Cts-Clinical and Translational Science最新文献

{"title":"Promising New Anti-TIGIT Agents: Stealthy Allies in Cancer Immunotherapy","authors":"Gatadi Srikanth,&nbsp;Durga Prasad Beda,&nbsp;Ashish Ranjan Dwivedi,&nbsp;Nandan Kumar Duddukuri,&nbsp;Srinivas Nanduri,&nbsp;Jitendra Patel","doi":"10.1111/cts.70212","DOIUrl":"https://doi.org/10.1111/cts.70212","url":null,"abstract":"<p>TIGIT (T cell immunoreceptor with immunoglobulin and tyrosine-based inhibitory motif (ITIM) domain), Vstm3, and VSIG9, are newly recognized immunological checkpoints. They are prominently expressed on CD4+ and CD8+ T cells, tumor-infiltrating lymphocytes (TILs), natural killer (NK) cells, and regulatory T cells (Tregs). The TIGIT (TIGIT) protein is crucial for immune modulation since it diminishes NK cell populations and hinders T cell activity in cancer patients and experimental models. CD155, the principal ligand of TIGIT in humans, has been recognized as a pivotal target for immunotherapy owing to its interaction with TIGIT. CD155 is linked to the efficacy of anti-programmed cell death protein 1 (PD-1) therapy, even without TIGIT expression, underscoring its importance in immune checkpoint suppression. Anti-TIGIT medicines, either independently or in conjunction with anti-PD-1 treatments, have demonstrated potential in augmenting immune responses to malignancies. This review examines the structural and functional characteristics of the TIGIT protein, new developments in anti-TIGIT drugs, and their prospective use in cancer immunotherapy.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70212","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recommended Clinical Context and Patient Context Data Elements for Liquid Biopsy Data Submitted to Data Repositories and Data Commons","authors":"Robert L. Grossman,&nbsp;Jake Vinson,&nbsp;Elizabeth Bain,&nbsp;Karl Bisselou,&nbsp;Sanchi Chandan,&nbsp;Carolyn Compton,&nbsp;John Hu,&nbsp;Donald J. Johann,&nbsp;Frederick Jones,&nbsp;Gregory Jones,&nbsp;Suzanne LeBlang,&nbsp;Jerry S. H. Lee,&nbsp;Tara Lichtenberg,&nbsp;Christina M. Lockwood,&nbsp;John Lyle,&nbsp;Jean-Francois Martini,&nbsp;Jason D. Merker,&nbsp;Lauren Saunders,&nbsp;Howard Scher,&nbsp;Stella Somiari,&nbsp;Jenny You,&nbsp;Lauren C. Leiman","doi":"10.1111/cts.70227","DOIUrl":"https://doi.org/10.1111/cts.70227","url":null,"abstract":"<p>In 2020, BLOODPAC recommended 11 pre-analytical minimal technical data elements for collection and submission of liquid biopsy data to public databases. This article expands on that work by recommending 22 clinical context and 10 patient context data elements. These elements, essential for liquid biopsy data submitted to repositories like the BLOODPAC Data Commons, cover tumor characteristics, disease progression, and patient demographics, supporting biomarker validation, research, and clinical trials.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70227","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143856896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking the Mysteries of Rare Disease Drug Development: A Beginner's Guide for Clinical Pharmacologists","authors":"Mariam A. Ahmed,&nbsp;Bilal AbuAsal,&nbsp;Jeffrey S. Barrett,&nbsp;Karim Azer,&nbsp;Yuen Yi Hon,&nbsp;Salwa Albusaysi,&nbsp;Elizabeth Shang,&nbsp;Meng Wang,&nbsp;Maria Burian,&nbsp;Noha Rayad","doi":"10.1111/cts.70215","DOIUrl":"https://doi.org/10.1111/cts.70215","url":null,"abstract":"<p>Clinical pharmacologists face unique challenges when developing drugs for rare diseases. These conditions are characterized by small patient populations, diverse disease progression patterns, and a limited understanding of underlying pathophysiology. This tutorial serves as a comprehensive guide, offering practical insights and strategies to navigate its complexities. In this tutorial, we outline global regulatory incentives and resources available to support rare disease research, describe some considerations for designing a clinical development plan for rare diseases, and we highlight the role of biomarkers, real-world data, and modeling and simulations to navigate rare disease challenges. By leveraging these tools and understanding regulatory pathways, clinical pharmacologists can significantly contribute to advancing therapeutic options for rare diseases.