefits, accounting, taxes or other back-office administration needs, visit https://every.io30:20 Bitcast joins the show31:23 Luma AI - Luma builds accessible, professional-grade AI tools for creatives. Try Luma Agents for free at https://lumalabs.ai/twist32:30 Mining crypto with YouTube36:48 Why Bitcast is focused on the crypto space to start39:11 How healthy is the creator economy?47:26 When will the AI bubble collapse?53:44 Score joins the show54:42 How Score will make vision AI more accessible57:16 VLMs v. LLMs1:01:14 Demo of the Manako platformSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisCheck out all our partner offers: https://partners.launch.co/Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.com

Send us Fan MailIs this AI moment in healthcare really different from all the hype that came before?In this clip from our episode “A Brief History of AI in Healthcare”, Lekan Wang, Partner at JSL Health Capital, makes his case for why the data is finally backing up the optimism.Check out the full episode here

Send us Fan MailAI has been promising to transform healthcare for decades. So what's actually different this time? From Palantir's early data integration work to the frontier of AI-driven drug discovery, the evidence for optimism is growing and so is the urgency to get it right.Lekan Wang, Partner, JSL Health Capital joins host John Driscoll to discuss the real history of AI, where it's already delivering results in healthcare, and what investors are betting on next.

For more thoughts, clips, and updates, follow Avetis Antaplyan on Instagram: ⁠⁠⁠⁠⁠https://www.instagram.com/avetisantaplyan⁠⁠⁠⁠In this episode of The Tech Leader's Playbook, Avetis Antaplyan sits down with Alok Tayi, a Harvard-trained scientist, repeat tech founder, and the founder of Vibe Bio. Alok shares his journey from academia and engineering into entrepreneurship, where he built multiple pharmaceutical software companies collectively worth nearly $1 billion before launching Vibe Bio with a deeply personal mission. After his daughter was born with two rare diseases that had no available treatments, Alok turned his attention to one of biotech's most overlooked challenges: accelerating innovation for rare disease patients.The conversation explores how AI is changing drug discovery, why rare disease innovation has historically been underfunded, and how new tools, data, and regulatory pathways are creating fresh opportunities for founders and investors alike. Alok explains how Vibe Bio uses proprietary AI to evaluate drug programs, support pharma decision-making, and guide venture investments into high-potential therapeutics. He also shares hard-won lessons on leadership, mission-driven company building, culture, and the importance of staying obsessed with the problem while remaining flexible on tactics. This episode is a thoughtful look at the intersection of science, entrepreneurship, capital, and meaningful impact.TakeawaysIntro to Alok Tayi and the mission behind Vibe BioFrom scientist to serial founder in life sciences softwareHow Alok's daughter's diagnosis changed his life and careerLeadership lessons from scaling companies at different stagesWhat Vibe Bio actually does and how its AI worksWhy biotech and pharma are harder than most founders expectBalancing regulation, speed, and commercial realityWhy rare disease communities have been historically overlookedWhy rare disease innovation may become more viable nowWhy non-scientists can still play a major role in biotechCapital efficiency, biotech cycles, and the real funding questionWhy AI is an accelerant for biotech, not a replacementThe rise of parent-led and unconventional biotech foundersVibe Bio's AI platform versus its venture fundPlatform companies vs. individual therapy companiesHow AI-driven evaluation changes therapeutic investingAlok's biggest business and culture lessons as a founderBooks that shaped Alok's thinkingFinal advice on building with both impact and economic successChapters00:00 Intro to Alok Tayi and the mission behind Vibe Bio01:09 From scientist to serial founder in life sciences software03:16 How Alok's daughter's diagnosis changed his life and career04:28 Leadership lessons from scaling companies at different stages06:48 What Vibe Bio actually does and how its AI works10:37 Why biotech and pharma are harder than most founders expect13:51 Balancing regulation, speed, and commercial reality15:54 Why rare disease communities have been historically overlooked17:38 Why rare disease innovation may become more viable now19:25 Why non-scientists can still play a major role in biotech22:04 Capital efficiency, biotech cycles, and the real funding question24:33 Why AI is an accelerant for biotech, not a replacement26:57 The rise of parent-led and unconventional biotech founders29:50 Vibe Bio's AI platform versus its venture fund33:43 Platform companies vs. individual therapy companies37:12 How AI-driven evaluation changes therapeutic investing39:48 Alok's biggest business and culture lessons as a founder43:15 Books that shaped Alok's thinking46:22 Final advice on building with both impact and economic success48:29 Where to find Alok and Vibe BioAlok Tayi's Social Media Links:https://www.linkedin.com/in/aloktayi/https://x.com/aloktayiResources and Links:⁠⁠⁠⁠⁠https://www.hireclout.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.podcast.hireclout.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/hirefasthireright⁠

