Clinical Pharmacology & Therapeutics最新文献

{"title":"HIGHLIGHTED ARTICLES","authors":"","doi":"10.1002/cpt.3742","DOIUrl":"10.1002/cpt.3742","url":null,"abstract":"","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":"118 2","pages":"288-289"},"PeriodicalIF":5.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing Clinical Pharmacogenomics Worldwide Through the Clinical Pharmacogenetics Implementation Consortium (CPIC).","authors":"Kelly E Caudle, Michelle Whirl-Carrillo, Mary V Relling, James M Hoffman, Roseann S Donnelly, Cyrine E Haidar, Melissa S Bourque, Samantha Frear, Li Gong, Katrin Sangkuhl, Ryan Whaley, Teri E Klein","doi":"10.1002/cpt.70005","DOIUrl":"https://doi.org/10.1002/cpt.70005","url":null,"abstract":"<p><p>The Clinical Pharmacogenetics Implementation Consortium (CPIC) has advanced clinical pharmacogenomics since 2009 by developing freely available, evidence-based gene/drug guidelines. Covering 34 genes and 164 drugs, CPIC guidelines have become the global standard for translating pharmacogenomic test results into actionable prescribing decisions. This paper summarizes data highlighting CPIC's pivotal role in accelerating the global adoption of pharmacogenomics and establishing itself as the leading resource for clinical implementation. To assess CPIC's growth and impact, we analyzed member demographics, guideline characteristics, author composition, bibliometric data, database/API usage, and real-world implementation using internal tracking, external databases (Scopus, iCite), website analytics, PubMed review (2019-2024), and CPIC member surveys (2012, 2024). CPIC has 28 active guidelines with international authorship and widespread adoption, garnering over 10,000 citations and 1.4 million views. Robust implementation is evident, with 85% of PubMed-indexed pharmacogenomic implementation studies referencing CPIC guidelines. Additionally, 128 healthcare institutions and 40 commercial laboratories report using CPIC content. The CPIC API supports over 80,000 monthly queries, increasingly integrated into EHRs, including Epic's foundational genomics module. Member surveys show a shift from scientific evidence concerns to practical barriers like clinician education, reimbursement, and EHR integration. CPIC has evolved from a guideline development initiative into a global leader in pharmacogenomics implementation, fostering collaboration, standardization, and sustainable integration into diverse healthcare settings.</p>","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model-Informed Drug Development: Bang for the Buck?","authors":"Allison Dunn,&nbsp;Piet H. van der Graaf","doi":"10.1002/cpt.3744","DOIUrl":"10.1002/cpt.3744","url":null,"abstract":"&lt;p&gt;Model-Informed Drug Development (MIDD) has emerged as a foundational pillar of modern drug development, transforming how evidence is generated, integrated, and acted upon throughout the lifecycle. Once viewed as a complementary strategy, MIDD is now routinely embedded in regulatory and industry decision-making, offering powerful tools to optimize study design, inform dose selection, and support benefit–risk assessments. Its impact is both measurable, saving time and reducing costs by streamlining development, and qualitative, reflecting the critical, but less easily quantified, value of more informed labeling statements that support clinical decision-making and patient care. As MIDD continues to evolve, its influence can be understood across three core areas: (1) improving efficiency and generating cost savings, (2) mitigating risk across development programs, and (3) enhancing product labeling to inform real-world decisions. Together, these dimensions illustrate the value of MIDD not only as a technical approach, but also as a strategic framework central to the future of drug development.&lt;/p&gt;&lt;p&gt;One of the most evident and widely recognized impacts of MIDD is its ability to improve the efficiency and reduce the overall cost of drug development. By integrating quantitative models early and throughout the development process, MIDD enables more strategic decision-making, allowing sponsors to streamline programs, reduce redundancy, and target resources more effectively. For example, model-based bridging approaches can support smaller or fewer clinical trials by extrapolating existing data across populations or dosing regimens, while optimized dose selection reduces the risk of trial failure due to suboptimal exposure-response relationships. Moreover, model-based trial designs, including adaptive designs, can accelerate Investigational New Drug and New Drug Application timelines by informing dose-ranging studies, refining endpoints, or enabling innovative approaches such as dose-exposure extrapolation or the waiver of confirmatory trials in specific contexts.