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70215","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Care Team Attributes Predict Likelihood of Utilizing Pharmacogenomic Information During Inpatient Prescribing","authors":"Zhong Huang,&nbsp;Matthew Jack,&nbsp;Kevin J. O'Leary,&nbsp;Edith A. Nutescu,&nbsp;Thomas Chen,&nbsp;Gregory W. Ruhnke,&nbsp;David George,&nbsp;Larry K. House,&nbsp;Randall Knoebel,&nbsp;Seth Hartman,&nbsp;Anish Choksi,&nbsp;Kiang-Teck J. Yeo,&nbsp;Minoli A. Perera,&nbsp;Mark J. Ratain,&nbsp;David O. Meltzer,&nbsp;Peter H. O'Donnell","doi":"10.1111/cts.70193","DOIUrl":"https://doi.org/10.1111/cts.70193","url":null,"abstract":"<p>Medication prescribing is imperfect, and unintended side effects complicate patient care. Pharmacogenomics (PGx) is an emerging solution that associates genotypes with personalized drug-related outcomes, but it has not been widely adopted. We hypothesize that patient and provider attributes may predict and promote PGx utilization. We studied PGx using data from the ACCOuNT study, a multi-institutional prospective trial that implemented broad preemptive PGx result delivery for African American inpatients [Clinicaltrials.gov NCT03225820]. Patients were genotyped, and their PGx information was made available within an integrated informatics portal. Utilization of PGx data (defined as the active choice to review PGx information) was left to the enrolled provider's discretion. Our primary endpoint was to identify patient and care team attributes associated with PGx use. We identified statistically significant univariate predictors and utilized logistic regression to compare relative predictiveness. This study included 187 patients (60.4% female, median age 55, 75.4% treated at the University of Chicago, 17.6% at Northwestern University, and 7.0% at the University of Illinois Chicago) and 188 providers (63.8% MD, 22.3% PharmD, 6.4% PA, and 7.4% APN). In multivariate analysis, we found that the use of PGx information in a prior admission significantly predicted the use in subsequent admissions (OR 7.62, <i>p</i> &lt; 0.05). Similarly, pharmacist participation on care teams significantly predicted PGx use (OR 4.52, <i>p</i> &lt; 0.05). In the first systematic analysis of the impact of patient and care team factors on inpatient PGx clinical decision support (CDS) adoption, we found that actionable care team attributes, such as pharmacist participation or successful initial adoption measures, predict PGx CDS use.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70193","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143856711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phenoconversion of CYP3A4, CYP2C19 and CYP2D6 in Pediatrics, Adolescents and Young Adults With Lymphoma: Rationale and Design of the PEGASUS Study","authors":"Rachel Conyers,&nbsp;Tayla Stenta,&nbsp;Andrew A. Somogyi,&nbsp;Carl Kirkpatrick,&nbsp;Andreas Halman,&nbsp;Sophie Wang,&nbsp;Claire Moore,&nbsp;Dhrita Khatri,&nbsp;Elizabeth Williams,&nbsp;Roxanne Dyas,&nbsp;Tim Spelman,&nbsp;David A. Elliott,&nbsp;Amanda Gwee,&nbsp;Marliese Alexander","doi":"10.1111/cts.70209","DOIUrl":"https://doi.org/10.1111/cts.70209","url":null,"abstract":"<p>Phenoconversion is the discrepancy between genotype-predicted phenotype and clinical phenotype, due to nongenetic factors. In oncology patients, the impact of phenoconversion on drug selection, efficacy, toxicity, and treatment outcomes is unknown. This study will assess acceptability and feasibility of investigating phenoconversion using probe medications in a pediatric and adolescent and young adult (AYA) oncology population. This prospective, single-arm, single-blind, nonrandomized