Pharmacogenomics in drug discovery and development

Baldeep Singh, Preeti Jain, K. Devaraja, Sadhna Aggarwal

Research output: Chapter in Book/Report/Conference proceedingChapter


The drug development process aims to discover novel drugs with high efficacy and low toxicity. However, efficacy does not always replicate in patients after the drug is moved to the market. Furthermore, approved drugs could also show severe adverse effects in small or large number of individuals, leading to withdrawal from the market. Variable drug response generally occurs because of genetic variability in drug-metabolizing enzymes, drug transporter proteins, and drug targets among individuals. Pharmacogenomics utilizes genetic tests to look for associations of genetic variants with varying drug efficacy and adverse effects. With the integration of pharmacogenomics with the drug development process, one can define responders, nonresponders, and high-risk groups. Therefore, after the approval, genotyping the patients will help in the prescription of the drug and its most effective and least toxic dose. However, other factors such as age, gender, and ethnicity should also be examined before the prescription. The single-gene approach, multigene approach, and haplotype study are different methods for studying the polymorphism among individuals. Marginal associations of the genetic factor with drug response, the complexity of pharmacogenomic results, the time lag between test order and report, and the emergence of rare but severe adverse effects are some challenges to integrate pharmacogenomics in the drug discovery process. Despite these challenges, high-throughput sequencing technologies, machine learning, appropriate surveillance system, and some web tools could provide future opportunities.

Original languageEnglish
Title of host publicationPharmacogenomics
Subtitle of host publicationfrom Discovery to Clinical Implementation
Number of pages40
ISBN (Electronic)9780443153365
ISBN (Print)9780443153372
Publication statusPublished - 01-01-2023

All Science Journal Classification (ASJC) codes

  • Medicine(all)
  • Biochemistry, Genetics and Molecular Biology(all)


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