AI is reshaping early drug discovery, but persistent translational gaps, biological complexity, and validation challenges limit how far machine learning alone can predict human outcomes.
Integrating patient-derived xenografts and organoids can help researchers identify responsive tumor subsets, anticipate resistance, and strengthen translational confidence before clinical testing.
The FDA’s National Priority Voucher program aims to cut standard review times from potentially years to months, raising questions about safety, access, and public health impact.
Preclinical systems such as patient-derived xenografts are providing unprecedented insight into tumor biology and helping bridge the gap between discovery and clinical translation.
New study uses simulations and machine learning to identify a single, high-impact interaction within a viral fusion protein, highlighting a potential new target for antiviral drug development.