Podcasts about montelukast

Broadcast from KSQD, Santa Cruz on 4-10-2025: Dr. Dawn responds to an email about difficult-to-control asthma, recommending quercetin and inhaled cromolyn as mast cell stabilizers, and suggesting Montelukast to address leukotrienes while investigating possible mold exposure as an underlying cause. She discusses groundbreaking research on age-related bone deterioration, explaining how osteocytes undergo structural changes with age, and exploring the concept of cellular senescence including potential treatments like quercetin/dasatinib combination therapy, fisetin, and metformin. A frequent caller with a history of sepsis, osteomyelitis and eye infections describes newly developed high blood pressure, with Dr. Dawn explaining how oxidative stress from infection can damage endothelial cells, reducing nitric oxide production and suggesting L-arginine, beet consumption, and proper blood pressure measurement techniques. Responding to an email about preventing cartilage loss, Dr. Dawn evaluates glucosamine sulfate research, noting key differences between effective and ineffective studies, while emphasizing the importance of achieving healthy body weight as a primary factor in preventing osteoarthritis progression. Dr. Dawn provides guidance to an email question about choosing a primary care physician before retirement, recommending selecting doctors established in their practice for 3-4 years and warning against Medicare Advantage plans that limit provider options. She addresses an email from someone experiencing persistent fatigue following Epstein-Barr virus reactivation, suggesting additional testing to confirm viral load through PCR rather than relying solely on antibody levels, while exploring alternative causes including long COVID, mold exposure, or autoimmune issues.

BUFFALO, NY — March 25, 2025 — A new #research paper was #published in Aging (Aging-US) on January 31, 2025, in Volume 17, Issue 2, titled “Cysteinyl leukotriene receptor 1 modulates retinal immune cells, vascularity and proteolytic activity in aged mice.” The study, led by first author and corresponding author Andreas Koller from the University Hospital of the Paracelsus Medical University, found that blocking an inflammatory receptor called CysLTR1 in the retinas of aging mice improved retinal health. These findings suggest a new approach to slowing age-related vision loss and protecting eye health in older adults. Age-related vision problems are a growing concern worldwide, and inflammation plays a key role in damaging the retina over time. The retina is the part of the eye that captures light and sends visual signals to the brain, making it vital for clear eyesight. In this study, scientists focused on the CysLTR1 receptor, which is known to promote inflammation and is found in high amounts in the retina. They explored whether blocking this receptor could reduce the harmful effects of aging in the eye. To achieve this, researchers treated aged mice with montelukast (MTK), a drug commonly used for asthma, which specifically blocks CysLTR1. The oral treatment lasted eight weeks and results were compared with both untreated aged mice and healthy young mice. After treatment, the older mice showed major improvements in retinal health. One key finding was a reduction in immune cells called microglia, which tend to increase with age and contribute to chronic inflammation in the retina. With CysLTR1 blocked, the number of these immune cells dropped significantly, suggesting reduced retinal inflammation. Lower inflammation is linked to a lower risk of age-related eye diseases like macular degeneration. “The reduction in immune cells caused by Cysltr1 suppression may dampen neuroinflammation, a known promoter of tissue aging.” Another important result was the restoration of blood vessel function. The tiny blood vessels in the retina had narrowed in aging mice, reducing blood flow and oxygen supply to the eye. MTK treatment increased the diameter of these vessels, improving circulation and possibly helping the retina work more efficiently. The study also indicated that blocking CysLTR1 helped boost the retina's natural ability to clear out waste proteins. As we age, this cleaning process slows down, allowing harmful material to build up in the eye. After treatment, the aged mice had stronger proteasome activity—the system responsible for breaking down cellular waste—and fewer signs of waste accumulation. Importantly, the treatment did not harm retinal nerve cells, which are essential for vision. This evidence indicates that the therapy was not only effective but also safe. While more research is needed to confirm these results in humans, this study highlights the potential of repurposing MTK to protect against age-related vision decline. Because it is already an approved drug, testing it for age-related eye diseases like macular degeneration or diabetic retinopathy could move forward more quickly. Blocking inflammation and supporting the eye's natural cleaning systems may be a promising new way to preserve healthy vision in aging populations. DOI - https://doi.org/10.18632/aging.206193 Corresponding author - Andreas Koller - a.koller@salk.at Video short - https://www.youtube.com/watch?v=ngnrPJzHlpI Please visit our website at https://www.Aging-US.com​​ and connect with us: Facebook - https://www.facebook.com/AgingUS/ X - https://twitter.com/AgingJrnl Instagram - https://www.instagram.com/agingjrnl/ YouTube - https://www.youtube.com/@AgingJournal LinkedIn - https://www.linkedin.com/company/aging/ Pinterest - https://www.pinterest.com/AgingUS/ Spotify - https://open.spotify.com/show/1X4HQQgegjReaf6Mozn6Mc MEDIA@IMPACTJOURNALS.COM

Dr Ross Walker joins Chris.See omnystudio.com/listener for privacy information.

