Pharmacogenomics-Guided Drug Dose Adjustment in Personalized Medicine: A Systematic Literature Review

Zakiah Thahir, Rahmah Mustarin, Rahmadani Rahmadani, Yuyun Sri Wahyuni, Delvi Sara Jihan Pahira, Suhartini Suhartini, A.Tenriugi Daeng Pine

Abstract


Pharmacogenomics-guided drug dose adjustment is an important approach in personalized medicine because genetic polymorphisms can influence drug metabolism, therapeutic response, dose requirements, and the risk of adverse drug reactions. This systematic literature review synthesized recent evidence on pharmacogenomics-guided dose adjustment, clinically relevant pharmacogenomic biomarkers, and emerging technologies supporting precision medicine. Literature searches were conducted in Scopus and PubMed for studies published between January 2021 and May 2026. Eligible studies were selected using predefined PICOS criteria and synthesized narratively because of heterogeneity in study design, therapeutic area, biomarkers, and reported outcomes. A total of 23 studies were included in the qualitative synthesis. The evidence covered various therapeutic areas, including infectious diseases, neurology, psychiatry, oncology, cardiovascular medicine, and transplantation. Pharmacogenomic-guided dosing was most clearly supported for clinically established gene–drug pairs, including CYP2C9/VKORC1–warfarin, CYP2C19-related therapies, DPYD–fluoropyrimidines, SLCO1B1–statins, CYP2B6–efavirenz, and selected CYP3A5-related immunosuppressant therapies. Other biomarkers, such as ABCB1, APOE, GABRG2, UGT genes, and receptor-related polymorphisms, were associated with treatment response or drug disposition but still require stronger clinical validation for routine dose-adjustment recommendations. Emerging technologies, including clinical decision support systems, model-informed precision dosing, population pharmacokinetic modeling, bioinformatics, artificial intelligence, and machine learning, may strengthen biomarker interpretation and individualized dose optimization. Overall, pharmacogenomic-guided dose adjustment is a promising strategy to support safer and more precise pharmacotherapy, although broader implementation requires standardized guidelines, prospective validation, population-specific evidence, and integration into routine healthcare systems.

Keywords


Pharmacogenomics; Drug Dose Adjustment; Personalized Medicine; Precision Medicine; Genetic Biomarkers

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References


E. A. Ashley, “Towards precision medicine,” Nature Reviews Genetics, vol. 17, no. 9, pp. 507–522, 2016. [Online]. Available: https://doi.org/10.1038/nrg.2016.86

M. Pirmohamed, “Pharmacogenomics: Current status and future perspectives,” Nature Reviews Genetics, vol. 24, no. 6, pp. 350–362, 2023. [Online]. Available: https://doi.org/10.1038/s41576-022-00572-8

M. Pirmohamed, “Pharmacogenomics: Current status and future perspectives,” Nature Reviews Genetics, vol. 24, no. 6, pp. 350–362, 2023. [Online]. Available: https://doi.org/10.1038/s41576-022-00572-8

M. V. Relling and W. E. Evans, “Pharmacogenomics in the clinic,” Nature, vol. 526, no. 7573, pp. 343–350, 2015. [Online]. Available: https://doi.org/10.1038/nature15817

R. M. Turner, E. F. Magavern, and M. Pirmohamed, “Pharmacogenomics: Relevance and opportunities for clinical pharmacology,” British Journal of Clinical Pharmacology, vol. 88, no. 9, pp. 3943–3946, 2022. [Online]. Available: https://doi.org/10.1111/bcp.15329

Y. Daali, A. Rostami-Hodjegan, and C. F. Samer, “Editorial: Precision medicine: Impact of cytochromes P450 and transporters genetic polymorphisms, drug-drug interactions, disease on safety and efficacy of drugs,” Frontiers in Pharmacology, vol. 12, art. no. 834717, 2022. [Online]. Available: https://doi.org/10.3389/fphar.2021.834717

R. Mosch, M. van der Lee, H. J. Guchelaar, and J. J. Swen, “Pharmacogenetic panel testing: A review of current practice and potential for clinical implementation,” Annual Review of Pharmacology and Toxicology, vol. 65, no. 1, pp. 91–109, 2025. [Online]. Available: https://doi.org/10.1146/annurev-pharmtox-061724-080935