feasibility study, will enroll individuals aged 6–25 years with a new diagnosis of Hodgkin Lymphoma or Non-Hodgkin Lymphoma. Genotyping will be performed at baseline using whole genome sequencing or targeted panel testing. Longitudinal phenotyping will be conducted throughout the cancer treatment using exogenous oral enzyme-specific probes, specifically subtherapeutic dextromethorphan (CYP2D6) and omeprazole (CYP2C19, CYP3A4) for enzyme activity assessment. The primary outcome measure will be the proportion of patients who consent to the study and successfully complete baseline and at least two longitudinal time points with valid probe drug metabolic ratio measurements. Secondary outcomes include classification of clinical phenotypes based on probe drug metabolic ratios, probe drug safety, barriers to consent, acceptability of pharmacogenomic and phenoconversion testing, longitudinal genotype/phenotype concordance, inflammatory profiles, and patient and disease factors influencing phenoconversion. The trial has received ethics approval (2023/ETH1954) and is registered at ClinicalTrials.gov (NCT06383338). Findings will be disseminated through peer-reviewed publications and professional conferences, providing critical insights to advance the understanding of phenoconversion in oncology from pediatrics to adults. These results will help shape future research and drive the implementation of more personalized precision medicine strategies for all people with cancer.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70209","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143857137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome Wide Association Study (GWAS) Identifies Novel Genetic Loci for Second-Generation Antipsychotics (SGA)-Induced Metabolic Syndrome (MetS)","authors":"Nihal El Rouby,&nbsp;Aniwaa Owusu-Obeng,&nbsp;Michael H. Preuss,&nbsp;Simon Lee,&nbsp;Mingjian Shi,&nbsp;Rajiv Nadukuru,&nbsp;Sara L. Van Driest,&nbsp;Jonathan D. Mosley,&nbsp;Melissa DelBello","doi":"10.1111/cts.70216","DOIUrl":"https://doi.org/10.1111/cts.70216","url":null,"abstract":"<p>Second-generation antipsychotics (SGA) are widely used for treating psychiatric disorders; however, their use is associated with an increased risk of metabolic syndrome (MetS). To identify common genetic associations of SGA-induced metabolic syndrome (SGA-MetS), we conducted a genome-wide association study (GWAS) in a diverse patient population within the BioVU and Bio<i>M</i>e electronic health records (EHRs)-linked biobanks. Additionally, we performed Mendelian Randomization (MR) analysis to investigate the association between the individual metabolic parameters comprising MetS (body mass index [BMI], fasting glucose, blood pressure, HDL, and triglycerides) and SGA-MetS. The meta-analysis of European ancestry GWAS from BioVU and Bio<i>M</i>e (<i>N</i> = 9248) identified a genome-wide signal (rs61900075, <i>β</i> = −0.27, SE = 0.05, <i>p</i> = 1.6 × 10⁻⁸) on chromosome 11. Multiple associated variants met the suggestive level of association (<i>p</i> ≤ 10⁻⁵) in the <i>PELO-ITGA1</i> locus on chromosome 5 and were associated among the Hispanic Ancestry within Bio<i>M</i>e. The meta-analysis of the African Ancestry patients of BioVU and Bio<i>M</i>e (<i>N</i> = 2018) identified multiple genome-wide signals that were functionally mapped to <i>NPPC-DIS3L2</i> in chromosome 2. Finally, the inverse-variance weighted average MR (BMI: OR = 1.2, 95% CI: 1.1–1.4, <i>p</i> = 0.002) showed that genetically predicted, higher BMI was associated with an increased risk of SGA-MetS. Similar results were seen in the sensitivity analyses using the weighted median and Egger MR. This study identified novel variants for SGA-MetS and suggested a role of BMI in increasing the risk of SGA-MetS. The findings highlight the value of EHR biobanks for identifying the genetics underlying SGA-MetS. The associations in chromosome 2 and 5 will need further replication.