&lt;/p&gt;&lt;p&gt;These methodological efficiencies are translating into tangible economic value. In this issue of &lt;i&gt;Clinical Pharmacology &amp; Therapeutics&lt;/i&gt; (&lt;i&gt;CPT&lt;/i&gt;), a recent analysis by Pfizer found that the use of MIDD approaches was associated with an average reduction of 10 months in development cycle time and $5 million in development costs per program.&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; To the best of our knowledge, this is the first retrospective analysis of internal research and development (R&amp;D) programs quantifying the broader organizational value of MIDD by capturing the key development questions informed by MIDD, associated assumptions and risks, and the potential impact on cost, timelines, and decision-making. Methods based on per-subject approximations and trial size reductions were used to estimate cost and time savings, using benchmarks for study timelines and enrollment metrics acros","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":"118 2","pages":"283-287"},"PeriodicalIF":5.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cpt.3744","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing Predictions of Oral Drug Absorption, CYP3A4 Induction, and Transporter-Mediated Interactions Using a Human Primary Intestinal 3D Model (EpiIntestinal™).","authors":"Paresh P Chothe, Andrea Whitcher-Johnstone, Aniruddha Karve, Diane Ramsden, Niresh Hariparsad","doi":"10.1002/cpt.70000","DOIUrl":"https://doi.org/10.1002/cpt.70000","url":null,"abstract":"<p><p>Accurate prediction of oral drug absorption in humans is essential for early drug development; however, physiologically relevant human models are lacking. This study aims to comprehensively assess the EpiIntestinal™, a human primary intestinal 3D model, for its ability to predict oral absorption (F_a), intestinal availability (F_g), CYP3A4 induction, and drug-drug interactions (DDIs). The model showed clinically relevant expression of a key drug-metabolizing enzymes, transporters, and a nuclear receptor, pregnane X receptor (PXR). The model demonstrated a moderate improvement over Caco-2 in correlating permeability coefficients with human absorption data for a set of 18 drugs. However, PBPK modeling, using EpiIntestinal™ permeability data, accurately predicted the clinical maximum plasma concentration (C_max) of the P-gp substrates digoxin and dabigatran etexilate, unlike the significant underpredictions from Caco-2 data. PBPK modeling using intrinsic clearance and permeability data from EpiIntestinal™ accurately predicted human F_g for CYP3A4/5 substrate drugs (except buspirone). Furthermore, the model demonstrated the induction of CYP3A4 and P-gp (threefold) by a strong PXR inducer, rifampicin. Combining induction parameters of rifampicin from EpiIntestinal™ with those from the TruVivo (human hepatic model) into PBPK modeling accurately captured DDI effects on midazolam, a sensitive CYP3A4/5 substrate. Additionally, the model accurately predicted clinical outcomes of P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) mediated DDIs for ARV-471. These data underscore the potential of EpiIntestinal™ in predicting human F_a and F_g, and in quantitatively assessing CYP3A4 induction and transporter-based DDIs.