J. D. Duarte and L. H. Cavallari, “Pharmacogenetics to guide cardiovascular drug therapy,” Nature Reviews Cardiology, vol. 18, no. 9, pp. 649–665, 2021. [Online]. Available: https://doi.org/10.1038/s41569-021-00549-w

S. Thottunkal et al., “Clinician experiences at the frontier of pharmacogenomics and future directions,” Journal of Personalized Medicine, vol. 15, no. 7, art. no. 294, 2025. [Online]. Available: https://doi.org/10.3390/jpm15070294

H. Hardi, Z. Fitrianti, L. E. Mahata, and M. Louisa, “Pharmacogenetics in tuberculosis-HIV coinfected populations: A systematic review of genetic variants influencing antiretroviral and anti-tuberculosis drug response,” Journal of Multidisciplinary Healthcare, vol. 18, pp. 7203–7218, 2025. [Online]. Available: https://doi.org/10.2147/JMDH.S555909

F. M. M. Climacosa et al., “The role of genetic polymorphisms on drug response in Alzheimer’s disease: A systematic review,” BMC Medical Genomics, vol. 18, art. no. 1, pp. 1–20, 2025. [Online]. Available: https://doi.org/10.1186/s12920-025-02225-1

M. Biswas, N. Vanwong, and C. Sukasem, “Pharmacogenomics and non-genetic factors affecting drug response in autism spectrum disorder in Thai and other populations: Current evidence and future implications,” Frontiers in Pharmacology, vol. 14, art. no. 1285967, 2023. [Online]. Available: https://doi.org/10.3389/fphar.2023.1285967

S. A. Anghel et al., “Receptor pharmacogenomics: Deciphering genetic influence on drug response,” International Journal of Molecular Sciences, vol. 25, no. 17, art. no. 9371, 2024. [Online]. Available: https://doi.org/10.3390/ijms25179371

S. Hausman-Cohen, C. Bilich, S. Kapoor, E. Maristany, A. Stefani, and A. Wilcox, “Genomics as a clinical decision support tool for identifying and addressing modifiable causes of cognitive decline and improving outcomes: Proof of concept support for this personalized medicine strategy,” Frontiers in Aging Neuroscience, vol. 14, art. no. 862362, 2022. [Online]. Available: https://doi.org/10.3389/fnagi.2022.862362

A. Ortolan, G. Cozzi, M. Lorenzin, P. Galozzi, A. Doria, and R. Ramonda, “The genetic contribution to drug response in spondyloarthritis: A systematic literature review,” Frontiers in Genetics, vol. 12, art. no. 703911, 2021. [Online]. Available: https://doi.org/10.3389/fgene.2021.703911

X. Shen et al., “Pharmacogenetics-based population pharmacokinetic analysis and dose optimization of valproic acid in Chinese southern children with epilepsy: Effect of ABCB1 gene polymorphism,” Frontiers in Pharmacology, vol. 13, art. no. 1037239, 2022. [Online]. Available: https://doi.org/10.3389/fphar.2022.1037239

Y. Jarrar and S. J. Lee, “The functionality of UDP-glucuronosyltransferase genetic variants and their association with drug responses and human diseases,” Journal of Personalized Medicine, vol. 11, no. 6, art. no. 554, 2021. [Online]. Available: https://doi.org/10.3390/jpm11060554

H. Aypek, O. Aygormez, and Y. Caliskan, “Genomics in pancreas–kidney transplantation: From risk stratification to personalized medicine,” Genes, vol. 16, no. 8, art. no. 884, 2025. [Online]. Available: https://doi.org/10.3390/genes16080884

C. Delage et al., “Cytochromes P450 and P-glycoprotein phenotypic assessment to optimize psychotropic pharmacotherapy: A retrospective analysis of four years of practice in psychiatry,” Journal of Personalized Medicine, vol. 12, no. 11, art. no. 1869, 2022. [Online]. Available: https://doi.org/10.3390/jpm12111869

S. Rezayi, S. R. N. Kalhori, and S. Saeedi, “Effectiveness of artificial intelligence for personalized medicine in neoplasms: A systematic review,” BioMed Research International, vol. 2022, art. no. 7842566, 2022. [Online]. Available: https://doi.org/10.1155/2022/7842566

