Discover how Turbine Simulated Cell Technologies is transforming drug development by addressing biases in training data. Guests Bence Szalai, MD, PhD, and Istvan Taisz, MD, PhD, share insights on the challenges of biased AI models in biology and introduce their groundbreaking framework, EFFECT (Evaluation Framework for Predicting Efficacy of Cancer Treatment).

Learn how Turbine's innovative bias detector ensures meaningful predictions, enhancing the accuracy of drug response models. Explore their tailored in silico biomarker discovery process, including a collaboration with Cancer Research Horizons to identify the right patient populations for new cancer drugs.

By integrating recent patient samples, Turbine achieves remarkable predictive capabilities, significantly improving model accuracy. This episode is essential for anyone interested in the future of biotechnology and precision medicine. Don’t miss this opportunity to understand how Turbine is shaping the landscape of drug development.

Listen now and be part of the conversation that’s paving the way for more effective cancer treatments.

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