How AI Can Boost Biotech Success Rates With: Krish Ramadurai
Krish Ramadurai explains how AI is transforming biotech from a high-risk guessing game into a predictive science. He discusses the need for diverse, human-based datasets to avoid the pitfalls of biased models that lead to drug failure. Ramadurai highlights the value of rescuing shelved drugs using chemo-informatics to tweak their properties for renewed clinical viability, as well as investing in companies with strong data moats. By combining robust biology with advanced AI, he envisions reversing biotech’s current 95% failure rate and accelerating time to market for safe, effective therapies.
Episode Contents:
About the Guest
Krish Ramadurai is a Partner at AIX Ventures, leading healthcare and life sciences investments in AI-driven biotech. Learn more at: https://www.linkedin.com/in/krishramadurai/
Key Takeaways
- AI can reduce biotech’s high failure rates by using human data early.
- Diverse, high-quality datasets improve drug trial success.
- Rescuing shelved drugs can be faster and cheaper than de novo development.
Transcript Summary
What is predictable and engineerable biology?
Using AI and robust human datasets to design drug assets with a high likelihood of clinical success.
Why do many AI-designed drugs fail?
They’re often trained on limited or biased datasets, leading to toxicity or poor trial performance.
How can AI speed biotech progress?
By rescuing shelved assets using chemo-informatics and building diverse data moats to guide development.
More Topics
- AI in Patient Care
- AI in the Healthcare Industry
- AI and Medical Innovation
- Healthcare Ethics and Policy
Keep Exploring
About the Series
AI and Healthcare—with Mika Newton and Dr. Sanjay Juneja is an engaging interview series featuring world-renowned leaders shaping the intersection of artificial intelligence and medicine.
Dr. Sanjay Juneja, a hematologist and medical oncologist widely recognized as “TheOncDoc,” is a trailblazer in healthcare innovation and a rising authority on the transformative role of AI in medicine.
Mika Newton is an expert in healthcare data management, with a focus on data completeness and universality. Mika is on the editorial board of AI in Precision Oncology and is no stranger to bringing transformative technologies to market and fostering innovation.