{"doi":"10.1002/prp2.1147","title":"Experimental pharmacology in precision medicine","abstract":"Following the initial sequencing of the human genome, it was widely predicted that this knowledge would lead to transformational advances in the identification, prevention, and treatment of disease.1 The terms “Precision Medicine” and “Personalized Medicine” have been used interchangeably over the last two decades to describe almost all applications of genomic information in the development and use of medicinal interventions.2 While there are notable clinical advances that exemplify the highly effective benefit/risk profiles of precision medicine-driven approaches1, 2 the general concept of targeting specific interventions to individual patients continues to be a rich area of translational research. The 19th World Congress of Basic & Clinical Pharmacology (WCP2023) was held in Glasgow Scotland from July 2 to 7, 2023. The British Pharmacological Society and International Union of Basic and Clinical Pharmacologists (IUPHAR) hosted this important international meeting. WCP2023 was attended by more than 2000 delegates from over 80 countries. It is noteworthy that many of the WCP2023 scientific sessions, across a wide range of therapeutic areas, addressed ongoing research relevant to the current state and aspirational goals of precision medicine approaches for improving human health. During WCP2023, the symposium “Experimental Pharmacology in Precision Medicine” presented recent advances and current challenges in the application of precision medicine to diverse areas, including drug metabolism, drug–drug interactions, therapeutic drug dose monitoring and therapeutic interventions for cystic fibrosis (CF). The speakers were Drs. K.E. Thummel, B. Prasad, J. Martin, and D.N. Sheppard and the co-chairs of the symposium were Drs. A. Urbaniak and M.F. Jarvis. Consistent with the goal of highlighting research from early career investigators, the WCP2023 organizers also invited Dr. A. De Nicolò to give an oral presentation based on his submitted abstract on the metabolism of antiretroviral drugs. In the following sections of this article, each of the speakers provides a summary of their oral presentations from this symposium. While definitions vary, Precision Medicine is generally described as a medical model that utilizes molecular information (e.g., “omic” technologies) to improve the precision with which patients are stratified to better inform clinical decisions, most notably drug selection, and dosing. Significant advances in this medical domain have occurred over the past 25 years, including testing for pharmacogene variations that affect drug safety and efficacy. One approach to categorizing pharmacogenes proposed by Bill Evans and Mary Relling,3 groups them into four categories: those affecting host susceptibility to adverse response, those implicated in disease pathogenesis, those affecting drug receptor function, and those affecting drug disposition. Perhaps the greatest strides towards broad clinical implementation have come with testing for variations in genes that encode human leukocyte antigen (HLA) proteins that affect the risk of life-threatening adverse responses to abacavir, carbamazepine, and other drugs. For example, results of a recent multi-center study from Mounzer et al.,4 showed a steady, marked reduction in abacavir hypersensitivity reaction incidence between 2007 and 2015 that accompanied increased implementation of HLA-B*5701 testing during the same period. The high negative predictive value of the test likely ensured near-complete adoption of the test before abacavir administration in the treatment of HIV. Similar clinical utility and wide-spread adoption have been demonstrated for a rapidly growing list of “companion diagnostic” tests to identify specific tumor variations that predict drug-specific anti-cancer efficacy, as well as testing for mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene that inform drug selection and efficacy in the treatment of CF.5, 6 Hundreds of drug-gene","journal":"Pharmacology Research & Perspectives","year":2023,"id":366291,"datarank":0.40132193978685726,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"self_citation_contribution":0.29188652235829704,"citation_network_contribution":0.10943541742856025,"self_endowment_contribution":0.29188652235829704,"citer_contribution":0.10943541742856025,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":4,"citers_with_citation_signal":4,"citers_with_endowment":4,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9504,"is_data_producer":true,"deposit_databanks":{"ClinicalTrials.gov":["NCT04121195"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":331595,"name":"Kenneth E. Thummel","orcid":"0000-0002-7799-3739","position":1,"is_corresponding":false},{"id":1122949,"name":"Ayoade N. Alade","orcid":null,"position":2,"is_corresponding":false},{"id":252366,"name":"Allan E. Rettie","orcid":"0000-0001-9894-8753","position":3,"is_corresponding":false},{"id":304535,"name":"Bhagwat Prasad","orcid":"0000-0002-9090-0912","position":4,"is_corresponding":false},{"id":791833,"name":"Amedeo De Nicolò","orcid":"0000-0002-5973-9948","position":5,"is_corresponding":false},{"id":1122535,"name":"Jennifer Martin","orcid":"0000-0002-8614-0199","position":6,"is_corresponding":false},{"id":487280,"name":"David N. Sheppard","orcid":"0000-0001-5533-9130","position":7,"is_corresponding":false},{"id":72976,"name":"Michael F. Jarvis","orcid":"0000-0001-9558-8203","position":8,"is_corresponding":false},{"id":743281,"name":"Alicja Urbaniak","orcid":"0000-0002-0807-1263","position":0,"is_corresponding":true}],"reference_count":33,"raw_metadata":null,"created_at":"2026-07-19T01:14:55.198227Z","pmid":"37885364","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}