Drug discovery is a complex and risky process, often plagued by lengthy timelines, high costs, and significant attrition rates in later development stages. The primary cause for failures in clinical trials is toxicity, responsible for over 40% of drug candidates being unsuccessful.
To address this challenge, various computational tools have emerged to screen and optimize potential drugs early in the development process.
However, there remains a growing need for platforms capable of assessing human toxicity on a large scale.Here, we introduce ModTox, a comprehensive computational platform designed for analyzing and improving the toxicity profiles of small molecules.
Leveraging established techniques such as molecular dynamics, docking, and machine learning, ModTox enables researchers to identify and mitigate toxicity risks efficiently.
By facilitating early toxicity screening and optimization, ModTox aims to enhance the success rates of drug development while minimizing costs and time investments.
Modesto Orozco, Institute for Research in Biomedicine (IRB) - Spain