What is the MOSAIC-NLP project around structured and unstructured EHR data? Why is structured data not really enough for drug safety studies? And to what degree is NLP speeding up access to data and research results? We will learn all that and more in this episode of Research in Action with Dr. Darren Toh, Professor at Harvard Medical School and Principal Investigator at Sentinel Operations Center. www.oracle.com/health www.oracle.com/life  www.sentinelinitiative.org -------------------------------------------------------- Episode Transcript: 00;00;00;00 - 00;00;26;14 What is the MOSAIC and LP project around structured and unstructured data? Why is structured data not really enough for drug safety studies? And to what degree is NLP speeding up access to data and research results? We'll find all that out and more on this episode of Research in Action. Hello and welcome to Research in Action, brought to you by Oracle Life Sciences.   00;00;26;14 - 00;00;50;14 I'm Mike Stiles. And today our guest is Dr. Darren Toh, professor at Harvard Medical School and principal investigator at Sentinel Operations Center. He's got a lot of expertise in Pharmacoepidemiology as well as comparative effectiveness research and real-world data. So, Darren, really glad to have you with us today. Thank you. My pleasure to be here. Well, tell us how you wound up where you are today.   00;00;50;14 - 00;01;26;22 What what attracted you in the beginning to public health? Good question. So I trained in pharmacy originally, and I got my Masters degree in Pharmaceutical Outcomes Research at a University of Chicago, Illinois, Chicago. And it's where I first learned about a field called Pharmacoepidemiology, which sort of very interesting to me because I like to solve problems with methods and data and pharmacoepidemiology.   00;01;26;22 - 00;02;00;29 It seems to be able to teach me how to do that. So I got into the program at the Harvard School of Public Health, and when I was finishing up, I was deciding between staying in academia and going somewhere and getting a real job. And that's when I found out about an opportunity within my current organization and I've heard great things about this organization.   00;02;00;29 - 00;02;29;26 So I thought I would give it a try. And the timing turned out to be perfect because when I joined, our group was responding to a request for proposal for what is called a mini sentinel pilot, which ultimately became the sentinel system that we have today. So I've been involved in the Sentinel system since the very beginning or before we began.   00;02;29;28 - 00;03;02;25 And for the past 15 years I've been with the system and the program and because I really like its public health mission and I'm also very drawn to the dedication of FDA, our partners and my colleagues to make this a successful program. Well, so now here you are, a principal investigator. What exactly is the Sentinel Operations Center? What's what's the mission there and what part do you specifically play in it?   00;03;02;27 - 00;03;52;26 Sentinel is a pretty unique system because it is a congressionally mandated system. So the Congress passed what is called the FDA Amendments Act in 2007. And within that FDA, the Congress asked FDA to create a new program to complement FDA existing systems to monitor medical product safety and more specifically, the Congress, US FDA, to create a post-market risk identification and analysis system that will be using data from multiple sources that will cover at least 1 million lives to to look at the safety of medical products after they are approved and marketed.   00;03;52;28 - 00;04;33;07 So in response to this congressional mandate, FDA launched what is called a Sentinel initiative in 2008 and in 2009 as I mentioned, FDA issued its request for proposal to launch the Mini Sentinel Pilot program, and the program grew into the sentinel system that we have today. So it's for my involvement. It sort of grew over time. So when I joined, as I mentioned, we were responding to this request for a proposal and we were very lucky to be awarded the contract.   00;04;33;09 - 00;05;04;05 So when it was starting, I serve as a one of the many epidemiologists on the team and I led several studies and I gradually took on more leadership responsibility and became the principal investigator of the Sentinel Operations Center in 2022. So I've been very fortunate to have a team of very professional and very dedicated colleagues within the operations center.   00;05;04;05 - 00;05;27;26 So on a day to day basis, we work with FDA to make sure that we can help them answer the questions they would like to get addressed. And we also work with our partners to make sure that they have the resources that they need to answer the questions for FDA. And most of the time I'm just the cheerleader in chief just to share my colleagues and our collaborators.   00;05;27;28 - 00;06;11;23 Now that's great. And and then specifically, there's the Mosaic NLP project that you're involved with. What is that trying to achieve and what are the collaborations being leveraged to get that done? So Sentinel Systems has always had access to medical claims data and electronic health record data or year data. One of the main goals for the current sentinel system is to incorporate even more data, both structured and unstructured, into the sentinel system and to combine it with advanced analytic methods so that FDA can answer even more regulatory questions.   00;06;11;25 - 00;06;40;09 So the Mosaic and NLP project was one of the projects that FDA funded to accomplish this goal. So the main goal of this project is to demonstrate how billing claims and data from multiple sources when combined with advanced machine learning and natural language processing methods, could be used to extract useful information from unstructured clinical data to perform a more robust drug safety assessment.   00;06;40;11 - 00;07;21;18 When we tried to launch this project, we decided that we would issue our own request for proposal. So there was an open and competitive process, and Oracle, together with their collaborators, were selected to lead this project. So I want to talk in broad or general terms right now about data sharing, the standards and practices around that. It kind of feels silly for anyone to say it's not needed, that we can get a comprehensive view and analysis of diseases and how they're impacting the population without it.   00;07;21;20 - 00;07;46;15 NIH is on board. It updated the DMS policy to promote data sharing. You know, the FDA obviously is leaning into this. So is data sharing now happening and advancing research as expected, or are there still hang ups? So I think we are making good progress. So I think the good news is data are just being accrued at an unprecedented rate.   00;07;46;17 - 00;08;28;21 So there are just so much data now for us to potentially access and analyze. There's always this concern about proper safeguard of individual privacy. And through our work, we also became very appreciative of other considerations, for example, the fishery responsibilities of the delivery systems and payers to protect patient data and make sure that they are used properly. So you mentioned the recent changes, including in data management, ensuring policy, which I think are moving us in the right direction.   00;08;28;26 - 00;08;56;23 But if you look closer at the NIH policy, it makes special considerations for proprietary data. So I would say that we have made some progress, but access to proprietary data remains very challenging. And the FDA, the NIH policy doesn't actually fully resolve that yet. When you think about the people who do make that argument for limited data sharing, they do mostly talk about what you just said about patient privacy.   00;08;56;23 - 00;09;25;20 IT proprietary data. Pharma is especially sensitive to that, I would imagine. So how do we incentivize the reluctant how can we ease their risks and concerns or can we? Yeah, it's a tough question. I think that this require a multi-pronged approach and I can only comment on some aspects of this. So I would say that at least based on our experience, the willingness or ability to share data often depends on the purpose.   00;09;25;23 - 00;09;55;29 That is, why do we need the data? Many data partners participate in Sentinel because of its public health mission, and our consideration is how would the data be used again, Is there proper safeguard of patient privacy and institutional interest? There are other ways to share data. For example, instead of asking the data to come to us, we can send analysis to where the data is.   00;09;56;06 - 00;10;34;22 And that is actually the principle follow by federated system like Sentinel. So we don't pull the data centrally. We send an analysis to the data partners and only get back what we need it. And it's usually in the summary level format. So that actually encourages more data sharing instead of less sharing. I would say that recent advances in some domains, such as tokenization and encryption, might also reduce some concern about a data sharing, a patient privacy concerns in academic settings.   