80% of all autoimmune diseases occur in women, and no one can explain why. Cancer cells are always present in your body, but it's only when your T cells go into energy deficit that cancer starts overtaking the system. And here's what almost no one is talking about: the mitochondria in your immune cells are the reason MS, chronic fatigue, neurodegeneration, and even cancer progression happen when they happen. In this episode, I sit down with Dr. Anurag Singh, MD, PhD immunologist who spent 20 years studying mitochondria and screened 4000 compounds from pomegranates to discover one molecule that changes cellular aging. We break down immunometabolism, the emerging field linking immune health and metabolism, why your T regulatory cells are the CEOs of your immune system, how mitochondrial dysfunction in immune cells triggers autoimmune conditions, and why rejuvenating mitochondria can get your immune system in check to defeat cancer. We also cover NAD+ (and why NMN and NR supplements don't work the way people think), the creatine sweet spot for muscle quality (500mg-1g, not the 5g everyone's taking), why Parkinson's is linked to paraquat, a mitochondrial toxin used in fertilizers and dry cleaning and how AI is fast-tracking the discovery of next-generation molecules for neurodegeneration. This conversation completely shifted how I think about immune health, brain protection, and what's actually driving the diseases we fear most. Reduce your risk of Alzheimer's with my science-backed protocol for women 30+: https://go.neuroathletics.com.au/youtube-sales-page Subscribe to The Neuro Experience for evidence-based conversations at the intersection of brain science, longevity, and performance. _____ TOPICS DISCUSSED 00:00 Intro: Why 80% of Autoimmune Diseases Occur in Women 01:24 Why Dr. Anurag Became an Immunologist 03:19 Immunometabolism: The Link Between Immune Health and Metabolism 04:20 T Cells, B Cells, and the Thymus Gland 05:51 MS and Autoimmune Disease: The T Regulatory Cell Problem 11:32 Mitochondrial Dysfunction and Immune Exhaustion 18:45 Cancer Cells and T Cell Energy Deficit 24:10 Urolithin A: Screening 4000 Pomegranate Compounds 31:20 Mitophagy and Autophagy: Cellular Housekeeping 38:50 NAD+ vs NMN and NR Supplements: What Actually Works 43:15 Creatine Dosing: The 500mg-1g Sweet Spot for Muscle Quality 48:30 Gut-Brain Connection and Neurodegeneration 50:54 Parkinson's Disease and Paraquat: The Mitochondrial Toxin 53:25 AI in Drug Discovery and Next-Generation Molecules 55:38 Skincare and Mitochondrial Health: Collagen Synthesis _______ Thank you to our sponsors KetoneIQ: https://ketone.com/NEURO for 30% OFF Caraway: Carawayhome.com/neuro10 Jones Road Beauty: https://www.jonesroadbeauty.com - Use code NEURO _______ I'm Louisa Nicola - clinical neurophysiologist - Alzheimer's prevention specialist - founder of Neuro Athletics. My mission is to translate cutting-edge neuroscience into actionable strategies for cognitive longevity, peak performance, and brain disease prevention. If you're committed to optimizing your brain- reducing Alzheimer's risk - and staying mentally sharp for life, you're in the right place. Stay sharp. Stay informed. Join thousands who subscribe to the Neuro Athletics Newsletter → https://bit.ly/3ewI5P0 Instagram: https://www.instagram.com/louisanicola_/ Twitter : https://twitter.com/louisanicola_ Learn more about your ad choices. Visit megaphone.fm/adchoices