</p>","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144625100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drug Loss in Japan: A Comparative Analysis with Europe for New Drugs Developed by Emerging Biopharma Companies.","authors":"Mihoko Kobayashi, Mamoru Narukawa","doi":"10.1002/cpt.70001","DOIUrl":"https://doi.org/10.1002/cpt.70001","url":null,"abstract":"<p><p>Emerging biopharma companies are key players in drug development, handling more than half of all clinical trials. Drug loss, a situation in which a drug approved in other countries has not been approved nor has its development been initiated at home, has become an issue in Japan following an increase in new drugs developed by emerging biopharma companies outside Japan. As 80% of these companies are not based in Europe, drug loss may also exist in Europe. In this study, we focused on drugs developed by emerging biopharma companies and examined the state of drug loss in Japan compared to Europe to explore the causes and solutions. Of the 98 new drugs approved in the United States between 2019 and 2023 and filed by emerging biopharma companies, drug-loss products in Japan accounted for 52.0%, which is much higher than that in Europe (19.4%). Regarding involvement in the pivotal study of new drug applications/biologics license applications in the United States, the number of drugs that included Japan in the pivotal study was quite low (16.3%), whereas those that included Europe were 73.4%. Emerging biopharma companies have been more aggressive in drug development in Europe than in Japan because of market attractiveness, language, geographical location, and country-specific regulatory requirements. Since emerging biopharma companies have a different business model from large pharmaceutical companies, taking specific measures to improve the state of drug loss in Japan is necessary.</p>","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population Pharmacokinetics and Exposure-Response Analysis of First-Line Osimertinib Plus Chemotherapy in Patients with EGFR-Mutated Advanced NSCLC.","authors":"Jincheng Yang, Damilola Olabode, Aarti Sawant-Basak, Richard Baldry, Karthick Vishwanathan, Srinivas Bachina, Alexandar Todd, Dana Ghiorghiu, Yuri Rukazenkov, Diansong Zhou, Azar Shahraz","doi":"10.1002/cpt.3759","DOIUrl":"https://doi.org/10.1002/cpt.3759","url":null,"abstract":"<p><p>Osimertinib, a third-generation, central nervous system-active epidermal growth factor receptor-tyrosine kinase inhibitor, potently and selectively inhibits epidermal growth factor receptor-tyrosine kinase inhibitor sensitizing and T790M resistance mutations, with efficacy in epidermal growth factor receptor-mutated non-small cell lung cancer. In FLAURA2 (NCT04035486), first-line osimertinib plus platinum-pemetrexed chemotherapy showed significant improvement in progression-free survival over osimertinib monotherapy in patients with epidermal growth factor receptor-mutated advanced non-small cell lung cancer. A population pharmacokinetics analysis using cumulative pharmacokinetics data from 2,196 patients across six studies (AURA, AURA2, AURA3, ADAURA, FLAURA, and FLAURA2) assessed pharmacokinetics and its variability due to intrinsic and extrinsic factors. Upon a formal covariate search, none of the covariates retained in the final model had a clinically meaningful impact on the pharmacokinetics of osimertinib and its active metabolite, AZ5104. The osimertinib exposure derived from the population pharmacokinetics model was used to evaluate the relationship between osimertinib exposure and progression-free survival, as the efficacy primary end point, in the FLAURA2 combination arm. A Cox proportional hazard analysis indicated no exposure-progression-free survival relationship for osimertinib and its metabolite; the number of pemetrexed cycles was likely to be associated with progression-free survival. No exposure-safety relationship was observed between osimertinib exposure and the occurrence of adverse events, including those leading to osimertinib dose interruption/reduction/discontinuation, and other pre-determined adverse events. These results further reinforce the benefits of the FLAURA2 clinical data that establish osimertinib 80 mg once daily plus chemotherapy as a first-line treatment for patients with epidermal growth factor receptor-mutated advanced non-small cell lung cancer.