Research and Economic Development | University at Buffalo’s Post

Is this the beginning of a rAIvolution in Drug Development? I just read a thought-provoking paper on arXiv that suggests it might be. Charlotte Bunne’s "How to Build the Virtual Cell with Artificial Intelligence" is a collaborative effort including an impressive team: • Theofanis Karaletsos (Chan Zuckerberg Initiative - CZI) • Aviv Regev (Genentech / read her interview with Andrew Dunn https://lnkd.in/ebgR2wGV) • Emma Lundberg (Stanford University, KTH Royal Institute of Technology, CZI) • Jure Leskovec (Stanford University, CZI) • Stephen Quake (Stanford University, CZI) The author list includes researchers from Harvard University, University of California, Berkeley and many other institutions too, reflecting a truly broad collaboration. They're proposing AI-powered virtual cells (AIVC) that could fundamentally change how we model cellular behavior and develop new drugs. The idea of running thousands of in silico experiments without touching a pipette is fascinating. The paper outlines a roadmap for creating these AIVC, addressing challenges in data integration, model architecture, and biological fidelity. It emphasizes the need for universal representations across molecular, cellular, and tissue scales. The paper calls for cross-sector collaboration. It's not just a technical challenge, but a push for a new way of working together in our field. So where do we go from here? The authors suggest prioritizing data generation, developing evaluation frameworks, and fostering open collaboration. It's an ambitious vision that will require sustained effort from the entire biomedical community. I’m curious to hear others' thoughts. How might tools like this impact our work? What challenges do you foresee in making this vision a reality? Read the paper here: https://lnkd.in/eDa_b6Kd What's your take on this potential rAIvolution in biotech? #AI #Biotech #DrugDevelopmemt #Innovatiom #rAIvolution #AugmentedBiology Illustration EMxMJ

Come join Dror Hilman and Daniel Koster from Code Ocean and myself from team #VPE at BioMed X Institute in partnership with Sanofi for a fire side chat where we will discuss progress towards building #AI Agents for Pharma R&D (#AI4Pharma).   𝐏𝐨𝐢𝐧𝐭𝐬 𝐰𝐞 𝐰𝐢𝐥𝐥 𝐜𝐨𝐯𝐞𝐫 👉 How can AI Agentic workflows improve Pharma R&D? 👉 Demo of AI Agents for Pharma. 👉 What are the next steps to making AI Agents pharma ready?   📍Register here https://lnkd.in/eNdA7-By.  #GenerativeAI #ComputationalBiology #DataScience #MachineLearning #VirtualPatients #DigitalTwins #DrugDiscovery #DrugDevelopment

🌐 Cerebras - Transforming Industries with Cutting-Edge AI Computation Cerebras Systems’ groundbreaking technology is now driving progress across multiple industries, offering remarkable computational speed and efficiency. 🚀 🔍 Key Cerebras Applications: 1. Pharmaceuticals: AstraZeneca has integrated Cerebras’ system to accelerate drug development, leveraging AI-driven data analysis to contribute to advancements in innovative healthcare. 2. Energy: TotalEnergies is using the Cerebras CS-2 to perform computations over 200 times faster than traditional GPUs, utilizing AI insights to enhance energy efficiency. 3. Government and Research Institutions: The U.S. Department of Defense and Argonne National Laboratory also leverage Cerebras technology, playing a crucial role in cancer treatment research and cutting-edge scientific studies. These use cases demonstrate how Cerebras technology is driving AI innovation across diverse fields and delivering tremendous value across industries. Keep an eye on Cerebras as it unlocks the potential of the future! #Cerebras #AI #MachineLearning #DeepLearning #Innovation #ArtificialIntelligence #IndustryRevolution

Important news at PGxAI.

