Impact AI Discovering Protein Drug Candidates with Hanadie Yousef from Juvena Therapeutics
How can advancements in biotechnology and machine learning lead to revolutionary treatments for age-related diseases? In this episode, I speak with Hanadie Yousef, CEO and Co-Founder of Juvena Therapeutics, to discuss her work on protein-based therapeutics. Hanadie, a neurobiologist specializing in aging and tissue degeneration, has pioneered research at Juvena to identify regenerative proteins that can restore tissue function and combat chronic diseases.
In our conversation, Hanadie details Juvena’s AI-driven platform that identifies, validates, and engineers protein candidates with therapeutic potential. We explore the power of machine learning models in drug discovery, the challenges of working with multi-omics data, and the potential for new treatments to revolutionize healthcare by targeting disease at the molecular level. Join us to hear how Juvena Therapeutics is setting a new standard in precision medicine aimed at helping individuals age with vitality.
Key Points:
- The founding story of Juvena Therapeutics and its mission to restore tissue health.
- How the company leverages AI to identify regenerative proteins from stem cell secretions.
- Learn how Juvena's machine learning models enable targeted protein engineering.
- Explore the different types of data that Juvena utilizes and how they are structured.
- Hear about the benefits of in-house data generation for model training and validation.
- Discover the challenges of generating sufficient data for accurate model predictions.
- Technological advancements in proteomics and multi-omics that support its platform.
- Hanadie shares advice for AI-driven startups and her hopes for Juvena's future impact.
Quotes:
“Juvena is part of really, a new approach to leveraging the biology of aging and underlying mechanisms associated with why our tissues decline in function, in order to target this biology so that we can treat a broad swath of diseases.” — Hanadie Yousef
“That's ultimately the goal of Juvena, to really enable people to age with dignity, to continue to contribute to society, and to really maintain their health until the very end.” — Hanadie Yousef
“Ultimately, [machine learning is] leveraged at every stage of the process from in silico prediction, and screening through to the actual engineering and drug development.” — Hanadie Yousef
“When it comes to wet lab data generation, sometimes you're really limited by just the quantity of data that you can generate.” — Hanadie Yousef
“AI isn't the solution to everything. Oftentimes, you do still want to have that human in the loop and really test the accuracy of these models.” — Hanadie Yousef
Links:
Juvena Therapeutics on LinkedIn
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