Aryan Pedawi — accepted AI-conference papers

2026

APEX: Approximate-but-exhaustive search for ultra-large combinatorial synthesis libraries

Aryan Pedawi, Jordi Silvestre-Ryan, Bradley Worley, Darren Hsu, Kushal Shah, Elias Stehle +2

ICML 2026poster

Make-on-demand combinatorial synthesis libraries (CSLs) like Enamine REAL have significantly enabled drug discovery efforts. However, their large size presents a challenge for virtual screening, where the goal is to identify the top compounds in a library according to a computational objective (e.g.…

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2022

An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries

Aryan Pedawi, Pawel Gniewek, Chaoyi Chang, Brandon M Anderson, Henry van den Bedem

NeurIPS 2022accept

Virtual, make-on-demand chemical libraries have transformed early-stage drug discovery by unlocking vast, synthetically accessible regions of chemical space. Recent years have witnessed rapid growth in these libraries from millions to trillions of compounds, hiding undiscovered, potent hits for a va…

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