Pharmacogenomics (PGx) is an evolving field that integrates genetic information into clinical decision-making to optimize drug therapy and minimize adverse drug reactions (ADRs). Its application in rare disease (RD) drug development is promising, given the genetic basis of many RDs and the need for precision medicine approaches. Despite significant advancements, challenges persist in developing effective therapies for RDs due to small patient populations, genetic heterogeneity, and limited surrogate biomarkers. The Orphan Drug Act in the U.S. has incentivized RD drug development. However, the traditional drug approval process is constrained by logistical and economic challenges, necessitating innovative PGx-driven strategies. Identifying genetic biomarkers in the early drug development stages can optimize dose selection, enhance therapeutic efficacy, and reduce ADRs. Case studies such as eliglustat for Gaucher disease and ivacaftor for cystic fibrosis demonstrate the efficacy of PGx-guided treatment strategies. Integrating PGx into global drug development requires the harmonization of regulatory policies and increased diversity in genetic research. Artificial intelligence (AI) tools further enhance genetic analysis, disease prediction, and clinical decision-making. Modernizing drug labeling with PGx information is critical to ensuring safe and effective drug use. Collectively, PGx offers transformative potential in RD therapeutics by facilitating personalized medicine approaches and addressing unmet medical needs.
Keywords: Pharmacogenomics; dose optimization; drug development; genetic biomarkers; personalized medicine; precision medicine; rare diseases.
Pharmacogenomics (PGx) is transforming drug development by using genetic information to personalize treatments, improve dosing, and reduce treatment side effects. This is especially important for rare diseases (RD), where small patient groups and genetic differences make treatment challenging. PGx helps identify the best responders and improve drug effectiveness. While regulations like the Orphan Drug Act have sped up RD drug development, identifying the ideal dose to achieve the greatest treatment benefits with the lowest risk remains a major challenge. Examples like eliglustat for Gaucher disease and ivacaftor for cystic fibrosis show the benefits of PGx in precision medicine. However, obstacles such as regulatory differences, lack of diversity in genetic research, and the complexity of RD remain. Advancements in artificial intelligence, global data-sharing, and inclusive clinical trials are crucial to overcoming these issues. Expanding PGx use in clinical practice will improve personalized treatments and patient outcomes.