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

We’ve compiled everything related to how our AI cloud benefits life sciences and healthcare on a single page: https://lnkd.in/dVF_Z7Gj Here are some of the domains where Nebius can be particularly useful: - Life sciences and drug discovery With accelerated computing, researchers can virtually model millions of molecules and screen hundreds of potential drugs simultaneously, reducing costs and speeding time-to-solution. - Genomics and multi-omics Using HPC to accelerate genome analysis in population and cancer genomic studies can help identify rare diseases and bring tailored therapeutics to market faster, advancing the journey to precision medicine. - HealthTech AI-powered tools can be an extra set of “eyes,” helping to quickly read images, calculate measurements, monitor changes and identify urgent findings to optimize workflows and enhance patient care. See which companies and laboratories are already using Nebius for various tasks, read customer testimonials, connect with our expert Ilya Burkov and discover additional details: https://lnkd.in/dmbFEqqJ #lifesciences #healthtech #biotech #drugdiscovery

🌟 AI in Drug Discovery: Shaping the Future of Healthcare! 💊 Artificial Intelligence is transforming drug discovery at an unprecedented pace, and the impact is evident in several key areas: 📚 Publications: We've seen a 134% increase in AI-related research papers in biology, with most of these being published in high-impact journals. 💡 Patents: There's been a 17% rise in AI-driven drug discovery patents, focusing on three crucial areas—understanding diseases, target discovery, and molecule optimization. 💰 Funding: The flow of funding is significant, especially in countries with robust economies, emphasizing commercial viability. 🔭 Future Potential: Despite these advances, we've only scratched the surface. The potential of AI in drug discovery is vast, with novel approaches yet to be fully explored. The future of drug discovery is bright, and AI is at the heart of this innovation. Stay ahead in this rapidly evolving field by staying informed and engaged. #AIinDrugDiscovery #Biotech #AI #MachineLearning #DrugDiscovery #Innovation #FutureOfHealthcare #Patents #Research #Funding

Join Douglas McCloskey from BioMed X Institute and Dror Hilman and Daniel Koster from Code Ocean for a fireside chat on December 17th, 2024, at 12 pm EST / 9 am PT, as we delve into the transformative role of AI agents in pharmaceutical research and development. Event Highlights: • Understanding AI’s Impact: Explore how AI agents can streamline drug discovery and development, addressing critical bottlenecks in Pharma R&D. • Expert Insights: Gain perspectives from industry leaders on the challenges and opportunities presented by AI integration in pharmaceutical research. • Innovative AI Agents: Discover three pioneering AI agents developed to enhance Pharma R&D: • Talk2Biomodels: Facilitates communication with PK/PD/QSP models. • Talk2Cells: Enables interaction with single-cell sequencing data. • Talk2KnowledgeGraphs: Connects with biomedical knowledge graphs. • Live Demonstrations: Witness these AI agents in action and understand the technology that powers them. • Future Outlook: Engage in discussions about the current capabilities, limitations, and the roadmap for making these AI agents industry-ready. Don’t miss this opportunity to explore the future of AI in Pharma R&D. Register here: https://lnkd.in/dHM7Y93W #GenerativeAI #ComputationalBiology #DataScience #MachineLearning #VirtualPatients #DigitalTwins #DrugDiscovery #DrugDevelopment

How can Machine Learning (ML) increase the production of medicine? 💊 And how far is the pharma industry with adopting Industry 4.0 technologies such as ML? Watch the video below 📹 - and learn about the answers in this article: https://lnkd.in/dPa_mb7R In the video, MADE PhD from DTU - Technical University of Denmark Breno Renato Strüssmann Junior tells about his research on applying ML and other I4.O technologies at FUJIFILM Diosynth Biotechnologies, Hillerød. The research is part of the MADE FAST research platform including more than 50 company partners, universities and RTOs. The largerst investment in the platform comes from Innovationsfonden. Partners in the research project: DTU, FORCE Technology and FUJIFILM Diosynth Biotechnologies. #Industry4 #MachineLearning #DKpharma #Hillerød #dkproduktion