Assessment of Drug Efficacy in Indian Maternity Hereditary Lineage: A Pharmaco-Genomics Study

Context & Background

India is the second largest market for internationally manufactured drugs. However, clinical trials are primarily done on Western populations, leaving maternal healthcare guidelines in India based on biased genetic databases. Hereditary genetic variations in the Indian population can cause significant differences in drug efficacy and adverse drug reactions (ADR) in mothers and newborns.

Problems to be Addressed

Maternal and prenatal health disorders require precise treatment, but prescribing generic drug therapies without accounting for genetic diversity leads to high rates of toxicity and treatment failure. There is currently no comprehensive repository mapping drug-kinase interactions for the Indian population.

Aims and Objectives

1. Identify variations in kinase proteins that destabilize drug interactions using IndiGen genomic data.
2. Propose alternative drug modifications using machine learning to minimize ADR in offspring.

Methodology

The project compiles a druggable kinase gene dataset from Indian maternity lineages. Variants are modeled at structural levels using homology and ab-initio modeling. High-throughput screening and quantitative structure-activity relationship (QSAR) modeling estimate drug binding affinity, which is then validated experimentally in-vitro.

Expected Outcomes

A database of kinase variants in the Indian population, validated target candidates for personalized maternal medicine, and commercialization of software workflows for drug screening.