00;10;34;29 - 00;11;24;26 We've been talking a lot about days, for example, for individual who collect the data and the people I propose to offer them authorship or proper acknowledgment if they are willing to share their data. But that is not sufficient in many cases outside of academic settings. If you look at what is happening in the past ten years or so, there are now a lot of what people call data aggregators that are able to bring together data from multiple delivery systems or health plans, and they seem to be able to develop a pretty effective model to convince the data provider to share that data in some way.   00;11;24;29 - 00;11;55;28 And a way to do that could be to help these data providers to manage their data more efficiently or to help them identify individuals who might be eligible for clinical trials. More quickly. So there are some incentives that we could think of to allow people to to share that data more openly but personally, I think that scientific data should be considered public good and hopefully that will become a reality one day.   00;11;56;00 - 00;12;23;21 Yeah, that's really interesting because it sounds like it's both a combination of centralized and decentralized tactics in terms of of data sharing and gathering. Why is it so important to use unstructured data in pharmacoepidemiology studies? And does NLP really make a huge difference in overcoming the limitations and extracting that data? So in the past, I think that that's true.   00;12;23;21 - 00;12;58;07 Now, many pharmaco epidemiologic studies rely on data. They are not collected for research purposes. So we use a lot of medical claims, data that are maintained by payers. We use each our data that are maintained by delivery systems. So this data are not created for research purposes and much of this data, at least for claim, is data stored in structured format using established coding systems like ICD ten.   00;12;58;10 - 00;13;39;06 Coding system and structured data sometimes are not granular enough for a given drug safety study and certain data or set of variables that are required for claims reimbursements or other business purposes might not be collected at all. And people felt that, well, maybe the information that we need could be extracted from unstructured data because as part of clinical care, the physicians or nurse practitioner or the health care provider might include that information in the notes, but use user data also pretty messy, especially that unstructured data.   00;13;39;08 - 00;14;05;25 So instead of going through the unstructured notes manually to extract this information manually, technique by natural language processing could help us do this task much more efficiently so that we can mind a larger model of unstructured data. Well, obviously, when it comes to real world evidence, you're a fan. Tell us what excites you about using it to complement clinical research.   00;14;05;25 - 00;14;42;07 Get us more evidence based insights and help practitioners make better decisions. Yeah, that's a great question. Yes, I'm a fan of so I personally don't quite like the dichotomy between conventional, randomized, controlled trial and real world data studies because they actually sit along a continuum. But is true that conventional randomized trials cannot address all the questions in clinical practice.   00;14;42;09 - 00;15;30;17 So that's where real data and real data studies come in, because real data like we discussed come from clinical practice. So they capture what happens in day to day clinical practice. So if we are thoughtful enough, we will be able to analyze the data properly and generate useful information to fill some of the knowledge gap. The truth is we have been using real data throughout the lifecycle of medical product development for many years now, ranging from understanding the natural history or burden of diseases to using real data as controls for single arm trials, and that we have been doing this before the term real data became popular.   00;15;30;19 - 00;15;57;11 So I see real data to complement what we could do in conventional randomized trials. So real data studies don't replace clinical trials. I see them to be complementary, and real data studies sometimes are the only way for us to get certain evidence. We already talked about Mosaic and LP that project, but I kind of want to go a little deeper with it.   00;15;57;11 - 00;16;42;02 The idea is to tackle the challenges of using link data structured and unstructured at scale. Tell us about a use case for that project and why it was chosen for this project. We actually, Cerner proposed to use the association between Montelukast, which is an asthma drug and neuropsychiatric events as a motivating example. It is also important to note that the project is not designed to answer this particular safety question, because if you look at the label of Montelukast, there's also already a box warning on neuropsychiatric events.   00;16;42;02 - 00;17;18;26 So FDA already has some knowledge about this being a potential adverse event associated with the medication. The reason why or recalls is has proposed this project was because we actually did look at this association in a previous sentinel study that only used structured data, although the study provided provided some very useful information. We also recognized that certain information that we needed was available in such a data, but may be available in unstructured data.   00;17;18;28 - 00;17;42;18 So if we are able to get more data from unstructured data, we might be able to understand this association better. So that's why this motivating example was chosen. Well, this is an Oracle podcast and Oracle is involved in Mosaic, so I think it's fair to ask you about the technology challenges that are involved in what you're trying to do.   00;17;42;19 - 00;18;17;24 What does the technology have to be able to do for you to experience success? So Mosaic in LP is I was at a very ambitious project because it is using an LP to extract multiple variables that are important for the study. That includes the study outcome, which when you look at it, is a composite of multiple clinical outcomes and it's also trying to extract important covariates that could help us reduce the bias associated with real data study.   00;18;17;26 - 00;19;01;24 So I think technology comes in well is powerful in many ways. First, thanks to technology, the project is able to access very large amount of data from millions of patients who seek care in more than 100 healthcare delivery systems across the country. So this was hard to imagine maybe ten or 15 years ago. But now we have access to lots and lots of data at our fingertips because of advances in technology, because of the large amount and the complexity of the data methods side and LP becomes even more important.   00;19;01;26 - 00;19;33;19 And for this project, we are also particularly interested in whether an LP algorithm developed in one year trial system could be applied to another system, which has been a challenge in our field because each year our system is created very differently. So one, an algorithm that works in one system might not work in another. So we are hoping that through advanced methods and technology, we will be able to address this problem.   00;19;33;21 - 00;19;57;15 So without this technology advances, we might not be able to do this study as efficiently as we could all So the task might might not be possible. So where are we going with this? I mean, let's say the project is a success. What will that mean in terms of the FDA's goals and how NLP gets applied in medical therapeutics safety surveillance?   00;19;57;18 - 00;20;38;03 The hope is that Sentinel system can answer even more questions than it can address today. And the way that we are trying to accomplish that is to see whether or how this complex, unstructured data, we combine it with advanced analytic methods can help us answer questions that could not be addressed by structured data alone. I think through this project we also learned a lot about how the challenges associated with analyzing a very large amount of data from multiple sources.   00;20;38;06 - 00;21;11;14 Again, service data is compiled from more than 100 systems, so it is big but also very complex. And in many of our studies we really need that large amount of data just to be able to answer the question because we may be focusing on rare exposures or real come. So you really need to start with very large from our data just to get to maybe the ten patients that are taking a medication.   00;21;11;17 - 00;21;44;15 And what you learn with Mosaic, can that get applied to addressing other public health issues like disparate ease and asthma diagnosis and treatment, especially when you think about diverse groups? Yeah, that's a great question. So is the project is not designed to address these important questions, but if we are able to better understand the completeness of social drivers of health in these data sources, then we will be able to leverage this data to answer these questions in the future.   00;21;44;18 - 00;22;04;26 I think about how a project like this gets a evaluated at various steps along the way. I guess that's my question. How I mean, what what methods are used to ensure the validity of real world evidence? So the good news is in the past few decades we have been using real data, even though we might not be using the term.   00;22;04;28 - 00;22;36;22 So there's been a lot of progress in the field to improve the validity of Real-World Data studies. So we now have a pretty good framework to identify fit for purpose data, and we also have very good understanding of appropriate design and analytic methods. So to target trial emulation and propensity score methods. So this project and many other projects in Sentinel are following this principle.   00;22;36;24 - 00;23;14;03 And one thing to also note that this project is also following the overall sentinel principle in transparency. So everything we do will be in the public domain to allow people to reproduce, so replicate the analysis. So the protocol is available in public domain, and when we are done with the study, everything will be made publicly available. So that's one way to make sure that the the work at least is reproducible or replicable.   