</p>","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144598992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of Proteomic Pharmacodynamic Biomarkers of IFNβ-1a Biologics to Inform Potential Utility in Biosimilar Development","authors":"Lakshmi Manasa S. Chekka,&nbsp;Deepti P. Samarth,&nbsp;Yan Guo,&nbsp;Esraa G. Mohamed,&nbsp;Erica Decker,&nbsp;Murali K. Matta,&nbsp;Qin Sun,&nbsp;William Wheeler,&nbsp;Carlos Sanabria,&nbsp;Joel Wommack,&nbsp;Joseph Gogain,&nbsp;Sarah J. Schrieber,&nbsp;Jeffry Florian,&nbsp;Yow-Ming Wang,&nbsp;David G. Strauss,&nbsp;Paula L. Hyland","doi":"10.1002/cpt.3754","DOIUrl":"10.1002/cpt.3754","url":null,"abstract":"<p>Pharmacodynamic (PD) biomarkers can support biosimilarity assessment, potentially reducing the need for comparative clinical efficacy studies. This study aimed to characterize previously identified proteomic PD biomarker candidates for Interferon beta-1a (IFNβ-1a, <i>n</i> = 248) and pegylated IFNβ-1a (pegIFNβ-1a, <i>n</i> = 528) biologics at therapeutic doses, to further evaluate the utility of proteomics in biosimilar development. Here, we reproduced the results at lower doses and characterized PD responses across multiple doses using criteria for justifying PD biomarker use in biosimilar development. We analyzed candidate proteins from longitudinal proteomics data (SomaScan™ Assay v4.1) from 48 healthy subjects administered intermediate or low doses of IFNβ-1a (15, 7.5 μg) or pegIFNβ-1a (62.5, 31.25 μg) in an FDA-sponsored study, alongside previously published therapeutic dose and placebo data. EDTA plasma samples were collected at 0, 0.125, 0.33, 0.67, 1.33, 2, 3, 4, 5, 6 days and at 9, 13 days additionally for pegIFNβ-1a. Prioritization criteria included significant differential expression at the intermediate dose vs. placebo, ≥20% response difference from placebo, significant baseline-adjusted area under the effect curve (AUEC) and a monotonic dose–response relationship across all doses. Among the candidates, 165 and 323 were differentially expressed at intermediate doses of IFNβ-1a and pegIFNβ-1a respectively. Nine PD biomarkers, including C-X-C motif chemokine 11 (I-TAC), Lymphocyte activation gene 3 protein (LAG3), and Granulins (GRN), were prioritized as common to both biologics. Most candidates followed the <i>E</i>_max dose–response model. I-TAC showed the strongest response, and LAG-3 showed the least variability in AUEC. Our study identified several suitable plasma PD biomarkers for IFNβ-1a and pegIFNβ-1a biologics with potential utility in biosimilar development programs.</p>","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":"118 4","pages":"935-945"},"PeriodicalIF":5.5,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ascpt.onlinelibrary.wiley.com/doi/epdf/10.1002/cpt.3754","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144558623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Navigating the Real World: A Scoping Review of Structured Frameworks to Effectively Identify, Evaluate, and Select Real-World Data Sources for Fit-for-Purpose Studies","authors":"Sonia Zebachi,&nbsp;Julien Tanniou,&nbsp;Elisabeth Bakker,&nbsp;Sieta T. de Vries,&nbsp;Rossella Di Bidino,&nbsp;Entela Xoxi,&nbsp;Anna Glaser,&nbsp;Gianluigi Savarese,&nbsp;Jan Hillert,&nbsp;Peter G. M. Mol,&nbsp;Kelly Plueschke,&nbsp;Billy Amzal,&nbsp;Ghinwa Y. Hayek,&nbsp;Jeverson Moreira","doi":"10.1002/cpt.3746","DOIUrl":"10.1002/cpt.3746","url":null,"abstract":"<p>The potential of real-world data (RWD), particularly from patient registries, has been increasingly recognized over the last decade by academia, regulators, and health technology assessment (HTA) bodies for its role in assessing a product's effectiveness and supporting regulatory submissions. The selection of an appropriate RWD source is of primary concern, since the success of regulatory processes depends on the quality and relevance of the data. In more recent years, EMA and FDA have released extensive guidance on the use of RWD to produce evidence. Simultaneously, public and private research institutions have proposed structured frameworks developed to guide stakeholders in evaluating and selecting “fit-for-purpose” RWD sources. This scoping review provides an overview of these structured frameworks, identifying nine key tools, including the Registry Evaluation and Quality Standards Tool (REQueST) and the Structured Process to Identify Fit-For-Purpose Data (SPIFD2). Each framework is briefly described, followed by a comparative analysis of the criteria they assess. These criteria relate to dimensions such as study design, data reliability, data relevance, ethical considerations, and practical factors such as cost and feasibility. Our findings indicate that while these frameworks offer robust tools for ensuring the suitability of RWD sources, each has unique strengths and limitations depending on the specific context of use. By providing a comprehensive understanding of these frameworks, this review aims to assist stakeholders in identifying and/or evaluating and/or selecting the most appropriate RWD sources for generating high-quality evidence for regulatory and HTA purposes.