#98, Advancing Adaptive Clinical Trials with Causal ML, with Raviv Pryluk from PhaseV

AWS Health Innovation Podcast

In this episode of the AWS Health Innovation Podcast, Guy Spigelman, EMEA lead for Healthcare and Life Sciences Startups at Amazon Web Services, sits down with Raviv Pryluk, CEO and Co-Founder of PhaseV, a company leveraging cutting-edge technologies like reinforcement learning and causal machine learning to revolutionize clinical trial design and execution.

1. How did Raviv and his co-founder identify the clinical trials space as ripe for innovation?

• Raviv shares the extensive research and criteria-driven process he undertook with co-founder Elad to identify the clinical trials space as ripe for innovation. They sought an area with major positive impact potential that leveraged their expertise in machine learning, neuroscience, and engineering.

2. What innovative technologies does PhaseV employ to transform clinical trials?

• PhaseV's platforms harness cutting-edge technologies like reinforcement learning and causal ML to enable adaptive trial designs and advanced data analysis. This allows more efficient, ethical trials with faster detection of subgroups responding differently to treatments.

3. How does PhaseV's causal ML platform extract insights from complex biological data?

• PhaseV's causal ML platform can analyze intricate biological mechanisms and multi-endpoint trials to identify true causal relationships, not just correlations. This surfaces actionable insights into why certain patient subgroups respond better to specific drugs.

4. How does PhaseV aim to accelerate drug development timelines?

• By leveraging machine learning for surrogate endpoints and virtual head-to-head comparisons in Phase 2, PhaseV aims to predict trial outcomes faster. This could dramatically reduce the 10+ year, $3B+ timeline for new drug approvals.

5. How is PhaseV positioned to capitalize on regulatory shifts post-COVID?

• The pandemic prompted increasing regulatory flexibility and digitization in clinical trials. PhaseV is well-positioned to capitalize on this evolving landscape and usher in a new era of precision medicine through innovative trial methodologies.

6. How does PhaseV build its multidisciplinary team?

• Raviv discusses PhaseV's strategic hiring approach, carefully assembling a diverse team spanning software, data science, medicine, and biology. Maintaining an "adaptive" mindset allows continuous reevaluation based on new data.

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