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70216","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143857138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Patient-Derived 3D Cyst Model of Polycystic Kidney Disease That Mimics Disease Development and Responds to Repurposing Candidates","authors":"Alina Meyer,&nbsp;Bola Khalil,&nbsp;Margarita Iljin,&nbsp;Hester Bange,&nbsp;Leo S. Price,&nbsp;Natalia Dyubankova,&nbsp;Gerard J. P. van Westen,&nbsp;Herman van Vlijmen,&nbsp;Dorien J. M. Peters,&nbsp;Per Artursson","doi":"10.1111/cts.70214","DOIUrl":"https://doi.org/10.1111/cts.70214","url":null,"abstract":"<p>Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease. Its progressively expanding, fluid-filled renal cysts eventually lead to end-stage renal disease. Despite the relatively high prevalence, treatment options are currently limited to a single drug approved by the FDA and EMA. Here, we investigated human ADPKD patient-derived three-dimensional cyst cultures (3DCC) as an in vitro model for ADPKD and drug repurposing research. First, we analyzed the proteomes of 3DCC derived from healthy and diseased tissues. We then compared the protein expression profiles with those of reference tissues, mainly from the same patients. We quantified 290 proteins affecting drug disposition and proposed target proteins for drug treatment. Lastly, we investigated the functional response of the quantified target proteins after exposure to repurposing candidates in the 3DCC. Proteomic profiling of human 3DCC reflected previously reported pathophysiological alterations, including aberrant protein expression in inflammation and metabolic reprogramming. While the 3DCCs largely recapitulated the disease phenotype in vitro, drug transporter expression was reduced compared to in vivo conditions. Target proteins for proposed repurposing candidates showed similar expression in vitro and in tissues. Exposure to these repurposing candidates inhibited cyst swelling in vitro, supporting the suitability of the 3DCC for ADPKD drug screening. In summary, our results provide new insights into the ADPKD proteome and offer a starting point for further research to improve treatment options for affected individuals.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70214","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143836094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-Driven Applications in Clinical Pharmacology and Translational Science: Insights From the ASCPT 2024 AI Preconference","authors":"Mohamed H. Shahin,&nbsp;Prashant Desai,&nbsp;Nadia Terranova,&nbsp;Yuanfang Guan,&nbsp;Tomáš Helikar,&nbsp;Sebastian Lobentanzer,&nbsp;Qi Liu,&nbsp;James Lu,&nbsp;Subha Madhavan,&nbsp;Gary Mo,&nbsp;Flora T. Musuamba,&nbsp;Jagdeep T. Podichetty,&nbsp;Jie Shen,&nbsp;Lei Xie,&nbsp;Mathew Wiens,&nbsp;Cynthia J. Musante","doi":"10.1111/cts.70203","DOIUrl":"https://doi.org/10.1111/cts.70203","url":null,"abstract":"<p>Artificial intelligence (AI) is driving innovation in clinical pharmacology and translational science with tools to advance drug development, clinical trials, and patient care. This review summarizes the key takeaways from the AI preconference at the American Society for Clinical Pharmacology and Therapeutics (ASCPT) 2024 Annual Meeting in Colorado Springs, where experts from academia, industry, and regulatory bodies discussed how AI is streamlining drug discovery, dosing strategies, outcome assessment, and patient care. The theme of the preconference was centered around how AI can empower clinical pharmacologists and translational researchers to make informed decisions and translate research findings into practice. The preconference also looked at the impact of large language models in biomedical research and how these tools are democratizing data analysis and empowering researchers. The application of explainable AI in predicting drug efficacy and safety, and the ethical considerations that should be applied when integrating AI into clinical and biomedical research were also touched upon. By sharing these diverse perspectives and real-world examples, this review shows how AI can be used in clinical pharmacology and translational science to bring efficiency and accelerate drug discovery and development to address patients' unmet clinical needs.