J. Khong et al., “Tacrolimus dosing in liver transplant recipients using phenotypic personalized medicine: A phase 2 randomized clinical trial,” Nature Communications, vol. 16, art. no. 1, 2025. [Online]. Available: https://doi.org/10.1038/s41467-025-59739-6

J. J. Lima et al., “Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2C19 and proton pump inhibitor dosing,” Clinical Pharmacology & Therapeutics, vol. 109, no. 6, pp. 1417–1423, 2021. [Online]. Available: https://doi.org/10.1002/cpt.2015

S. L. Stocker and T. M. Polasek, “Using pharmacogenomics to personalise drug therapy: Which drugs, when and how,” Australian Prescriber, vol. 48, no. 3, pp. 82–86, 2025. [Online]. Available: https://doi.org/10.18773/austprescr.2025.021

M. Bigossi et al., “A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance,” European Heart Journal - Cardiovascular Pharmacotherapy, vol. 9, no. 6, pp. 536–545, 2023. [Online]. Available: https://doi.org/10.1093/ehjcvp/pvad040

L. Marques et al., “Advancing precision medicine: A review of innovative in silico approaches for drug development, clinical pharmacology and personalized healthcare,” Pharmaceutics, vol. 16, no. 3, art. no. 332, 2024. [Online]. Available: https://doi.org/10.3390/pharmaceutics16030332

T. M. Polasek and R. W. Peck, “Beyond population-level targets for drug concentrations: Precision dosing needs individual-level targets that include superior biomarkers of drug responses,” Clinical Pharmacology & Therapeutics, vol. 116, no. 3, pp. 602–612, 2024. [Online]. Available: https://doi.org/10.1002/cpt.3197

S. Goutelle, M. Guidi, V. Gotta, C. Csajka, T. Buclin, and N. Widmer, “From personalized to precision medicine in oncology: A model-based dosing approach to optimize achievement of imatinib target exposure,” Pharmaceutics, vol. 15, no. 4, art. no. 1081, 2023. [Online]. Available: https://doi.org/10.3390/pharmaceutics15041081

L. V. Karthikeyan, Subamathi, Pragathi, Vaishnavi, Sanjana, and Sangamithra, “Effectiveness of pharmacogenomics-guided dosing in improving treatment outcomes,” Indian Journal of Pharmacology, vol. 58, no. 4, pp. 332–341, 2026. [Online]. Available: https://pubmed.ncbi.nlm.nih.gov/42583968/

A. Maslarinou, V. G. Manolopoulos, and G. Ragia, “Pharmacogenomic-guided dosing of fluoropyrimidines beyond DPYD: Time for a polygenic algorithm?,” Frontiers in Pharmacology, vol. 14, art. no. 1184523, 2023. [Online]. Available: https://doi.org/10.3389/fphar.2023.1184523

D. K. Sahu, “Applications of pharmacogenomics in personalized drug therapy and precision healthcare management,” vol. 5, no. 1, pp. 78–84, 2026. [Online]. Available: https://www.researchgate.net/publication/406978851_Applications_of_Pharmacogenomics_in_Personalized_Drug_Therapy_and_Precision_Healthcare_Management

N. M. A., I. D. Yusuf, and M. H. Y., “Personalized medicine in cardiovascular pharmacology: Advances in pharmacogenomics and drug development,” Open Journal of Clinical Diagnostics, 2025. [Online]. Available: https://www.scirp.org/journal/paperinformation?paperid=145292

J. Lu et al., “Genetic polymorphism of GABRG2 rs211037 is associated with drug response and adverse drug reactions to valproic acid in Chinese southern children with epilepsy,” Pharmacogenomics and Personalized Medicine, vol. 14, pp. 1141–1150, 2021. [Online]. Available: https://doi.org/10.2147/PGPM.S32959




DOI: https://doi.org/10.37311/ijpe.v6i2.39109

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Copyright (c) 2026 Zakiah Thahir, Rahmah Mustarin, Rahmadani, Yuyun Sri Wahyuni, Delvi Sara Jihan Pahira, Suhartini, A.Tenriugi Daeng Pine

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