Data in Biotech

• How AI Can Increase Clinical Trial Efficiency with Patrick Leung from Faro Health

  How can AI improve clinical trials and accelerate drug development?  In this episode of Data in Biotech, Ross Katz sits down with Patrick Leung, CTO of Faro Health, to explore how AI-driven tools are reshaping clinical trial design. Patrick shares insights into document generation, patient burden analysis, and AI governance in biotech.  Learn how Faro Health is developing clinical protocols and leveraging AI to optimize trial success while ensuring regulatory compliance. Whether you're in biotech or healthcare, this conversation offers valuable takeaways on the future of AI in increasing clinical trial efficiency.  What You'll Learn in This Episode: How AI is used to generate clinical trial protocols and reduce inefficiencies.The role of AI in assessing patient burden and optimizing trial designs.How data model development enables specialized biomedical AI workflows.How large language models (LLMs) support clinical trial automation.Future trends in AI-driven clinical trial optimization. Links: Find out more about Faro Health: https://www.farohealth.comConnect with Ross Katz on LinkedIn: https://www.linkedin.com/in/b-ross-katz/ Connect with Patrick Leung on LinkedIn: https://www.linkedin.com/in/puiwah/ Meet Our Guest: Patrick Leung is the Chief Technology Officer at Faro Health, where he leads AI-driven innovations in clinical trial design. With a background in data science and software engineering from companies like Google and Two Sigma, Patrick brings a fresh perspective to life sciences, focusing on optimizing clinical trials through AI and structured data models. About the Host: Ross Katz is the Principal and Data Science Lead at CorrDyn, specializing in applying data science to biotech and healthcare. As the host of Data in Biotech, Ross explores the latest trends and innovations shaping the industry. Enjoying the Show? Visit Faro Health to learn more about AI-driven clinical trial optimization. Don’t forget to rate and review Data in Biotech on Apple Podcasts! Sponsored by CorrDyn This episode is brought to you by CorrDyn, a leader in data-driven solutions for biotech and healthcare. Learn more at CorrDyn.

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• Organoids and Active Learning for Chronic Disease with Naren Tallapragada

  In this episode of Data In Biotech, Ross Katz interviews Naren Tallapragada, CEO and Co-founder of Tessel Bio, about his background in electrical engineering and physics and how personal circumstances led to him pivoting his focus to enter biotech and start Tessel Bio. Naren breaks down Tessel Bio’s unique approach to drug discovery, which involves "reverse engineering" chronic diseases. Instead of starting with a potential drug and testing its effects, they begin with a clear picture of the disease itself—specifically, how it appears and behaves in the body. A key part of their method is using human organoids—tiny, lab-grown versions of human tissues—to closely replicate real diseases and see how different treatments interact with them. This “small data” approach is made substantially more efficient with the addition of active learning. Join us for a fascinating conversation about Tessel Bio’s approach to finding cures for chronic diseases that impact hundreds of thousands of people every day.  ​​What You'll Learn in This Episode: Naren’s journey into biotech and personal motivationUnderstanding Tessel Bio's approach to drug discoveryThe role of organoids in disease modelingData gathering and target identification strategiesActive learning in drug discovery at Tessel Bio Connect with Our Guest: Sponsor: CorrDyn, a data consultancyFind out more about Tessel Bio Connect with Naren on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science.Subscribe and leave a review if you enjoyed this episode!

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• How Alex Junge from amass is Speeding Up Scientific Breakthroughs with AI

  In this episode of the Data and Biotech Podcast, host Ross Katz sits down with Alexander Junge, Co-Founder and CTO of amass, to break down how AI is reshaping scientific research in life sciences.  Alex walks us through how his platform is creating professional tools for researchers, biotech companies, and venture firms to navigate the (rapidly!) growing breadth and depth of scientific knowledge by leveraging artificial intelligence - and what this will look like in the future.  Alex also shares insights into his company’s work with Nordic Bio Ventures and how amass delivers reliability and builds trust in its platform. ​​What You'll Learn in This Episode: What challenges researchers face in formulating questions and retrieving relevant answers from the breadth of scientific knowledge.The importance of design and user experience in life sciences, and how the company adopts a rigorous approach to information retrieval. How amass helps life sciences professionals navigate complex scientific domains by building trust in answers generated by AI. A real-world case study of how amass is assisting Nordic BioVentures a venture firm to build a biotech company.Alex’s predictions for AI's impact on scientific discovery over the next decade. Connect with Our Guest: Sponsor: CorrDyn, a data consultancyFind out more about amassConnect with Alex on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science.Subscribe and leave a review if you enjoyed this episode!

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• Advancing Therapeutic Design in Gene and Cell Therapy with Dipen Sangurdekar

  In this episode of Data in Biotech, Ross sits down with Dipen Sangurdekar, VP of Data Sciences at KSQ Therapeutics, to discuss the role of data-driven approaches in therapeutic design and development. The conversation explores the intersection of computational biology, machine learning, and bioinformatics in advancing personalized medicine and improving patient outcomes. Dipen shares his journey in the industry, emphasizing the importance of integrating data science with biological research and the challenges associated with working in the rapidly evolving field of cell therapies. From hypothesis-driven research to leveraging multimodal data for actionable insights, this episode explores the nuances of using statistical methods and AI to enhance drug development. Key Takeaways: Successful data science in therapeutics requires a deep understanding of both statistical methods and biological processes.High-dimensional but low-sample-size data demands a guided hypothesis-driven approach to avoid false positives.Data integration and collaboration between computational and biological teams are critical for generating meaningful insights.Emerging AI and machine learning tools are enhancing productivity but must be carefully applied in therapeutic research.Picking a problem you’re passionate about and going deep into it is crucial for long-term success in the field. Connect with Our Guest: Sponsor: CorrDyn, a data consultancyFind out more about KSQ Therapeutics Connect with Dipen on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science.Subscribe and leave a review if you enjoyed this episode!

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• Democratizing Therapeutic Discovery for Neglected Diseases using AI with Timothy Jenkins of DTU Bioengineering

  This week on Data in Biotech, we welcome Timothy Jenkins, the Head of Data Science and Associate Professor at DTU Bioengineering, a leading scientific community dedicated to advancing areas of biotechnology, food technology, and health through innovative teaching and research.  Timothy starts the conversation by walking us through his background and early career beginnings, from the first time he expressed interest in zoology and venomous snakes to now leading a research group focused on AI-guided drug discovery for snake antivenom. He and our host, Ross Katz, dive into one of DTU’s most exciting recent publications about "de novo" designed proteins to neutralize lethal snake venom toxins.  Inspired by Nobel Prize winner David Baker’s groundbreaking paper and in collaboration with the Baker Lab on computational design methodology, this project holds great promise in therapeutic discovery and drug development. Tim explains how computational protein design and protein structure prediction are revolutionizing his field, highlighting compelling examples and milestones from his research on antivenom. He also provides an overview of the process used to discover new antivenoms, including the sourcing of biological data, model training, and integration of experimental feedback. Finally, we get Tim’s perspective on the future of AI-powered therapeutic discovery, and his take on the integration of quantum computing into protein design. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Useful Links Nature - De novo designed proteins neutralize lethal snake venom toxins Timothy’s LinkedIn DTU Bioengineering Website UW Institute for Protein Design “de novo” designed proteins project Information on Nobel Prize winner David Baker

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