Pharmacogenetics is pivotal in modern HIV management, facilitating the transition from the traditional "one-size-fits-all" model toward personalized precision medicine. By analyzing how unique genetic profiles influence pharmacological responses, clinicians can maximize therapeutic efficacy while minimizing toxicities and adverse drug reactions. Given the high interindividual variability in antiretroviral drug exposure and the necessity for lifelong treatment, identifying key genetic biomarkers is essential to optimize patient safety, treatment adherence, and overall quality of life.

Cancer therapy-related cardiomyopathy (CTR-cardiomyopathy) is the leading noncancer late effect contributing to morbidity and mortality among adult survivors of childhood cancer. Anthracycline chemotherapy and thoracic radiotherapy are the primary treatment-related risk factors. However, substantial variability among similarly treated individuals highlights the role of germline genetic susceptibility. This review summarizes pharmacogenomic evidence for CTR-cardiomyopathy and the integration of genetic and clinical risk factors for individualized risk prediction. We searched PubMed through July 2026 for studies examining the molecular underpinnings and risk prediction in these survivors. Candidate gene studies identified associations across pathways involved in drug transport (ABCC1, ABCC2, SLC28A3), metabolism (CBR3), oxidative stress (SOD2, CYBA, NCF4), DNA damage response (RARG, XRCC5, MGMT), and inflammation (P2RX7). Genome-wide studies have identified additional loci, including HAS3, ancestry-specific signals (PHTF1/MAGI3, AGBL1), and a doxorubicin-specific locus (KCNK17). Despite progress, barriers to clinical implementation remain, including heterogeneous phenotype definitions, limited replication, especially in non-European populations, and lack of prospectively validated risk models. Integration of multi-omics approaches may improve detection of subclinical cardiac injury. Ultimately, combining polygenic and other omic risk scores with clinical factors and validating these models prospectively across diverse populations will be essential for advancing precision survivorship care.

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.