Advances in Genomics for Drug Development

Abstract

Drug development (target identification, advancing drug leads to candidates for preclinical and clinical studies) can be facilitated by genetic and genomic knowledge. Here, we review the contribution of population genomics to target identification, the value of bulk and single cell gene expression analysis for understanding the biological relevance of a drug target, and genome-wide CRISPR editing for the prioritization of drug targets. In genomics, we discuss the different scope of genome-wide association studies using genotyping arrays, versus exome and whole genome sequencing. In transcriptomics, we discuss the information from drug perturbation and the selection of biomarkers. For CRISPR screens, we discuss target discovery, mechanism of action and the concept of gene to drug mapping. Harnessing genetic support increases the probability of drug developability and approval.

Drug–Drug Interactions in Vestibular Diseases, Clinical Problems, and Medico-Legal Implications

“…Furthermore, sex-aging related differences in genomic instability were found, including a major tendency of DNA mutations, telomere attrition and sometimes methylation in men [ 258 ]. This assumption may affect gene expression related drug development, one of the present and future direction of pharmaceutic industry [ 259 , 260 ]. In addition, physicians should remember that females live longer than males, but have a higher risk of frailty and morbidity.…”

Hippo(crates): An integrated atlas for natural product exploration through a state‑of‑the art pipeline in chemoinformatics

“…Recent advances in genetics, clinical genomics and personalized medicine have led to the need of discovering effective therapeutic agents for several pathological conditions (51)(52)(53)(54). The discovery and correlation of NPs has shed light on the seemingly unrelated correlation between human diseases and certain molecules, leading to novel biologically active drugs.…”

Prediction of recessive inheritance for missense variants in human disease

“…Computational methods to predict the effect of coding variants have numerous applications, such as the diagnosis of genetic diseases [1][2][3][4] , genetic association studies [5][6][7][8] , and drug design 9,10 . Currently available methods perform very well at discriminating pathogenic and benign missense variants, typically reporting accuracy in the range of 58-86% [11][12][13] .…”