00;23;14;05 - 00;23;43;00 And through that process, we hope to be able to improve the validity of this study. And what about comparisons? How do you compare the results from different data sources like claims data, structured data? You know, I extracted unstructured data, all of that. How was that done, the comparisons? So if you're talking about the Mosaic and LP study, so we have a pretty structured approach to address that question.   00;23;43;02 - 00;24;13;14 So we are using this proven principle of changing one thing and keeping everything else fixed to see what happens. So the project will start by using only claims data to replicate the previously done Sentinel study. And then we are going to add on such data to see whether the results are different. And then we add on an LP extract that unstructured data one at a time to see whether the results change.   00;24;13;21 - 00;24;40;24 So by fixing everything else to be constant and changing one thing, we'll be able to assess the added value of each how data, both structure and structure. And that's how we are going to do it within the Mosaic and LP study. And then what about scalability? How would you make sure the NLP models that you develop are scalable and transportable across all these different health systems of which there are many?   00;24;40;27 - 00;25;10;10 Yeah. The question again is about transport ability. So one thing that is unique about this study, as we briefly discussed earlier, was that the the survey yesterday to actually come from multiple healthcare systems. So the end up models that we are developing will be trained in tune on a sample of patients from this system and not from a single hospital network.   00;25;10;10 - 00;25;42;18 So at the development phase, we are already taking into account the potential diversity of different delivery system. And as part of this project, we also include another delivery system to apply and test the method as part of the transport ability assessment. So we are doing that to make sure that the LPI models that we are developing for this project will be useful for other system as well.   00;25;42;20 - 00;26;12;29 Unknown There is a larger question about computational resources, so that will be the issue that would still need to be addressed because a train and tuning this and NLP models within such a huge amount of data requires a lot of computing resources. So that is something that we could only partially address in our study. But if we want to apply or do the same thing in our system, that would be something to consider.   00;26;13;02 - 00;26;43;13 We talked a little bit about the collaboration with your tech partner, but these things usually have so many stakeholders and disciplines and silos. Tell us first why collaboration is a good thing and unavoidable anyway, and then what the challenges of collaboration are. Maybe some tips on how to best make them work. The problems that we face, at least many of the problems that I face quite complex and they require expertise from multiple domains.   00;26;43;13 - 00;27;18;19 So that calls for collaboration from multiple stakeholders. And we always have our blind spots. So we only see things in a certain way and we always miss things. So that's why I think collaboration is important. But it's really hard sometimes because we all have our priorities and perspectives and sometimes they don't align. And I also learned throughout the years that we don't communicate enough and we may also not have time to communicate or we may be under pressure to deliver.   00;27;18;21 - 00;27;47;21 So all of that sort of contribute to the challenges of collaborating effectively, especially when you collaborate across disciplines, because we might be using different languages to mean the same thing or use the same term to describe different things. So even though we can all speak the same language less English, we might not be talking about the same thing and not communicate at all.   00;27;47;21 - 00;28;17;25 Because because we are using different joggers and terminology. So that has been tough. But I think we are getting better. And so I think that it is for us within the center of operation center, we try to communicate honestly and respectfully and we try to understand different perspectives and we try to find common ground. And but I think ultimately what brings us together is that we have a shared common goal.   00;28;17;27 - 00;28;44;17 A lot of the work that we do. So for music and NLP, we are all trying to answer the same question, which is that how do we use unstructured data and advanced analytic methods to answer safety question? So once we apply on this common goal, things become easier because we start to understand each other better or be able to communicate more effectively.   00;28;44;19 - 00;29;19;16 Just out of curiosity, what are the different stakeholders involved in Mosaic? Who falls on the roster? we have people from different disciplines, so we have experts in natural language processing and artificial intelligence. We have epidemiologists, both statisticians, clinicians, we experts in psychiatric conditions and respiratory disease. We have data scientists, we have engineers, we have project managers. So it's a very big group of individuals with different expertise in this project.   00;29;19;18 - 00;29;46;14 Well, you probably noticed Oracle's really thrown itself into and committed huge resources to health and life sciences. Things got really exciting with the acquisition of Cerner and Cerner and Visa. What's Oracle doing right and what do you think it should be doing to make itself even more valuable in health and life sciences? Well, this is a great but very difficult question, so I cannot comment too much what Oracle is doing or will be doing.   00;29;46;17 - 00;30;23;06 But I can say more generally that there have been a number of technology companies that have tried to foray into health or life sciences. I would say with mixed results. And one reason is that our health care system remains highly fragmented and complex, so it takes a lot of energy to break the status quo. So you probably know that we were one of the last countries in the world to transition from ICD nine to ICD ten coding system, and we are soon going to move into the ICD 11 system.   00;30;23;06 - 00;31;00;05 So I'll be interested to see whether the US is ready for that. And that again, is maybe a reflection of just how complex and fragmented our system is and disruptive innovation and I think are great, but they may or may not translate into successes when they applied to health care. That is not to say tempesta mistake. I'm actually pretty optimistic that the perspectives and solutions and ideas brought by technology companies could help us solve a lot of problems that we have today.   00;31;00;07 - 00;31;31;26 But I think that it will be good to engage people who will be struggling with these issues early on and to work together with them to develop solutions that are not just good on paper, but also feasible in practice. So at least in my very limited experience, we have seen some very cool technology that ended up not being useful for health care just because it's very hard to change what people have been doing.   00;31;31;28 - 00;31;56;09 So again, disruptive innovations are good, but sometimes it's just very hard to adopt, at least not quickly enough for for us to see meaningful changes. Yeah, that's really fascinating. It's, you know, it is disruptive innovation, but it's not always applicable to the to the goals you're pursuing. But it does feel like technology where that's concerned, the future is coming at us faster and faster.   00;31;56;11 - 00;32;32;21 So what are the technologies that are most interesting to you? Is it A.I. or what big advances in public health do you see coming? Maybe sooner than we thought. Yeah. Yeah. You know, I feel like you said some of this came too fast. Like, I wish I. And closer to retirement, I don't worry about this. But so even though I say disruptive innovation sometime might not work in health care, but I will say generative A.I. seems to be a recent exception.   00;32;32;24 - 00;33;10;14 So I would say that generative is definitely on the list of things that surprised me in a very nice way. I will also say that the continue fast accrual of better real data is also something that excites me and the continue recognition or increased recognition of the potential real data of. It's also something that I think is good to have for things that came sooner than I found it again, generative.   00;33;10;19 - 00;33;44;13 AI So if you ask me when, we'll be ready for generally. AI Last year or two years ago, I would say not yet, but now we in the era where everything seems possible. So I remain extremely optimistic about generative in some of these last language models that will help us analyze unstructured data even more efficiently. Well, therein it's deeply fascinating and exciting stuff.   00;33;44;14 - 00;34;10;27 Thanks again for letting me pester you with these questions. If our listeners want to learn more about Sentinel, Operation Center or Mosaic or you, what's the best way for them to do that? So Sentinel has a poverty website where we post everything that we do. So is Sentinel initiative dot org. So I am a member of the Department of Population Medicine at Harvard Medical School.   00;34;10;29 - 00;35;00;16 So our website's population is a thought, but these would be two places that would be very informative for audience. Who wants to know more? All right. We appreciate that. And to our listeners, go ahead and subscribe to the show. Feel free to listen to past episodes because they are free. There's a lot to learn here. And if you want to learn more about how Oracle can accelerate your own life sciences research, just go to Oracle dot com slash life dash sciences and we'll see you next time on Research in Action.

