AI-driven Platform for Anti-Tubercular Drug Discovery

In collaboration with Institut Pasteur Korea, Standigm aims to assess the implementation and validation of an AI-based drug discovery platform for discovering new tuberculosis treatment drug leads with automated early discovery. With the aid of hit clustering, compound selection, in vitro assay testing, and prioritization of the final candidates, Standigm aims to validate the automated approach and refine the algorithm. In response to the urgent need for new anti-tubercular drugs, particularly in face of multidrug-resistant tuberculosis, the assessment of such AI-driven drug discovery platforms has the potential to accelerate the overall drug discovery process and to be applied widely to drug discovery in various disease areas.