Life Sciences Updates’ Post

AI has the potential to really help in #DrugDiscovery. Lower costs to develop and access medicines. More equitable access. Brand new lines of discovery. But, no matter what folks tell you, it isn't there yet. We are going to need many iterations of the lifecycle from experiment, to data, to training an AI, to prediction, to experimental test of that prediction, to more data... before we get there. What's more, we need to invite everyone to collaborate to make sure that cycle is virtuous. THAT is what CACHE is all about. With the results of CACHE Challenge 1 announced below, we're just getting started.

The final results of the first international CACHE challenge on virtual screening have just been released! We are happy to be among the winners with a unique computer vision method to compare protein cavities and identify seed fragments, then link them by deep learning to fully enumerate hits. Many thanks to my students Merveille Eguida and François SINDT for this beautiful achievement. CACHE #1, run in partnership with the Structural Genomics Consortium and funded by the Michael J. Fox Foundation, was an open science challenge where participants used computational models to predict new molecules for drug discovery and resulted in the identification of seven promising “hits” for familial Parkinson’s disease. For more details on the technology, take a look at Eguida, M. and Rognan, D. (2020) A computer vision approach to align and compare protein cavities: Application to fragment-based drug design. J. Med. Chem., 63, 7127-7142 doi: 10.1021/acs.jmedchem.0c00422   Eguida M, Rognan D. (2021) Unexpected similarity between HIV-1 reverse transcriptase and tumor necrosis factor binding sites revealed by computer vision. J. Cheminform., 13, 90 doi: 10.1186/s13321-021-00567-3.   Eguida, M., Schmitt, C., Hibert, M., Villa, P. and Rognan, D. (2022) Target-Focused Library Design by Pocket-Applied Computer Vision and Fragment Deep Generative Linking. J. Med. Chem., 65, 13771-13783 doi: 10.1021/acs.jmedchem.2c00931 #drugdiscovery #artificialintelligence #computationalchemistry

The pharmaceutical industry is continuing to face high research and development (R&D) costs and low overall success rates of clinical compounds during drug development. There is an increasing demand for development and validation of healthy or disease-relevant and physiological human cellular models that can be implemented in early-stage discovery, thereby shifting attrition of future therapeutics to a point in discovery at which the costs are significantly lower. There needs to be a paradigm shift in the early drug discovery phase (which is lengthy and costly), away from simplistic cellular models that show an inability to effectively and efficiently reproduce healthy or human disease-relevant states to steer target and compound selection for safety, pharmacology, and efficacy questions. This perspective article covers the various stages of early drug discovery from target identification (ID) and validation to the hit/lead discovery phase, lead optimization, and preclinical safety. We outline key aspects that should be considered when developing, qualifying, and implementing complex in vitro models (CIVMs) during these phases, because criteria such as cell types (e.g., cell lines, primary cells, stem cells, and tissue), platform (e.g., spheroids, scaffolds or hydrogels, organoids, microphysiological systems, and bioprinting), throughput, automation, and single and multiplexing endpoints will vary. The article emphasizes the need to adequately qualify these CIVMs such that they are suitable for various applications (e.g., context of use) of drug discovery and translational research. The article ends looking to the future, in which there is an increase in combining computational modeling, artificial intelligence and machine learning (AI/ML), and CIVMs. Ekert JE, Deakyne J, Pribul-Allen P, Terry R, Schofield C, Jeong CG, Storey J, Mohamet L, Francis J, Naidoo A, Amador A, Klein JL, Rowan W. Recommended Guidelines for Developing, Qualifying, and Implementing Complex In Vitro Models (CIVMs) for Drug Discovery. SLAS Discov. 2020 Dec;25(10):1174-1190. doi: 10.1177/2472555220923332. Epub 2020 Jun 4. PMID: 32495689. #Gesundheit #Bildung #Fuehrung #Coaching #Mindset #Motivation #Gehirn #Neuroscience #Psychologie #Persoenlichkeitsentwicklung #Kindheit #KeyNoteSpeaker #Humangenetik #Biochemie #Neuroleadership #Ernaehrung #Transformation #Stress #Demografie #Gender #Age #ArtificialIntelligence #Epigenetik #Veraenderung #Organoidintelligence #Change #Gesellschaft #Organisationsentwicklung