Dr Dave teaches Dr Jo about Heart Foundation resources, Atrial fibrillation and anticoagulation, Liquid morphine formulations, Liraglutide and dulaglutide, Oestrogen patches, Potassium in dietary supplements, Medicine-induced hyponatraemia, pseudoephedrine, Prescribing to competitive athletes subject to drug testing, Montelukast, Vitamin D supplementation in pregnancy and infants, and Abortion reversal.

Lamotrigine is an antiseizure medication and also may be used for bipolar disorder. A rash is a major side effect to remember with this medication. Valganciclovir is an antiviral medication that can be used to prevent cytomegalovirus (CMV) in patients with a suppressed immune system. Fluconazole is an azole antifungal that can be used to treat candidiasis, blastomycosis, and tinea infections. Drug interactions, QTc prolongation, and hepatotoxicity are potential risks. Atenolol is a beta-blocker used to treat atrial fibrillation and hypertension. It is relatively selective for beta-1 receptors meaning that it doesn't affect the lungs as much as non-selective agents. Montelukast is a medication that blocks the actions of leukotrienes. This can be beneficial for the management of allergies and asthma.

Một loại thuốc trị hen suyễn thông thường dành cho trẻ em có liên quan đến ba vụ tự tử ở Úc và hàng trăm ca bệnh khác. Các bậc cha mẹ đang kêu gọi Cơ quan quản lý dược phẩm Úc làm theo quy định của Châu Âu và Hoa Kỳ là dán nhãn “cảnh báo trên hộp thuốc”.

