Computational and pharmacogenomic resources

With recent advances in the scientific world, drug design, drug work, and metabolism have been revolutionized. A “one-size-fits-all” model for drug distribution is faulty because there is significant heterogeneity in drug-response characteristics. The goal of pharmacogenomics is to increase therapeutic efficacy and minimize negative effects by examining how human genetic information affects drug response. The field of pharmacogenomics under which comprises of pharmacokinetics (PK) and pharmacodynamics (PD) has been revolutionized by well-established fields such as molecular modeling, computational biology, computational tools, computer-aided drug design (CADD), structure-based drug design (SBDD), ligand-based drug design (LBDD), C2Maps, and traditional Chinese medicine systems pharmacology database and analytic platform (TCMSP). Pharmacogenomic resources, which include Pharmacogenomics Knowledge Base (PharmGKB), Pharmacogene Variation (PharmVar), DrugBank, SCAN and PACdb, Genotype-Cytotoxicity Association, Human Cytochrome P450 database, etc., are the backbone in the development design and metabolism of drugs. With these resources and associated fields, the construction of drugs on one’s genome specificity is giving leads all the way. The field of pharmacogenomics is leading from the front for the treatment and eradication of serious illness through the construction of personalized drugs by considering genome specificity. The computational approaches are more commonly used to identify disease-causing variants; however, their impact is quite less on variant drug response. Until now, a few algorithms have been developed to predict the effect of pharmacogenomic variations. Bioinformatics and pharmacogenomics are the two emerging fields that have a positive impact and decrease the risk along with overall cost.