Generate:Biomedicines’ Post

Join Cameron Slayden as he explores the transformative impact of AI on our work and clients. From AI-driven research to generative design of drugs and biologics, learn how machine learning and generative AI are revolutionizing scientific progress. Gain insights into how these technologies function, their implications for the future, and the evolving therapeutic landscape. Don't miss this chance to understand AI's role in shaping our field! #GenerativeAI #ScientificProgress #AMI2024

𝗔𝗽𝗽𝗹𝘆𝗶𝗻𝗴 𝗚𝗲𝗻𝗔𝗜 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 𝗶𝗻 𝗗𝗿𝘂𝗴 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗮𝘁 𝗜𝗗𝗟 ▶ AI Model Employment at IDL: At IDL, we have developed in-house transformer-based (GenAI) model to handle large multi-omics datasets. These models help predict new uses for existing therapies based on their known target-genes, enabling drug repurposing pipeline's efficiency. ▶ See also the commentary of earlier work done (https://lnkd.in/ewWt8Dmk) where we introduce the concept of AI/ML using such drug connectivity mapping approaches. ▶ Implementation in Research In our research settings done by Mihai Todor and Kaz de Souza Mateus Azim ---- Bridging biotech worlds with comp bio⚡💪🏽, GenAI models help to facilitate rapid hypothesis generation and validation, significantly speeding up the drug repurposing pipeline for our biotech partners. 🤝 Reach out to us if you wish to learn more, require support for your projects and and future collaborations. Image credit: https://lnkd.in/eGaKbNsF

Generative AI is transforming the landscape of drug delivery systems, revolutionizing how we approach this critical aspect of biotechnology. As a biotech researcher, I am fascinated by how generative AI accelerates innovation by enabling the creation of sophisticated drug delivery mechanisms with unprecedented precision and efficiency. Researchers in Australia, lead by Monash University, have developed an innovative AI tool that promises to transform virtual screening processes in early-stage drug discovery, significantly boosting scientists' capacity to identify potential new medications. Read more: https://lnkd.in/gGybAX4H #Drug_delivery #generative_ai #monash_university

Creating a therapeutic antibody is a complex, time-consuming, and costly process. It involves overcoming challenges related to biophysical properties (like solubility, stability, and production yields), as well as addressing cross-reactivity and toxicity concerns. See how we're leveraging AI to transform this process: 🌐 mabsilico.com #Antibody #AI #ML #DrugDesign #DrugDiscovery #BioTech

A fantastic representation of small-Molecule Discovery for GPCRs using MD simulations 👏

The drug discovery process can be complex, but luckily generative AI is simplifying some aspects of early-stage discovery and development. "GenAI has the potential to expedite and reduce the cost of every step of the drug discovery and early-stage development process, where only 10% of candidate molecules advance to clinical trials," writes Ranu Carroll and Kevin Anderson Jr. One use case of generative AI that really stands out to me is target validation. De novo drug design, which is the generation of entirely new molecules with specified properties, can benefit from GenAI. This technology can allow professionals to better explore more chemicals and design custom compounds made to target specific diseases. What's the GenAI use case in drug development that stood out most to you? Be sure to check out the benefits in this article: https://lnkd.in/e_25w8gk #PharamaIndustry #DrugDiscovery #GenerativeAI

Machine learning in preclinical drug discovery - Nature.com: Machine learning in preclinical drug discovery  Nature.com http://dlvr.it/T9sKbP #ai #artificialintelligence

An image might be worth a thousand words, but a video can convey much more. At Acellera Therapeutics, we've created a video to simplify our complex small-molecule discovery process. Discover how our QuantumBind® platform, powered by AI and Quantum chemistry, is transforming drug discovery. Watch now and see innovation in action. For more information, visit: https://www.acellera.com. #DrugDiscovery #AI #QuantumChemistry #Innovation #Acellera

🚀 **Revolutionizing Drug Discovery with Generative AI** 🧬 The future of pharmaceuticals is here, and it's powered by #GenerativeAI! 🤖✨ By leveraging cutting-edge AI, we're transforming drug discovery into a faster, more efficient process. 🔬 **What's Changing?** Generative AI can design novel drug molecules from scratch, predict their properties, and evaluate their potential—all at lightning speed. This means less time in the lab and more time bringing life-saving treatments to market. ⏱️💊 🌟 **Why It Matters?** AI-driven models analyze vast datasets to uncover hidden patterns, enabling researchers to explore a broader chemical space and discover new drug candidates like never before. The synergy between AI and human expertise promises groundbreaking therapies developed at an unprecedented pace. 🌐💡 future of healthcare with #ai and #innovation! 🌍💼 #drugdiscovery #bioinformatics #cadd #bigdata #generativeai #deeplearning #molecularmodeling #structurebiology #alphafold3 #healthcarerevolution #biotech #pharma #techInnovation #futureofmedicine

#AIfordrugdiscovery On March 8, Insilico Medicine claimed to have created the first “true AI drug” that’s advanced to a phase II clinical trial. The company R&D team published a paper in Nature Biotechnology describing a candidate drug for a lung disease, idiopathic pulmonary fibrosis. I would invite you to dig in because it s a game changer. 🧐 Not only AI software suggested a possible target (a protein called "TNIK"). But they tagged several chemicals that could interfere with it, one of which was then tested in cells, animals, and ultimately in humans in initial safety tests. It s unique to get such a comprehensive demonstration of how to develop a drug candidate using AI. "From soup to nuts" as the MIT Technology Review rightly comments. MIT reports 2 other company endeavors in that domain : ✅ Recursion Pharmaceuticals and ✅ Isomorphic Labs (a spin-out of Google’s DeepMind). Worth reading : 👉 Nature paper : https://lnkd.in/eTTr4cgW 👉 MIT report : https://lnkd.in/eicjXYXP Barnabé Lecouteux Igal Slama Thorsten Alexander Rall Moïse Tignon Salah AZIZI