Listen to Mike's personal account of his experience with Montelukast, a medication he had been taking since he was 14 years old. He vividly describes the physical and mental struggles he endured until one day he discovered a black box warning associated with this drug. Being forced to abruptly stop taking it, Mike gradually realized that many of his ongoing physical issues were linked to his use of Montelukast.It's crucial to hear Mike's story and be aware of the potential side effects of this medication, including its ability to permeate the blood-brain barrier. In a previous episode, we also discussed the drug's impact on a guest's daughter. Remember, knowledge is power, and this is an episode you do not want to miss!Montelukast Facebook GroupSupport the show

In this episode we discuss the evidence behind the effectiveness of watchful waiting, weight loss, Montelukast, and adenotonsillectomy in the treatment of obstructive sleep apnea (OSA) in pediatrics. This episode's guests are Miriam Weiss, CPNP-PC and Mariana Bedoya, MD.

Chris and Ashley share their story with us about their daughter, Genevieve.  Genevieve left this world 15 months ago, which also left a lot of unanswered questions for her parents.  As Chris and Ashley have sifted through journals and Genevieve's phone, they have discovered a lot, which led to even more questions.  In this episode, Chris and Ashley share with us so many things about suicide and what kids are going through at such young ages.  They also share a medication that Genevieve was using for asthma called Montelukast (Singulair).  Like every medication, there are side effects, but one of the side effects of Montelukast (Singulair) is suicide ideation.  This is a new side effect that has just been made public by the Black Box Warning issued by the FDA.  At the time of Genevieve's passing, they had no idea that this was a side effect.  It is not on the box, you have to do some digging to find ALL of the side effects of this medicine. Chris and Ashley are on a mission to educate while bringing awareness and love to those suffering.  We are so proud and feel so honored to be able to share their story with all of you.  Resources: Facebook support group for Montelukast (Singulair) Side Effects https://www.facebook.com/groups/40378158644/?ref=share&mibextid=NSMWBT Facebook support group 'Parents who have lost a child to suicide https://www.facebook.com/groups/53437786878/?ref=share&mibextid=NSMWBT Utah Suicide Prevention Coalition https://www.cachecounty.org/fairgrounds/live-on.htmlLive On Utah https://liveonutah.org/ Boxed warning about mental side effects for Singular https://www.fda.gov/drugs/drug-safety-and-availability/fda-requires-boxed-warning-about-serious-mental-health-side-effects-asthma-and-allergy-drug

Some oddball additional medications in asthma treatment, including theophylline, montelukast, cromolyn, methylprednisolone, omalizumab Need more help; you can find many of my mnemonics books on Audible that you might be able to get your first for free if you've never had one before.  https://www.audible.com/pd/Memorizing-Pharmacology-Mnemonics-Audiobook/B07DLGC8MP?source_code=AUDFPWS0223189MWT-BK-ACX0-118296&ref=acx_bty_BK_ACX0_118296_rh_us    

Download the cheat: https://bit.ly/50-meds  View the lesson: https://bit.ly/MontelukastSingulairNursingConsiderations    Generic Name montelukast Trade Name Singulair Indication prevent or treat asthma, manage seasonal allergies, prevent exercise-induced bronchoconstriction Action disrupts the effects of leukotrienes which effect airway edema, smooth muscle constriction, and cellular activity Therapeutic Class allergy, cold, and cough remedies, bronchodilators Pharmacologic Class Leukotriene Antagonist Nursing Considerations • assess respiratory status • assess liver function tests • medication does not treat acute asthma attacks

In the first episode of Pulmpod we discuss the newly imposed FDA black box warning on montelukast and what are some of the evidence behind it including the justification and previous instances in the history of medicine and their implications.

This week, we alerted listeners to the drug montelukast, brand name Singulair. This anti-leukotriene drug is commonly given to children and adults with allergies and asthma. The manufacturer has known for at least ten years that it can cause severe psychiatric effects in children, and yet the drug continues to be prescribed. I discussed the […]

Research supports the individualized medicine approach of Functional Medicine for rheumatoid arthritis; Montelukast should not be used for just allergic rhinitis because of mental health side effects; Using drug mining to find new uses for old medications -- demonstrated to find to combat Zika virus neural damage; The variety of GI microbiome tests reveals interest but show inconsistent results; Scandal concerning the EPA panel that regulates particulate size pollution; Research suggests COVID-19 lockdowns decreased premature births; Safe doses of Tylenol vary with age and amount of alcohol consumption; Bilirubin is shown to be anti-inflammatory and influential to the immune system -- it is not just a waste product; Review of supplement dose suggestions for calcium, magnesium, vitamin K2, vitamin D and omega 3 fatty acids

Research supports the individualized medicine approach of Functional Medicine for rheumatoid arthritis; Montelukast should not be used for just allergic rhinitis because of mental health side effects; Using drug mining to find new uses for old medications -- demonstrated to find to combat Zika virus neural damage; The variety of GI microbiome tests reveals interest but show inconsistent results; Scandal concerning the EPA panel that regulates particulate size pollution; Research suggests COVID-19 lockdowns decreased premature births; Safe doses of Tylenol vary with age and amount of alcohol consumption; Bilirubin is shown to be anti-inflammatory and influential to the immune system -- it is not just a waste product; Review of supplement dose suggestions for calcium, magnesium, vitamin K2, vitamin D and omega 3 fatty acids

