InSilicoTrials’ Post

Apheris is at the Drug Discovery Innovation Forum this week 🔗 link to the event: https://lnkd.in/eYPBiuni 📆 When? 4th & 5th September 2024 👉 Where? Hotel Palace Berlin (in person event) Ellie Dobson, VP of Product Apheris, will be giving a talk on “Securely connecting life science data for collaborative AI”. Looking forward to connecting with experts in the drug discovery field. There are many great speakers and presentations - here are some that I am particularly looking forward to: * José Duca, Global Head of Computer-Aided Drug Discovery at Novartis, discussing AI in drug discovery (best practices, hype and myths etc.) * Petrina Kamya, Ph.D., Global Head of AI Platforms, VP Insilico Medicine, sharing real-world examples of how AI is being leveraged in pre-clinical drug discovery and development * Richard Bickerton, Chief Systems Scientist, Exscientia, presenting on patient-first AI drug discovery * Uli Schmitz, Senior Director, Structural Chemistry Gilead Sciences, speaking on practical AI in small molecule drug discovery. Much looking forward to insightful discussions. #DrugDiscovery #LifeSciences #AI #DDIF

Check out Kennedy Schaal 's fascinating talk about the innovative work happening at Rejuve.Bio They are making waves in longevity therapeutics by focusing on:  ✔️Building a biomedical research platform ✔️Creating science-backed longevity therapeutics ✔️Collaborating with pharmaceutical companies for drug discovery AI's Role: By integrating AI, long-lived animal models, and crowdsourced human data, Rejuve Bio is paving the way for groundbreaking solutions in healthspan optimization. Addressing Bias: Kennedy emphasizes the importance of democratizing biomedical research and ensuring diverse data representation to improve healthcare outcomes for everyone. Looking Ahead: With hopes for significant breakthroughs in longevity research within the next year, Kennedy's work is set to make a real impact on preventative medicine. Interested in learning more? Check out the full talk here: https://lnkd.in/d6GhY-GK #Longevity #HealthTech #RejuveBio #Innovation #PreventativeMedicine #AI #Biotech #LSD2024

⭐ Monday's Speaker Spotlight ⭐ Yang-Ming Zhu, SVP, Head of Engineering at Superluminal Medicines Inc., will be sharing cutting-edge work using AI to unlock new therapeutic possibilities for G protein-coupled receptors (GPCRs) at this year's AI Driven Drug Discovery Summit (November 12-14, Boston). Session Focus: 🔍 ADME/Tox predictive models: Leveraging these models early and often to assess compound risks and liabilities. 🔍 Predictive docking: How this approach is transforming virtual screening by boosting throughput. 🔍 Generative AI: Integration in screening, hit expansion, and lead optimization. 📢 Latest News: Superluminal Medicines Inc. recently secured a $120M Series A led by Eli Lilly, aiming to advance six GPCR-focused drug programs. Their platform combines machine learning, chemistry, and generative biology to quickly develop new therapies, pushing boundaries in drug discovery. Join us to connect with leading innovators and thought leaders in AI-driven drug discovery this November! Book before THIS Friday for your LAST CHANCE to save: https://lnkd.in/eMxB9_EB #AIDDD #aidrivendrugdiscovery #aidrugdiscovery

Are you ready to revolutionize drug discovery? The agenda has now been released for the 𝟯𝗿𝗱 𝗔𝗻𝗻𝘂𝗮𝗹 𝗔𝗜 𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗿𝘂𝗴 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗦𝘂𝗺𝗺𝗶𝘁 taking place on November 11-13, in Boston. 🤝 Connect with over 300 industry leaders 🔎 Explore specialized content in biology and chemistry tailored to your research 🔬 Discover groundbreaking innovations in our Innovation Hub and Tech Test Lab 📈 Learn about the latest AI advancements, including next-gen machine learning models and data analytics. Take a look at our top sessions and diverse speaker faculty features experts from Sanofi, GSK, Bristol Myers Squibb, Recursion, Insilico Medicine, Novartis and Novo Nordisk. This summit is your platform to showcase innovations, connect with industry trailblazers and gain insights into effective AI integration strategies, helping you optimize drug design, personalize treatments, and stay at the forefront of AI-driven drug discovery. Download the agenda now - https://hubs.ly/Q02zSfXg0 #AIDDD #AIDrivenDrugDiscovery #DrugDiscovery #AI

