Integrating in silico drug design and predictive ADMET modeling: from virtual screening to in vivo outcomes

The drug discovery landscape is being revolutionized by the integration of computational methods with traditional experimental approaches. In silico drug design, paired with predictive ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) modeling, has emerged as a powerful tool, streamlining the path from virtual screening to real-world therapeutic outcomes. Advanced computational techniques, such as molecular docking and dynamics simulations, enable researchers to explore vast chemical spaces and design drug candidates with optimal pharmacological properties. However, translating these predictions into effective treatments remains challenging, particularly in understanding how drug candidates interact within the biological environment.

For more information and to contribute to this research topic, visit: bit.ly/4duoYko

To address this, predictive ADMET modeling provides critical insights into the pharmacokinetic and toxicological profiles of potential drugs, helping researchers make informed decisions early in the drug discovery process and reducing the risk of late-stage failures. A forthcoming special issue will showcase the latest advancements in the synergy between in silico design and ADMET modeling, featuring contributions from leading experts.

This issue aims to foster interdisciplinary dialogue and accelerate the development of novel therapeutics by highlighting cutting-edge methodologies and translational insights.