Montelukast is best used as an adjunctive drug. It is best when used for the treatment of allergic rhinitis, asthma, and exercise induced bronchoconstriction (EIB). The brand name is Singulair. This drug works through selectively inhibiting the cysteinyl leukotrienes which leads to pulmonary and nasal mucosal benefits along with the alteration of the inflammation process. This comes in several dosage forms being 4 mg packets/granules, a 10 mg tablet, and in 4 mg and 5 mg chewable tablets. Common side effects include dizziness, fatigue, urticaria, and infection. There is a black box warning for serious neuropsychiatric events so it is very important to access/watch for serious signs and symptoms that may be of neuropsychiatric nature, and to weigh the risk/benefits for patient usage. Go to DrugCardsDaily.com for episode show notes which consist of the drug summary, quiz, and link to the drug card for FREE! Please SUBSCRIBE, FOLLOW, and RATE on Spotify, Apple Podcasts, or wherever your favorite place to listen to podcasts are. The main goal is to go over the Top 200 Drugs with the occasional drug of interest. Also, if you'd like to say hello, suggest a drug, or leave some feedback I'd really appreciate hearing from you! Leave a voice message at anchor.fm/drugcardsdaily or find me on twitter @drugcardsdaily --- Send in a voice message: https://anchor.fm/drugcardsdaily/message

In this episode:  When and how do you start a young child (

We speak with Dallas Children's Hospital's Section Chief Dr. Ron Mitchell about Management of Pediatric OSA. --- EARN CME Reflect on how this Podcast applies to your day-to-day and earn AMA PRA Category 1 CMEs: https://earnc.me/3VIka3 --- SHOW NOTES In this episode, Dr. Ron Mitchell, a Pediatric Otolaryngologist, joins our hosts Dr. Gopi Shah and Dr. Ashley Agan to speak about pediatric Obstructive Sleep Apnea (OSA) and its evaluation and management. Dr. Mitchell starts off the discussion by speaking about the importance of sleep and initial presentations and symptoms of sleep apnea in children, including apneic episodes, fatigue, and inattention as well as studies that recommend tonsillectomy for pediatric OSA. Dr. Mitchell then speaks about a current study underway that looks at OSA in pediatric patients with mild symptoms and the indications of surgery and if it is necessary in all patients. It is analyzing patients undergoing medical therapies, including Montelukast, nasal steroids, and others to evaluate efficacy against surgery. Specific indications and situations are also discussed. Dr. Mitchell notes that initially, with patients with mild symptoms, a sleep study may not be necessary. On the other hand, those undergoing high risk surgery or other developmental delay may need a sleep study, with observation and symptoms being the primary method of evaluation of progress. It is important to assess goals of the family prior to making the decision to obtain a sleep study with shared decision making. Dr. Mitchell then speaks about the impact of COVID on obtaining sleep studies and the effects on evaluation of pediatric OSA. He then indicates that home sleep studies may not be beneficial to obtain in the pediatric population, unlike in adults. The discussion continues onto the topic of tonsil size and the variable effect it can have on pediatric OSA. The history of tonsillectomies is further discussed with possible causes for the increase in the number of tonsillectomies for sleep related problems. The discussion rounds out on the important consideration of patients who undergo surgery with tonsillectomy and adenoidectomy with persistent OSA. Dr. Mitchell mentions possible etiologies (adenoid regrowth, nasal obstruction, etc.) which can be evaluated with nasal endoscopy and managed with nasal steroids. Weight loss in overweight and obese patients may also be beneficial. Other important considerations would be in patients with Down Syndrome, due to the difficulty of implementing CPAP and other managements. In these patients, sleep MRI is useful in determining the site of airway obstruction, usually at the tongue base, with additional surgery being useful for them.

This week we cover the the risk of antihypertensive med use during the pandemic; The Emergency Use Authorization for remdesivir in hospitalized patients with suspected or confirmed COVID-19; The addition of a Boxed Warning to Montelukast; A new Farxiga indication; And a novel treatment for acute migraines.

Here are the links for everything discussed in Episode 24. Approval of Sarclisa for Multiple Myeloma Durysta approval for OAG and OHT New boxed warning for montelukast products CDC updates on COVID-19 CDC updates on influenza reporting Connect with The Rx Daily Dose:Twitter      Instagram      YouTube      Linkedin       WebsiteEmail: therxdailydose@gmail.comConnect with Ian Parnigoni PharmD. on social media:Twitter       Instagram       Linkedin  ★ Support this podcast on Patreon ★

Do you know why mental health history is essential when deciding your controller medication?   Dr G shares her top tips on using inhalers and when it is appropriate to use a nebulizer. She also explains the side effects of certain controller medications and why doctors need to know more about you as a patient (even your mental health) when prescribing a controller medication. The decision of going on medication should be made with you in mind.    What we cover in this episode: Inhaler tips: know that there are different brand names for the same medicine, using a spacer, how to remember to take your controller The side effects of inhalers What are nebulizers and when are they used (at home and the ER) Montelukast is a leukotriene receptor antagonist. When it is prescribed and the side effects.  Why you want to disclose your mental health history with your allergist when decided what medication to go on.    Supporting information and a graphic of all asthma medications: https://www.itchpodcast.com/post/episode-13

On this episode, I discuss montelukast pharmacology Montelukast is a leukotriene receptor antagonist. Leukotrienes play an important role in causing inflammation and smooth muscle contraction in asthma and allergic rhinitis. Because montelukast blocks the effects of leukotrienes, it can be advantageous to use this medication for allergies and asthma. It is important to remind patients that montelukast is NOT a substitute for an acute relief medication like albuterol in the management of asthma symptoms. Montelukast has been reported to cause mood and behavioral changes and it is important to monitor our patients for these rare concerns.

