ADVANCED HPC BASED DRUG DISCOVERY WITH CONVERGED DEEP PHYSICS AND AI
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- ADVANCED HPC BASED DRUG...
A unified HPC framework aims to reduce structure generation time, binding free energy calculation time, and computing costs in the pharmaceutical industry, reducing discovery time by 25% and costs by 20%.
Start date: 01/06/2021
Duration in months: 18
Problem Description
Drug discovery costs around €800m and lasts around 5 years. Computer-aided drug design has emerged as a new in silico method for the discovery stage, with SMEs competing and outsourcing research. The SMEs Iktos and Qubit Pharmaceuticals help many pharma companies advance their research projects.
Goals
Reduce time to solution
Challenges
To offer services and products for the drug discovery stage: Iktos offers AI-based tools assisting with finding drug candidates, and Qubit Pharmaceuticals offers HPC-based computational tools to assess the quality of such candidates.
Innovation results
Using this new physics-based/AI-assisted workflow, ML algorithms can be trained using high-quality data from molecular simulations to understand protein target engagement that is not yet well described in the literature.
Business impact
Iktos and Qubit Pharmaceuticals developed an in silico framework for drug discovery with the potential to cut drug discovery time by 25% and reduce overall drug development costs by 20%, which translates to savings of several million euros or potentially much more.