Pharmacogenomics-driven precision pharmacy: Mechanisms, challenges, and translational advances

Pharmacogenomics of Adverse Drug Reactions: Integrating Genetic Biomarkers into Precision Pharmacotherapy

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.

Pharmacogenetics and Pharmacogenomics as Enabling Technologies for Precision Drug Development and Personalized Therapy.

Pharmacogenomics and Precision Pharmacotherapy in Heart Failure: A Narrative Review

Heart failure is a life-threatening condition affecting approximately 1% of the global population, with its prevalence continuing to rise. Genetic factors, including pathogenic variants in sarcomere, cytoskeletal, and ion channel genes, contribute to disease progression, often following Mendelian inheritance patterns. However, most interindividual variability in disease course and therapeutic response arises from polygenic, non Mendelian patterns, particularly single nucleotide polymorphisms (SNPs). SNPs can modestly influence gene expression, protein function, and downstream signaling pathways, thereby affecting the pharmacokinetics and pharmacodynamics of cardiovascular drugs. Variants in genes such as CYP2D6, ACE, AGT, CYP11B2, ADRB1/2, SLC5A2, and UGT2B4 have been associated with differential responses to β-blockers, SGLT2-inhibitors, and ACE inhibitors. The clinical application of genomic approaches remains limited due to small study sizes, interpatient variability, and the lack of standardized biomarkers. Nevertheless, integrating genetic, epigenetic, and phenotypic data offers a promising strategy to guide more effective and individualized heart failure pharmacotherapy.

CYP450 Gene Variations and Their Implications for Drug Response: A Pharmacogenomic Review

The Human Genome Project (HGP) has significantly advanced our understanding of how human genetic variation affects drug response, particularly through metabolic enzymes such as Cytochrome P450 (CYP450). This study aimed to explore the impact of genetic variation on drug metabolism and its consequences for precision medicine therapies. This approach involved a literature review of various scientific articles discussing pharmacogenomics, CYP450 enzymes, and their clinical applications. The findings indicate that CYP450 enzymes are crucial in drug metabolism, especially during phase I reactions, such as oxidation, and their activity is heavily influenced by genetic polymorphisms, including those in CYP2C19. These genetic differences lead to variations in the ability of individuals to activate or eliminate drugs, thereby affecting the effectiveness of therapy and the likelihood of side effects. In addition to genetic factors, drug interactions, environmental influences, and the microbiome also play a role in drug response. For instance, genetic variation in the use of clopidogrel can result in therapeutic failure or a heightened risk of clinical events. Ultimately, integrating genomic data from the HGP with CYP450 enzyme profiles provides a vital basis for implementing precision medicine, allowing for more accurate drug and dosage selection, thereby enhancing therapeutic effectiveness and reducing the risk of side effects in patients.

Pharmacogenomic Determinants of Post-Liver Transplant Diabetes Mellitus: A Systematic Review and In Silico Pharmacogenomic Analysis

Tacrolimus remains central to liver transplantation, yet its narrow therapeutic index and pharmacokinetic variability are associated with increased risk of post-transplant diabetes mellitus (PTDM). While polymorphisms in metabolizing enzymes modulate drug exposure and diabetogenic risk, this relationship has not been systematically integrated through targeted pharmacogenomic approaches. The objective of this study was to systematically evaluate genetic variants in tacrolimus-metabolizing genes and their associations with PTDM through integrated in silico pharmacogenomic analysis. An in silico analysis was performed, integrating data from public repositories (PharmGKB), curated literature, and functional annotations of genetic variants. Machine learning models were developed using synthetic data generated from literature-derived effect sizes to demonstrate proof-of-concept feasibility. We prioritized genes (CYP3A5, CYP3A4, ABCB1) based on PharmGKB evidence levels, functional impact, and clinical associations with tacrolimus exposure and PTDM risk, incorporating genotype information, drug dosing, and metabolic outcomes. The CYP3A5*1 allele emerged as a key determinant, consistently requiring 1.5- to 2.8-fold higher tacrolimus doses and conferring a significantly elevated risk of PTDM compared to non-expressers, an effect mediated by cumulative drug exposure. In the systematic review and synthetic modeling, carriers of functional CYP3A5 alleles with expressing genotypes exhibited a significantly increased PTDM risk relative to non-expressers, demonstrating a clear dose–exposure–toxicity relationship. In contrast, CYP3A4 and ABCB1 showed only suggestive but heterogeneous evidence of association. This in silico pharmacogenomic study demonstrates a clinically significant association between genetic variability in tacrolimus metabolism and the development of PTDM following liver transplantation. These findings support genotype-guided strategies to optimize immunosuppressive therapy and advance precision medicine in transplant care.

Pharmacogenomic and Drug Interactions Risk in Cardio-Oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.