PERSONALIZED DRUG DEVELOPMENT: TAILORING THERAPIES FOR INDIVIDUAL GENETIC PROFILES

Abstract

Personalized drug development has emerged as a transformative approach in precision medicine, shifting the focus from standardized treatment protocols to therapies tailored to individual genetic profiles. This paradigm aims to enhance therapeutic efficacy, minimize adverse drug reactions, and improve clinical outcomes by integrating genomic, environmental, and lifestyle information into treatment planning.This study explores the application of pharmacogenomics, gene editing technologies (such as CRISPR-Cas9), and next-generation sequencing (NGS) in developing personalized therapeutics. The methodology involved a comprehensive review and synthesis of advancements in genomic profiling, enzyme polymorphism analysis, and gene-targeted drug design. The investigation also includes modeling of genotype-drug interactions and proposed workflows to optimize drug selection and dosing strategies.Results indicate that genetic variability in drug-metabolizing enzymes, especially those in the CYP450 family, significantly influences drug efficacy and toxicity. Pharmacogenomic testing demonstrated strong predictive value in selecting appropriate therapeutic agents and dosages for patients across various domains including oncology, cardiology, and neuropharmacology. The integration of genomic technologies was shown to improve the precision of treatment while reducing healthcare costs related to adverse reactions and trial-and-error prescribing.The study concludes that while personalized drug development offers substantial clinical benefits, its implementation is hindered by ethical, regulatory, and accessibility challenges. Safeguarding genetic privacy, updating regulatory frameworks, and ensuring equitable access to genomic tools are critical for the widespread adoption of this model. Overall, personalized medicine is poised to redefine modern therapeutics, enabling safer and more effective treatment pathways aligned with individual biological variation.