Guest: Drs. Shuibing Chen and Hans Clevers, members of the Steering Committee for the ISSCR Consortium on Advanced Stem Cell-Based Models in Drug Discovery and Development, discuss the need to accelerate the responsible integration of stem cell–derived models into preclinical drug development. Their conversation reflects growing regulatory and policy momentum around new approach methodologies (NAMs) and underscores the importance of rigorous standards, regulatory alignment, and cross-sector collaboration to improve reproducibility and advance more predictive, human-relevant therapies. Building on its long-standing leadership in global standards, ethics, and policy, the ISSCR is uniquely positioned to convene industry, academia, and regulators around this effort. The initiative also reflects the Society's expanding industry engagement, with industry membership increasing nearly 180% over the past five years – creating new opportunities for strategic partnerships to address shared scientific and translational challenges. Featured Products and Resources: Learn how organoids can be used to expand clinical applications of diseases and disorders.   Get a free wallchart showing how organoids are used as model systems to study infectious diseases, cancer, congenital disorders, and tissue regeneration. The Stem Cell Science Round Up Treating Frailty with Stem Cells – In a clinical trial, mesenchymal stem cell therapy improved walking distance and physical function in older adults with frailty. Combined Bone & Bone Marrow Organoids – Researchers developed a scalable iPSC-derived bone marrow organoid that models human lympho-myeloid hematopoiesis and disease. CAR-NK Progenitors Prevent Relapse – Engineered pluripotent stem cell–derived CAR-expressing NK progenitor cells reduced minimal residual disease and prevented relapse in leukemia models following chemotherapy. Whole-Body Single-Cell Mapping – Scientists have developed a 3D single-cell-resolution map of mouse organs and the whole neonatal body. Photo Reference: Courtesy of Drs. Shuibing Chen and Hans Clevers Subscribe to our newsletter! Never miss updates about new episodes. Subscribe

On today's episode of Dr. M's Women and Children First Podcast, we welcome a scientist whose work has quietly shaped the cardiovascular health of millions around the world. Dr. Sundeep Dugar is a pharmaceutical innovator, inventor, and industry leader with more than three decades at the forefront of drug discovery. He is best known as a co-inventor of ezetimibe — marketed as Zetia® — a landmark cholesterol-lowering medication that transformed lipid management by targeting intestinal cholesterol absorption. He also co-inventor of the combination therapy Vytorin® (ezetimibe plus simvastatin), expanding treatment options for patients at high cardiovascular risk. For this groundbreaking work, Dr. Dugar and his colleagues received the prestigious 2005 National Inventor of the Year Award from the Intellectual Property Owners Association and the Heroes of Chemistry award from the American Chemical Society. Across his career, Dr. Dugar has contributed to more than 140 patents and has authored over 70 scientific publications, reflecting a lifetime devoted to translating chemistry into real-world therapies. He is currently the founder of Aayam Therapeutics, where he leads efforts to develop innovative, accessible medicines through collaborative global research. He also serves as Co-Chief Executive Officer of Blue Oak Nutraceuticals, advancing a novel mitochondrial-targeted compound known as Mitokatlyst™, designed to stimulate mitochondrial biogenesis and cellular energy — with potential implications for muscle strength, metabolic health, cardiovascular function, and inflammation. He is the first one to decipher the mechanism by which exercise induces mitochondria levels. Mitokatlyst mechanism of action mimics this process. Dr. Dugar's scientific journey spans continents and some of the world's premier institutions. He earned both his Bachelor's and Master's degrees in Organic Chemistry from the University of Delhi, completed his PhD in Chemistry at the University of California, Davis, and pursued postdoctoral research at ETH Zürich in Switzerland and at Cornell University. Today, we'll explore the story behind major pharmaceutical breakthroughs, the science of mitochondrial health, and what the future of therapeutics may look like when innovation meets global accessibility. Please join me in welcoming Dr. Sundeep Dugar.

Ep194: Ansu Satpathy on Cancer and Autoimmune Drug Discovery by Timmerman Report

a16z general partner Jorge Conde talks with Vasant Narasimhan, CEO of Novartis International, about transforming a 250-year-old conglomerate into a pure play medicines company and unlocking $180 billion of value in the process. They cover Novartis's platform technologies: cell and gene therapies, RNA medicines, and radioligand therapies. They also discuss AI in drug discovery, the rise of China as a biotech competitor, and what Vasant looks for when evaluating startup partnerships, including his advice on the killer experiments and CMC work that can make or break a deal. Resources: Follow Vasant Narasimhan on X: https://twitter.com/VasNarasimhanFollow Jorge Conde on X: https://x.com/JorgeCondeBio  Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.