Husna Rahim, PharmD, RPh & Emma Louis, B.S. Secondary Author
• Pharmacogenomic testing identifies genetic variations affecting drug metabolism in elderly patients managing multiple chronic conditions
• Next-generation sequencing technologies enhance detection of complex drug-gene interactions in polypharmacy scenarios
• Implementation requires healthcare system integration and specialized clinical decision support tools
Two 75-year-olds with identical health issues—diabetes, hypertension, and heart disease—take the same five medications. One does well; the other experiences severe side effects requiring hospitalization. This scenario plays out daily across healthcare systems, with adverse drug reactions (ADRs) accounting for 10-30% of hospital admissions among elderly patients (Swen et al., 2018). The management of multiple medications, or polypharmacy, is further complicated by genetic variations that influence drug metabolism. Enhancing medication safety for the elderly requires the integration of next-generation sequencing (NGS), age-specific clinical decision support systems (CDSS), and medication review practices based on genetic information.
Unlike traditional single-gene testing, NGS sequences entire genomes in one analysis, providing comprehensive pharmacogenomic (PGx) insights crucial for elderly patients taking multiple medications (Green at al., 2016). However, clinical uptake of NGS-based PGx testing remains limited, with most clinical laboratories still relying on targeted genotyping assays rather than sequencing (Schwarz et al., 2019). Advancement with NGS enables clinicians to anticipate drug response with superior precision before prescribing, rather than reacting to ADRs after they occur.
CDSS specifically designed for elderly polypharmacy represents essential infrastructure for translating genetic data into actionable treatment modifications. These systems must integrate PGx information with age-related physiological changes, comorbidities, and existing medication regimens (Moore et al., 2023). NGS and sophisticated algorithms work hand in hand: the former generates vital data, while the latter contextualizes other variables to transform the results into actionable clinical insights.
Finally, medication reconciliation protocols incorporating PGx data can transform routine transitions of care into opportunities for optimization. Each hospital admission, discharge, or specialist referral becomes a checkpoint for reviewing genetic compatibility across all prescribed medications (Siu et al., 2025). This systematic approach prevents ADRs during particularly vulnerable transition periods.
Green DJ, Mummaneni P, Kim IW, Oh JM, Pacanowski M, Burckart GJ. Pharmacogenomic information in FDA-approved drug labels: Application to pediatric patients. Clin Pharmacol Ther. 2016;99(6):622-632. doi:10.1002/cpt.330
Moore C, Lazarakis S, Stenta T, et al. A systematic review of knowledge, attitude and practice of pharmacogenomics in pediatric oncology patients. Pharmacol Res Perspect. 2023;11(6):e01150. doi:10.1002/prp2.1150
Schwarz U, Gulitat M, Kim R. The Role of Next-Generation Sequencing in Pharmacogenetics and Pharmacogenomics. Cold Spring Harb Perspect Med. 2019;9(2):a033027. doi:10.1101/cshperspect.a033027.
Siu WS, Maruf AA, Shaheen SM, et al. Estimating the Frequency of False-Negative Pharmacogenetic Test Results by Self-Reported Ancestry. Clin Pharmacol Ther. Published online April 27, 2025. doi:10.1002/cpt.3697
Swen JJ, Nijenhuis M, van Rhenen M, et al. Pharmacogenetic Information in Clinical Guidelines: The European Perspective. Clin Pharmacol Ther. 2018;103(5):795-801. doi:10.1002/cpt.1049