Jul 2026· Current Drug Discovery Technologies· Vol 23· 0 citations
Medicine
TL;DR
How pharmacogenetics and pharmacogenomics function as enabling technologies across the pharmaceutical and clinical domains is synthesized, with emphasis on biomarker-guided drug development, patient stratification, safety optimization, regulatory translation, precision oncology, sex-related variability, population diversity, artificial intelligence, and multi-omics integration.
The integration of pharmacogenomics into routine healthcare has the potential to optimize individualized drug therapy, minimize preventable ADRs, and accelerate the transition toward precision medicine, ultimately improving clinical outcomes and healthcare quality.
Rayapudi Vasavi Sai Saraswati, U. M. Vattikuti, Arthika Chauhan Laudia et al.· International Journal of Cur...· 0 citations
The integration of artificial intelligence and machine learning approaches for pharmacogenomic prediction, the emergence of polygenic risk scores, and the role of multi-omics integration in refining therapeutic decision-making are examined.
Hao Sun, Zijun Qiao, Jinze Yu et al.· Brazilian Journal of Science· 0 citations
A critical evaluation of clinically validated PGx biomarkers for chemotherapeutics and targeted therapy with a focus on translational relevance and strength of evidence shows high-impact germline markers such as DPYD, TPMT, NUDT15 and UGT1A1 are highlighted as key determinants of genotype-guided dosing for improving safety without compromising efficacy.
Satyam Kumar Vishwash, Ram Babu Soni, Sourabh Kosey et al.· Journal of chemotherapy· 0 citations
Off-label drug use (OLDU) is frequent in populations insufficiently represented in clinical trials, including pediatrics, rare diseases, and psychiatry. Although it broadens
therapeutic options, uncertainty regarding safety and response remains a central concern. Physical
chemistry properties influence drug distribution, target promiscuity, and exposure profiles in offlabel contexts. Because the biological processes that translate these intrinsic molecular properties
into pharmacokinetic and pharmacodynamic phenotypes are modulated by genetic variability,
pharmacogenomics may provide a complementary strategy for anticipating interindividual differences in safety and efficacy.
This narrative review integrates pharmacogenomics (PGx) evidence from
curated clinical resources (ClinPGx, CPIC, DPWG, and regulatory sources) with principles of medicinal chemistry, prioritizing mechanistic evidence linking genetic variability to drug response variability in commonly prescribed off-label therapies across selected therapeutic areas.
Across the therapeutic areas examined, several drugs with frequent off-label use were identified as having available pharmacogenetic information. A subset of these agents was further discussed, considering mechanistic considerations derived from medicinal chemistry principles.
Intrinsic molecular characteristics help explain biodistribution patterns and off-target
effects observed during off-label prescribing. Gene-drug interactions involving metabolizing enzymes and transporters consistently influence drug response. Evidence specifically designed for
OLDU remains limited.
The convergence of medicinal chemistry and pharmacogenomics may offer a promising framework to enhance safety and precision in off-label prescribing. Although direct evidence in
these settings remains limited, the established influence of genetic variation on drug pharmacokinetics and pharmacodynamics provides a biologically plausible rationale for exploring PGx-guided
approaches in OLDU
Mariana Meira Scudeler, Isadora Renck Scherer, Gabriel Vaisam Castro et al.· Mini-Reviews in Medical Chem...· 0 citations
Interindividual variability in drug response remains a major challenge in clinical pharmacology despite substantial advances in therapeutic drug monitoring (TDM), pharmacogenomics, pharmacokinetics/pharmacodynamics (PK/PD), and model-informed precision dosing (MIPD). Although these approaches have improved individualized therapy, clinically important variability in efficacy and toxicity persists because drug response is determined not only by systemic exposure but also by target engagement, disease biology, compensatory pathways, organ function, immune status, and dynamic patient-specific molecular states. Recent advances in multiomics, systems pharmacology, and artificial intelligence (AI) provide an opportunity to integrate these complementary biological and clinical dimensions within more comprehensive precision pharmacotherapy frameworks. This narrative review examines the evolving integration of PK, PD, TDM, pharmacometrics, multiomic technologies, mechanistic AI, and systems pharmacology across drug development and clinical care. Particular emphasis is placed on the limitations of exposure-based dosing alone, the biological determinants of interindividual variability, the transition from conventional TDM toward adaptive model-informed monitoring, and emerging approaches for integrating molecular and clinical data to support individualized therapeutic decision-making. Operon™ is discussed as an illustrative example of an internally operated mechanistic systems biology platform to demonstrate how biologically informed computational frameworks may integrate pharmacological and multiomic information within drug development workflows. The review further examines applications in polypharmacy, drug–drug interaction assessment, clinical trial enrichment, regulatory science, and adaptive dosing, while emphasizing that analytical validity, clinical validity, clinical utility, prospective validation, transparency, and clearly defined contexts of use remain essential prerequisites for clinical implementation. Collectively, these developments support a transition from concentration-guided dosing toward mechanism-informed precision pharmacotherapy that integrates drug exposure with biological response and clinical outcomes while maintaining rigorous standards for validation and regulatory acceptance.
Ian Jenkins, Krista Casazza, Waldemar Lernhardt et al.· Pharmaceutics· 0 citations
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.
Unknown authors· Indonesian Journal of Pharma...· 0 citations
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