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploratory Study of Sex Differences in P-Glycoprotein Function at the Blood–Brain Barrier","authors":"Giordana Salvi de Souza,&nbsp;Wanling Liu,&nbsp;Pascalle Mossel,&nbsp;Joost F. Somsen,&nbsp;Anna L. Bartels,&nbsp;Cristiane R. G. Furini,&nbsp;Adriaan A. Lammertsma,&nbsp;Charalampos Tsoumpas,&nbsp;Gert Luurtsema","doi":"10.1111/cts.70196","DOIUrl":"https://doi.org/10.1111/cts.70196","url":null,"abstract":"<p>Permeability-glycoprotein (P-gp), a crucial efflux pump transporter encoded by the ABCB1 gene, plays a pivotal role in drug disposition at the blood–brain barrier (BBB) and is involved in the pharmacokinetics of numerous therapeutic agents. This study investigates differences in P-gp function at the BBB between males and females in a cohort of older (55+) healthy volunteers (HV) using [¹⁸F]MC225 and PET. Twenty HV (11 males and 9 females), free from medications that affect P-gp function and without a history of neurological or psychiatric disorders, underwent [¹⁸F]MC225 PET scans with manual arterial blood sampling. Tissue time-activity curves (TAC) were extracted using the Hammers maximum-probability atlas. Whole-blood TAC was derived from the internal carotid arteries, calibrated using manual arterial samples, and adjusted for the plasma-to-whole blood ratio and plasma parent fraction to obtain the image-derived input function. The volume of distribution (<i>V</i>_T) was estimated using a reversible two-tissue compartment model, yielding the parameter of interest. Statistical analysis revealed no significant differences in P-gp function between sexes, based on <i>V</i>_T values across various brain regions (Cohen's <i>d</i> &lt; 0.2). Furthermore, the arterial blood concentration, plasma parent fraction, and microparameters demonstrated no statistical differences between male and female participants. These findings suggest that P-gp function at the BBB does not exhibit substantial sex-related variability in healthy older adults (55+). For future [¹⁸F]MC225 PET studies, a mixed-sex population can serve as an appropriate age-matched control group for neurodegenerative studies. Further research is needed to explore sex-related differences in younger populations, particularly with respect to hormonal cycles.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70196","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large Language Models and Their Applications in Drug Discovery and Development: A Primer","authors":"James Lu,&nbsp;Keunwoo Choi,&nbsp;Maksim Eremeev,&nbsp;Jogarao Gobburu,&nbsp;Srijib Goswami,&nbsp;Qi Liu,&nbsp;Gary Mo,&nbsp;Cynthia J. Musante,&nbsp;Mohamed H. Shahin","doi":"10.1111/cts.70205","DOIUrl":"https://doi.org/10.1111/cts.70205","url":null,"abstract":"<p>Large language models (LLMs) have emerged as powerful tools in many fields, including clinical pharmacology and translational medicine. This paper aims to provide a comprehensive primer on the applications of LLMs to these disciplines. We will explore the fundamental concepts of LLMs, their potential applications in drug discovery and development processes ranging from facilitating target identification to aiding preclinical research and clinical trial analysis, and practical use cases such as assisting with medical writing and accelerating analytical workflows in quantitative clinical pharmacology. By the end of this paper, clinical pharmacologists and translational scientists will have a clearer understanding of how to leverage LLMs to enhance their research and development efforts.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"18 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cts.70205","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}