NEWS RELEASE: Conscience announces first results in open challenge to predict “hits” for Parkinson’s disease drugs We are extremely excited to announce today that the results of CACHE Challenge #1 are out! CACHE #1, run in partnership with the The Structural Genomics Consortium (SGC) and funded by the The Michael J. Fox Foundation for Parkinson's Research, was an open science challenge where participants used computational models to predict new molecules for drug discovery and resulted in the identification of seven promising “hits” for familial Parkinson’s disease. By using a challenge model that compares and lab tests dozens of computational methods against the same target protein, checks those predictions against reality, and then shares the results openly with the world, CACHE Challenges provide a consistent benchmark and shed much needed light on the most effective AI-powered, hit-finding algorithms. Along with the announcement of the top hits, we’ve made the entire experimental dataset available to the public, including the chemical structures of all the molecules tested, details of the experiments used to test them, and summaries of the computational methods used to make predictions. The challenge has two key outcomes: - New discoveries that can help advance novel treatments for Parkinson’s disease, a degenerative condition that affects more than 1.1 million people in North America. - Prospective benchmarking of multiple computational methods from leaders in the field to learn which predictive approaches are most promising, reveal the state-of-the-art, and guide future progress. Six of the winning molecules were submitted by university laboratories and one from a pharmaceutical company. These submissions were from the laboratories of David Koes at the University of Pittsburgh; Olexander Isayev (Carnegie Mellon University) and Artem Cherkasov (University of British Columbia); Christina Schindler and Lukas Friedrich at Merck Group; Dmitri Kireev at the University of Missouri; Christoph Gorgulla at St. Jude Children's Research Hospital; Didier Rognan at the Université Strasbourg; and Pavel Polishchuk at Palacky University. Read the full release, and find links to the open data: Release (EN) https://lnkd.in/gKT69k5M Release (FR) https://lnkd.in/gVKmkkvw Open data: https://lnkd.in/ggrhtqUP Want to learn more? Join us for the First Annual CACHE Symposium on March 6 and 7, in Toronto, to hear directly from the leading researchers in the challenge: https://lnkd.in/gMJZKsDP

𝗔𝗻𝘁𝗶𝘀𝗲𝗻𝘀𝗲 𝗢𝗹𝗶𝗴𝗼𝗻𝘂𝗰𝗹𝗲𝗼𝘁𝗶𝗱𝗲𝘀 (𝗔𝗦𝗢𝘀) - 𝘁𝗵𝗲 𝗽𝗮𝘀𝘁, 𝗽𝗿𝗲𝘀𝗲𝗻𝘁 𝗮𝗻𝗱 𝗳𝘂𝘁𝘂𝗿𝗲 𝗶𝗻 𝘁𝗵𝗲𝗿𝗮𝗽𝗲𝘂𝘁𝗶𝗰𝘀! My fascination for ASOs first comes from writing a paper at the University of Nottingham, looking at the use of ASOs for treating Huntington's disease, so when I saw this article I had to share! This article is a great summary to the origin, developments and potential of ASOs (Kim Lennox). The method for ASOs was first described in the 1970s and in the last 45 years has seen significant developments. The 2010s saw several ASO-class therapeutics approved by the FDA as research advanced, with improvements in reagent design and target selection. One of the leading ASOs companies includes, Ionis Pharmaceuticals, Inc. Great advancements have been made, but more work is needed in this space. It is still great to see how the space holds significant therapeutic potential for patients and I can imagine the next few years we will continue to see some incredible advancements in the space. #geneediting #oligonucleotides #antisense #lifescience

Nashville Biosciences LLC, a wholly owned subsidiary of Vanderbilt University Medical Center, and Illumina Inc., a global leader in DNA sequencing and array-based technologies, announced an agreement with Amgen, a global biopharmaceutical company, to whole-genome sequence approximately 35,000 DNA samples. The sample cohort is primarily made up of DNA from African Americans, who are currently underrepresented in research for the clinical applications of genomics, including drug target discovery. This cohort will be the largest datasets of genomes of its kind to date. To learn more: https://lnkd.in/dWQGPS_J #Databank #Datasets #DrugDiscovery #DNA #Samples #Genomics #Clinical #VUMC #Genetics #Research #GenomicData #Biomedical #Healthcare #Funding #AI #ML #Bioinformatics #Grant NashBio