🤔 How successful are AI-discovered drugs in clinical trials? My colleagues from Boston Consulting Group (BCG) tackle this important question in a recent paper published in Drug Discovery Today. In this first of a kind analysis, the authors show that Ph1 success rates reach ~90% for AI discovered drugs with Ph2 closer to historical averages at ~40% (albeit with a smaller sample size). It remains early days, but these results suggest that AI could significantly ease challenges creating drug-like molecules, with more to be done in cracking the fundamental biology. They write: "Ultimately, the promise of AI in drug discovery is to bring more innovative medicines to patients faster, better and cheaper. We have already started seeing the speed and cost impacts in preclinical workflows from these techniques. Our findings show that benefits are beginning to manifest in clinical trials as well." 🚀 Exciting times ahead for the field - to be continued! Check out the full article here: https://lnkd.in/eZpVqwup #AIdrugdiscovery #Clinicaltrials

Some takeaways from last month's AI-Driven Drug Discovery Summit (Kisaco Research). Machine learning systems are being incorporated in early-stage discovery through clinical phases, aiding in selection of optimal targets and indications, optimizing trial recruitment to minimize risk, and generating clinical summaries in preparation for regulatory engagement. Pharmas find that drug programs leveraging genetic evidence have lower risk. AI/ML systems built upon massive GWAS data sets are helping explore causality of distal variant targets—often located within enhancer regions or even across chromosomes. Some design ML tools to analyze SNP signatures for potential off-target effect predictions. Others are employing AI for pipeline prioritization after acquisitions. The quality of input data was echoed often in the presentations. Despite challenges in eliminating bias—found even in EHR data—cleaner datasets significantly enhance the accuracy of AI/ML predictions. #artificialintelligence #datascience #aiml #causality #distalvariant #patientstratification #clinicalrisk #dataquality #machinelearning The next AI Driven Drug Discovery Summit will be Nov 2024 (Boston)

We’re thrilled to announce Enchant, our state-of-the-art multi-modal transformer for drug discovery. Massive congratulations to the team at Iambic Therapeutics who created this technology. And thanks to technology partners who enabled it: Amazon Web Services (AWS) where all of our data infrastructure lives, NVIDIA for long collaboration on #AI technologies for #drugdiscovery, and Lambda for providing robust compute capacity for training models at scale. There’s plenty to read about what Enchant is and what it achieves. But to highlight one facet: we demonstrate that Enchant exhibits emergent performance on clinical tasks that improves through training on more preclinical laboratory data. https://lnkd.in/erJfTsU7

The synergy between technological innovation and regulatory advancement. At the 15th Annual Drug Discovery Innovation Forum in Berlin Sept. 4-5, Karen Sayal - MD PhD consultant clinical oncologist and industry-first scientist in AI-driven Clinical Translation and Clinical Development at Recursion - will give a talk on the synergistic advancement of AI-enabled drug discovery and regulation. She'll discuss: ◾ How industrialising drug development is unveiling hidden biological complexities to propel a paradigm shift in treating human disease. ◾ How technology-driven discovery is synergistic to the needs of our evolving next-generation regulatory ecosystem. ◾ And how we can achieve seamless interoperability between the needs of developing and deploying AI technologies and the needs of regulation through pragmatic bipartisan dialogue and coordinated evolution. Learn more & register: https://lnkd.in/d8EFpTuh #ai #ddif #ddif2024 #drugdiscovery #innovation #tech #techbio #regulation

Quality content. Flexible data models. Power your LLM with the content you already trust. Elsevier journals. The overall innovation picture for you and Elsevier? see Mirit’s post below! 💡

In his article for Pharma Bio World (PBW), Dr. Somesh Sharma- Executive Vice President and Head Discovery Services, Aragen Life Sciences, discusses how AI, machine learning, and deep learning are revolutionizing drug discovery by accelerating key processes like de novo drug design, virtual screening, and drug optimization, thereby unlocking vast new possibilities for developing novel treatments. He highlights groundbreaking examples of AI-designed drug candidates already advancing to clinical trials, emphasizing the growing role of AI in expediting the delivery of innovative therapies. However, Dr. Sharma also addresses critical challenges, including the need for high-quality data, ethical considerations, and the importance of strong industry collaborations, concluding that the future of AI in pharma is incredibly promising, offering the potential for personalized treatments and improved healthcare outcomes. Click here https://lnkd.in/gbM6t3qD to read the full article and explore the full impact of AI on drug discovery and the future of healthcare. #ai #ml #drugdiscovery #healthcare #moderndrugs #aiinpharma #cdmo #cro #noveltreatments #article #clinicaltrails #drugoptimization