Unleashing the Potential of Structural Biology with AI | Raphael Townshend, Atomic AI

In this episode, we delve into the fascinating world of AI-driven drug discovery and its potential to revolutionize the field of structural biology. Our guest, Raphael Townshend, the founder of Atomic AI, shares his journey from engineering to AI and his profound interest in the structural biology space. Raphael discusses his background in engineering and how his focus on AI, particularly computer vision, led him to pursue a Ph.D. in AI with a keen interest in structural biology. He explains how he discovered the relatively unexplored area of structural biology and recognized its potential for AI algorithms to make a significant impact. The conversation takes a deeper dive into the potential impacts of AI on drug discovery, with a particular focus on its application in finding cures for diseases with no known remedy, including Alzheimer's, Parkinson's, various cancers, and infectious diseases. Raphael explains how AI has already demonstrated remarkable success in folding molecules, an achievement that once required extensive time and resources. By leveraging AI algorithms, researchers can now significantly reduce the time and cost involved in the drug discovery process. Discover how AI algorithms are reshaping the landscape of drug discovery and paving the way for more efficient and cost-effective treatments. Tune in to this episode to explore the future possibilities of AI in structural biology and its potential to transform healthcare and improve countless lives. If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development. Founder Bio: Raphael Townshend is the Founder and Chief Executive Officer at Atomic AI, a biotechnology company using artificial intelligence to enable the next generation of RNA drug discovery. Prior to founding Atomic AI, Raphael studied for his Ph.D. at Stanford University, where he wrote his thesis on Geometric Learning of Biomolecular Structure and taught in Stanford’s machine learning and computational biology programs. He has been recognized in Forbes 30 Under 30, and his work has been featured on the cover of Science, recognized by the Best Paper award at NeurIPS, and published in other top venues such as Nature, Cell, and ICLR. During his Ph.D. program, Raphael also held positions at DeepMind and Google on their artificial intelligence and software engineering teams and founded the inaugural workshop on machine learning and structural biology. Time Stamps:   02:53 Raphael’s background and professional journey in AI 05:36 What are structural biology and the rational design of molecules 08:02 Impact of AI on drug discovery and medical research 09:18 Molecule design for undruggable diseases with AI-guided drug discovery 13:39 Designing RNA molecules for disease treatment using ai algorithms 15:30 Collecting data for AI model training 17:44 Exploring data generation for AI-powered RNA analysis 18:56 Complementing biological and AI scientists for AI model training 20:44 Predicting 3-dimensional protein shapes using machine learning 22:58 Exploring the Pharmaceutical and biotech industry 25:53 Structuring deals for startups in the biotech industry 27:55 Building a biotech company: found raising journey 30:49 Techbio investing and business modeling 34:06 Benefits of partnering models in Biotech and AI product usability 37:53 Progress in RNA drug discovery and AI-powered research 39:04 How to get in contact with the Atomic AI team   Resources: Company website: https://atomic.ai/ Twitter: https://twitter.com/AtomicAICo LinkedIn: https://www.linkedin.com/company/atomic-ai-rna/