Drug metabolism prediction using computational models refers to the application of computer-based algorithms and simulations to forecast how pharmaceutical compounds will be chemically transformed within biological systems, primarily through enzymatic processes in the liver and other organs. Research published in In…
Drug metabolism prediction using computational models refers to the application of computer-based algorithms and simulations to forecast how pharmaceutical compounds will be chemically transformed within biological systems, primarily through enzymatic processes in the liver and other organs. Research published in In-vitro In-vivo In-silico Journal examines the integration of computational approaches with experimental methods in drug design and development. The journal has addressed how in silico techniques complement traditional in vitro and in vivo research strategies to advance pharmaceutical compound optimization. This topic holds significance because accurate prediction of metabolic pathways and clearance rates during early drug development stages can reduce the time and cost associated with bringing new therapeutics to market, while also identifying potential safety concerns before clinical trials. Computational models enable researchers to screen large numbers of candidate molecules and predict their metabolic stability, potential drug-drug interactions, and formation of active or toxic metabolites. By bridging theoretical predictions with laboratory validation and animal studies, these integrated approaches support more informed decision-making in pharmaceutical development and contribute to understanding the complex relationships between chemical structure and biological transformation.
1 peer-reviewed article, ranked by relevance. Each links to its DOI.