Opioids are commonly prescribed as standards of care for various types of pain. Multiple pathways can impact pain response, and understanding medication metabolism is imperative to achieving optimal analgesic response. Pharmacogenomics (PGx) can assist with understanding interindividual variability and aid in safe medication prescribing. Genetic variants in pharmacokinetic and pharmacodynamic genes have been evaluated, and literature generally favors use of pharmacokinetic associations in clinical practice. Tramadol and codeine have the most literature to support integration of PGx into routine prescribing practices. Hydrocodone and oxycodone have theoretical implications; however, data have been inconsistent. Clinical decision support has been the mainstay of integration of PGx results into routine clinical practice. Future research should focus on additional pathways implicated in opioid metabolism and response to further guide effective pain management with opioids.

Cardiovascular diseases (CVD) remain a predominant cause of mortality and morbidity globally. Conventional therapy methods may be constrained by their inadequate acknowledgment of individual genetic and clinical variations. In this context, pharmacogenetics and artificial intelligence (AI) applications, essential elements of the precision medicine approach, present a novel paradigm for the management of cardiovascular disorders. Pharmacogenetics elucidates the genetic basis of individual responses to drugs, thereby improving treatment success and minimizing adverse drug effects. Conversely, artificial intelligence facilitates enhanced diagnostic accuracy, risk assessment, and treatment strategy formulation through the analysis of extensive and complex clinical, genetic, and imaging datasets. The amalgamation of these two domains provides substantial benefits in formulating tailored treatment plans and enhances clinical decision-making processes. Nonetheless, obstacles including data security, ethical concerns, and insufficient clinical validation hinder the extensive adoption of these technologies. In conclusion, the integration of pharmacogenetics and artificial intelligence has considerable promise for the enhanced, secure, and individualized management of cardiovascular illnesses. PubMed, Google Scholar, Scopus, and Web of Science were searched for relevant literature published from 1990 to 2026, with particular emphasis on recent and clinically relevant studies.

Platinum-based chemotherapies, including cisplatin, carboplatin, and oxaliplatin, are foundational treatments of multiple solid tumor types, inducing cell death via DNA cross-linking. Genetic markers of DNA repair have been extensively studied as determinants of response. We searched MEDLINE (2000-2026) and appraised 204 publications, contributing 212 study entries, against a four-tier evidence hierarchy, distinguishing throughout between prognostic vs. predictive biomarker claims. Defects in nucleotide excision repair and homologous recombination repair are associated with outcomes with platinum therapy across nearly every tumor type examined. Evidence supporting these markers as predictors of platinum-specific benefit is far narrower. Of 212 entries reviewed, only 10 compared platinum against an alternative regimen under randomized allocation, and five of these found no differential benefit. Homologous recombination deficiency predicts benefit from platinum-based therapy in high-grade serous ovarian carcinoma and randomized data support a predictive role for germline BRCA1/2 mutations in triple-negative breast cancer. For ERCC1, two randomized trials disagree, and no assay identified in this review distinguishes the single isoform competent to form the incision complex with XPF.

As precision medicine increasingly relies on genetic information, the development of reliable genomic point-of-care tests (POCTs) is essential. However, the number of technologies that have reached true clinical usability is limited. There is a growing need for POCTs that enable rapid, accurate analysis of human genetic variation, particularly across diverse clinical settings without requiring specialist expertise.

A precision medicine strategy is likely to be more impactful, when pharmacogenomics (PGx) guided selection of drugs and dosage wherever applicable is implemented across the globe. In regions where resources are disproportionately distributed, PGx implementation in routine clinical care can play a critical role in ensuring the optimal use of limited healthcare infrastructure. At present, PGx data from the majority of the distinct ethnic populations across Asia, Africa, and South America is limited. While international consortia, working groups, and scientific bodies have made significant contributions toward evaluating the evidence for PGx implementation, the majority of existing guidelines and recommendations are derived primarily from studies conducted in a limited number of ethnic groups. Precision Medicine Initiatives in countries like Korea, Taiwan, and Malaysia and PGx organizations like the African Institute of Biomedical Science and Technology (AiBST), Consortium for Genomics & Therapeutics in Africa (CGTA), implementation of pharmacogenetic testing for the effective care and treatment in Africa, Greater Middle East (GME) whole exome sequencing program, Ibero-American Network of Pharmacogenetics and Pharmacogenomics (RIBEF), Latin American Society of Pharmacogenomics and Personalized Medicine (SOLFAGEM), Latin American Network for Validation and Implementation of Pharmacogenomic Clinical Guidelines (RELIVAF), IndiGen initiative, Southeast Asian Pharmacogenomics Research Network (SEAPharm), are working toward consolidating the PGx presence in these regions.

Major depressive disorder (MDD) remains a significant illness worldwide, yet antidepressant therapy often follows an empirical "trial-and-error" approach. Escitalopram, a selective serotonin reuptake inhibitor is approved for MDD and generalized anxiety disorders, while aripiprazole (ARI), an atypical antipsychotic, is used as adjunctive therapy in treatment-resistant depression. Despite the broad availability of these agents, outcomes remain suboptimal. Data from the STAR*D trial indicate that only one-third of patients achieve remission after their first antidepressant trial, with many requiring multiple adjustments. This reactive approach prolongs symptom burden, increases adverse effects, and delays effective treatment.Advances in pharmacogenomics now offer a means to individualize therapy by identifying genetic polymorphisms - such as those found in CYP2C19 and CYP2D6-that influence escitalopram and aripiprazole metabolism and response. This literature review examines the evidence linking pharmacogenomic variability to antidepressant outcomes and explores how implementing genetic-guided prescribing can improve efficacy, reduce adverse effects, and enhance the pharmacists' role in mental health care.