In this episode, Daniel Searing, MD, Professor of pediatrics and allergies at Children's Colorado, talks about seasonal allergies and pollen. He discusses the effects of pollen, how to treat and alleviate allergies, and more. In this episode, Dr. Searing discusses: Pollen and how it affects allergies Why cottonwood trees are a big pollinator, especially in the springtime Why rain and humidity shut down pollen levels Why Colorado's climate makes people more susceptible to allergies How allergy symptoms will vary from year to year The importance of monitoring the quantitative level of pollen in the environment How physicians should manage the initial approach to a child with allergy symptoms Key features to look out for Why treating pollen allergies with persistent treatment is more effective What role the prescription drug Montelukast plays in treating allergic rhinitis What you can do to help prevent pollen from spreading Which medicines and therapies can help alleviate allergies When to see a doctor for seasonal allergies The approach of an immunotherapy treatment plan and the two phases of a typical treatment schedule

Got Hay fever, me too, well, I did. I've been taking Fexofenadine and Montelukast, let me explain how this went down. Please note, this is not medical advice, just me solving my hay fever, feel free to do as you please with this advice and solving your own hay fever. 

In this episode, Daniel Searing, MD, Professor of pediatrics and allergies at Children's Colorado, talks about seasonal allergies and pollen. He discusses the effects of pollen, how to treat and alleviate allergies, and more. In this episode, Dr. Searing discusses: Pollen and how it affects allergies Why cottonwood trees are a big pollinator, especially in the springtime Why rain and humidity shut down pollen levels Why Colorado's climate makes people more susceptible to allergies How allergy symptoms will vary from year to year The importance of monitoring the quantitative level of pollen in the environment How physicians should manage the initial approach to a child with allergy symptoms Key features to look out for Why treating pollen allergies with persistent treatment is more effective What role the prescription drug Montelukast plays in treating allergic rhinitis What you can do to help prevent pollen from spreading Which medicines and therapies can help alleviate allergies When to see a doctor for seasonal allergies The approach of an immunotherapy treatment plan and the two phases of a typical treatment schedule

In this episode, Daniel Searing, MD, Professor of pediatrics and allergies at Children's Colorado, talks about seasonal allergies and pollen. He discusses the effects of pollen, how to treat and alleviate allergies, and more. In this episode, Dr. Searing discusses: Pollen and how it affects allergies Why cottonwood trees are a big pollinator, especially in the springtime Why rain and humidity shut down pollen levels Why Colorado's climate makes people more susceptible to allergies How allergy symptoms will vary from year to year The importance of monitoring the quantitative level of pollen in the environment How physicians should manage the initial approach to a child with allergy symptoms Key features to look out for Why treating pollen allergies with persistent treatment is more effective What role the prescription drug Montelukast plays in treating allergic rhinitis What you can do to help prevent pollen from spreading Which medicines and therapies can help alleviate allergies When to see a doctor for seasonal allergies The approach of an immunotherapy treatment plan and the two phases of a typical treatment schedule

The post Montelukast (Singulair) Nursing Pharmacology Considerations appeared first on NURSING.com.

Erstes Ziel der vorliegenden Arbeit war eine Validierung dieses zweikammerganzkörperplethysmographischen Tiermodells durch Kontrollexperimente mit bereits etablierten Asthmamitteln durchzuführen und zu prüfen, ob und in welchem Maße Ergebnisse des Meerschweinchenmodells auf die Anwendung am Menschen übertragbar waren. Im Einzelnen waren die Bedingungen der Sensibilisierung der Versuchstiere gegen Hühnereiweiß (Ovalbumin), die optimalen Allergendosen, effektivere Sensibilisierungsmethoden, Art und Dauer der Allergen empfindlichen Phase, eine mögliche Re-Sensibilisierung oder Tachyphylaxie Effekte bei wiederholter Allergenexposition, eine evtl. Saisonabhängigkeit der Sensibilisierung bzw. der allergischen Reaktion bei Meerschweinchen und andere Möglichkeiten z. B. mit Histamin, eine bronchiale Hyperreagibilität bei Meerschweinchen zu provozieren, zu prüfen. Als nächstes war die neue Untersuchungsmethode an bekannten Asthmamitteln zu validieren, was mit den Bronchodilatatoren Fenoterol und Theophyllin sowie den Entzündungshemmern Budesonid, Methylprednisolon – Glukokortikoide - und Montelukast, einem Leukotrien-Antagonisten, geschah. Schließlich musste geprüft werden, ob sich die Methode zum Screenen von Pflanzenextrakten bei der Suche nach neuen antiasthmatischen Arzneistoffen eignete. Hierzu wurden Extrakte aus Picrorhiza kurroa und Acetosyringenin (ein Acetophenon, das chemisch strukturverwandt zum Pflanzeninhaltstoff Androsin ist und laut frühere Untersuchungen ausgeprägte antiasthmatische Wirkung besitzt) und 3 Drogen aus der traditionellen iranischen und südamerikanischen Volksmedizin (Angurate, Caiophora sepiara und Wascha aus Dorema ammoniacum) getestet. Die vorgelegten Untersuchungsergebnisse belegen, dass das plethysmographische Zweikammer- Tiermodell in der jetzt vorliegenden von uns validierten und standardisierten Methode an Ovalbumin-sensibilisierten Meerschweinchen geeignet ist, nicht nur die antiasthmatische Wirksamkeit von synthetischen Arzneistoffen zu bestätigen bzw. zu überprüfen, sondern auch Pflanzenextrakte und daraus isolierte Wirkstoffe auf ihr mögliches antiasthmatisches Wirkpotential hin zu untersuchen. Die antiasthmatische Wirksamkeit untersuchter bekannter in der Humanmedizin eingesetzter Antiasthmatika korrelierte eindeutig mit den Ergebnissen in unseren Tiermodellen. Die Methode ist sowohl für die Suche nach neuen Wirkstoffen als auch für die Wirkkontrolle in Industriebetrieben geeignet.