AI Applications Beyond Drug Discovery in Biotech
This article features an interview with Abhishaike Mahajan, a specialist in biological machine learning currently working at Noetik. Mahajan argues that while AI has significantly advanced preclinical drug candidate generation, the true bottlenecks in developing new treatments lie in clinical and postclinical stages. Drawing from his diverse career trajectory, he illustrates AI's potential across the drug lifecycle. His experience at Anthem involved using machine learning on electronic health records for risk stratification and causal inference in postclinical settings. At Dyno Therapeutics, he focused on preclinical work, utilizing protein structure prediction models like AlphaFold and BindCraft to engineer viruses for genetic therapy delivery. Currently, at Noetik, his work targets the clinical stage by analyzing tumor microenvironments to predict patient responses to investigational cancer drugs. The discussion highlights a shift in focus from merely generating molecules to solving complex problems in clinical trials and personalized medicine, suggesting that AI's most impactful applications may reside in optimizing later stages of drug development rather than just initial discovery.
Wire timeline
AI Applications Beyond Drug Discovery in Biotech
This article features an interview with Abhishaike Mahajan, a specialist in biological machine learning currently working at Noetik. Mahajan argues that while AI has significantly advanced preclinical drug candidate generation, the true bottlenecks in developing new treatments lie in clinical and postclinical stages. Drawing from his diverse career trajectory, he illustrates AI's potential across the drug lifecycle. His experience at Anthem involved using machine learning on electronic health records for risk stratification and causal inference in postclinical settings. At Dyno Therapeutics, he focused on preclinical work, utilizing protein structure prediction models like AlphaFold and BindCraft to engineer viruses for genetic therapy delivery. Currently, at Noetik, his work targets the clinical stage by analyzing tumor microenvironments to predict patient responses to investigational cancer drugs. The discussion highlights a shift in focus from merely generating molecules to solving complex problems in clinical trials and personalized medicine, suggesting that AI's most impactful applications may reside in optimizing later stages of drug development rather than just initial discovery.
Asterisk