Meet Julian Northen - Solid State Manager at the R&D facility at our Silverbriar site. We sat down with Julian to chat about his role and experiences in pharma... 💊 What does your role involve? 💊 “I am responsible for managing our solid form development activities that span early lead differentiation work and preformulation through to robust screening programs and crystallisation development. Ultimately the aim is to identify clinical development candidates. I am also responsible for expanding and embellishing the service offering at Onyx, to ensure that we continue to grow our reputation within the industry and provide a challenging and interesting environment for our scientists.” 💊 How have you found working at Onyx? 💊 “Working at Onyx has been a real journey of opportunity and pure scientific interest over the years. The exposure to such a diverse array of novel chemistry, solid form challenges and emerging novel treatment areas has provided an amazing opportunity to continually challenge and develop my understanding of the industry in which we work. All of the above of course would not be possible without the people and it is fair to say that working with such an amazing group of young (and old) scientists over the years has been a fundamental part of why I continue to enjoy my role at Onyx.” 👏 With so much experience, do you have any advice for people wanting to pursue a similar career path? 👏 “My advice would be to get a good understanding of the basics in any area of science that you enjoy, challenge yourself through university or via an apprenticeship and work hard with an eye to get involved in any opportunities to gain work experience outside of a purely academic environment. It is also fair to say that the industry is huge with opportunities to diversify once you get a firm footing on your career pathway, so do not ever feel that choices made early mean that you must stick to one area of science. Even within a small company, you are exposed to multiple disciplines, so above all stay interested, work hard and challenge yourself to achieve your goals.” 👏 Which scientific breakthrough achieved in your lifetime has had the biggest impact on people’s health? 👏 “This is a difficult question, but my personal bias trends towards the huge improvements made in the field of oncology through targeted modeling for small molecule design and the advances being made with antibody and gene directed therapies that have made significant advances since the mid 90’s when I first became interested in this as a therapeutic approach. But to be fair, one of the biggest and simplest breakthroughs, if we talk purely about numbers, has been the far wider public understanding of the impact lifestyle can have upon our health.” Learn more about our amazing team: https://lnkd.in/e_rG3ukz #Chemistry #PharmaJobs #PharmaCareer #CDMO

From Secured Labs to Global Collaboration: The Evolution of Life Sciences Research 🧬 Once a closely guarded sector, life sciences is now experiencing a paradigm shift towards open-source research. 🌱 Evan Floden, CEO at Seqera Labs, discusses in the interview with Pharma Voices how this transformative approach accelerates advancements in genetic diagnostics, cell therapies, and personalized vaccines. 💉 Discover how open science is becoming the backbone of the scientific process for the coming decades. ➡️ Check the article here: https://lnkd.in/dfjgDjt5 #innovation #openscience

🔬 Reflecting on Biopharma's 2023: A Year of Contrasts and Innovations As we step into 2024, it's essential to look back at the year that was in the biopharma industry. 2023 stood out as a year of remarkable technological advancements juxtaposed against economic challenges within the sector. 🧬 One of the most intriguing developments was the inception of "organoid intelligence" (OI), led by Dr. Thomas Hartung. This new field is pioneering the use of brain organoids from human stem cells for creating biocomputers, potentially revolutionizing pharmaceutical testing and our understanding of brain functions. However, it also raises significant ethical questions, which need careful consideration. 🤖 The role of AI in drug discovery saw mixed results in 2023. Success stories like Insilico Medicine and Verge Genomics were inspiring, showcasing the power of AI in developing new drug candidates and moving them through clinical phases. On the flip side, setbacks in clinical trials for some AI-designed drugs highlighted the complexities of this approach. 💻 In clinical research, AI made more definitive strides. Big Pharma companies like Amgen and Novartis leveraged AI tools for more efficient trial processes. Interestingly, smaller companies like Lantern Pharma also made notable contributions, demonstrating the widespread impact of AI across the industry. 🧪 The year also saw significant progress in AI-driven protein design, genome editing, and the growth of RNA modalities. Particularly, CRISPR-based therapies achieved remarkable milestones, with the first clinical approval for treating blood disorders. Additionally, the evolution of chemical modalities in medicinal chemistry continued to expand the druggable universe. 🌐 While challenges remain, such as in the realm of antibody-drug conjugates and the manufacturing complexities of new drug modalities, the year has undeniably pushed the boundaries of biopharma innovation. As we reflect on these developments, it's clear that the biopharma industry is at a pivotal point. The fusion of biology, technology, and AI is not just reshaping drug discovery and development but is also redefining what's possible in healthcare. Read Andrii Buvailo's insightful editorial review of major trends in drug discovery and biotech (link in the comments). We hope you have a productive and prosperous year ahead! Happy New Year! #biopharmatrend #drugdiscovery #biotech #WhereTechMeetsBio