Simulating Clinical Trials with Orr Inbarr from Quant Health

Drug development is notoriously time-consuming and expensive, but what if we could simulate clinical trials before they even begin? Orr Inbar, Co-Founder and CEO of QuantHealth, joins me to explore how his team is doing just that. By simulating trials with AI-native models, QuantHealth helps pharmaceutical companies make better decisions about how to design trials and test drugs.

Orr shares how QuantHealth uses real-world patient data and detailed drug biology to build deep-learning models capable of forecasting patient responses to new therapies. He breaks down their biggest challenges, like the complexities of messy healthcare data, hidden biases, and the importance of domain knowledge when building AI tools for regulated environments. He also shares a key lesson for any AI startup: focus on solving real problems, not just building clever models. Tune in for a fascinating look at how AI is reshaping drug development and what the future of clinical trials could look like!

Key Points:

• Some background on Orr, his parents, and how he founded QuantHealth.
• Key problems QuantHealth is solving as a clinical trial simulation company.
• A breakdown of the biggest challenges facing clinical trials.
• Why we need to improve data-driven trials of drugs.
• How QuantHealth builds their foundation models for trial simulations.
• Examples of the type of predictions their models make in clinical contexts.
• How they use patient and drug data to make predictions and build “digital drugs”.
• Key challenges of working with these different types of data.
• Methods for combating bias, including the use of exogenous data. 
• How they incorporate the medical context in model development.
• QuantHealth’s validation process: how they meet rigorous industry standards.
• Orr’s advice to other AI startups on creating value, not just smart models.
• Where you can expect to see QuantHeath in the next three to five years.

Quotes:

“There is a constant desire in drug development and pharmaceutical research to get your hands on more data. This makes sense since it's a very data-driven industry. But at the same time, there was a mismatch there, because there's actually quite a lot of data already out there.” — Orr Inbar

“How do we bridge the gap between the data that we already have and the insights that we need to generate to answer those questions?” — Orr Inbar

“If you take a step back and look at how drugs are being developed today and with an emphasis on clinical trials, we're essentially doing the same things that we were doing 50 years ago.” — Orr Inbar

“Even in a world of GenAI, you can't just snap your fingers and get the solution. It requires a lot of work to structure and harmonize the data.” — Orr Inbar

“Every trial that we simulate, we first go through a data enrichment process where we look for the latest information in terms of research publications, recently completed trials that are relevant to our drug of interest, and incorporate that data into our data sets.” — Orr Inbar

Links:

Orr Inbar on LinkedIn
QuantHealth

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