</p>","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":"118 4","pages":"894-905"},"PeriodicalIF":5.5,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12439006/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144551514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to “Optimizing Hydroxychloroquine Dosing for Patients With COVID-19: An Integrative Modeling Approach for Effective Drug Repurposing”","authors":"","doi":"10.1002/cpt.3755","DOIUrl":"10.1002/cpt.3755","url":null,"abstract":"&lt;p&gt;Garcia-Cremades, M., Solans, B.P., Hughes, E., Ernest, J.P., Wallender, E., Aweeka, F., Luetkemeyer, A.F., &amp; Savic, R.M. Optimizing hydroxychloroquine dosing for patients with COVID-19: an integrative modeling approach for effective drug repurposing. Clin. Pharmacol. Ther. 108, 253–263 (2020). https://doi.org/10.1002/cpt.1856.&lt;/p&gt;&lt;p&gt;Following the retraction of the publication “Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial” by Gautret et al. [&lt;span&gt;1&lt;/span&gt;], we write to report a correction to our article in &lt;i&gt;Clinical Pharmacology and Therapeutics&lt;/i&gt;, “Optimizing hydroxychloroquine dosing for patients with COVID-19: An integrative modeling approach for effective drug repurposing” [&lt;span&gt;2&lt;/span&gt;]. The Gautret et al. [&lt;span&gt;1&lt;/span&gt;] publication was retracted on the basis that methodological flaws were identified, including issues with study design, data handling, and statistical analysis, which ultimately compromised the validity and reliability of the results. Given that our article relied in part on the findings of Gautret et al. [&lt;span&gt;1&lt;/span&gt;], we have carefully reviewed our analyses to ensure the integrity and accuracy of our conclusions.&lt;/p&gt;&lt;p&gt;Our publication synthesized a comprehensive body of knowledge to develop model-informed dosing recommendations for hydroxychloroquine. We integrated emerging data from preclinical evaluations and in vitro antiviral testing—largely derived from early COVID-19 studies—with the extensive pharmacological knowledge accumulated over decades of hydroxychloroquine use in malaria. This included published clinical population pharmacokinetic models, exposure-efficacy relationships, and exposure-safety data. We used two independent studies to compare results, evaluate the variability of COVID-19 natural history and effect on drug efficacy, and to validate our modeling outcomes. By integrating this totality of evidence, we were able to propose informed dosing regimens tailored to the COVID-19 context. Our analyses determined that hydroxychloroquine doses of 400 mg or below twice daily for five or more days were predicted to have no effect on viral loads and reduction of the proportion of patients with detectable SARS-CoV-2 infection. However, we also found that doses exceeding 600 mg twice daily were predicted to result in clinically concerning QTc prolongation. We acknowledged that this finding had potential safety implications that would require careful prospective assessment.&lt;/p&gt;&lt;p&gt;We estimated a clinical EC50 value of 5.3 μM using data from the Gautret et al publication to simulate outcomes in Figure 6 [&lt;span&gt;2&lt;/span&gt;] The in vivo EC50 value was in the range of the in vitro EC50s reported in Figure 4. The geometric mean of the in vitro EC50s was only slightly higher (9.95 μM versus 5.3 μM), and if we replaced this value in the simulations of Figure 6, we would come to similar conclusions.&lt;/p&gt;&lt;p&gt;A later trial done in Brazil teste","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":"118 3","pages":"744-745"},"PeriodicalIF":5.5,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ascpt.onlinelibrary.wiley.com/doi/epdf/10.1002/cpt.3755","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144525710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of First-of-Its-Kind Patient-Facing Pharmacogenetics Tool on Dosing Decisions and Treatment Outcomes","authors":"Youngwoo Cho,&nbsp;Sami Elahi,&nbsp;Matthew M. Jack,&nbsp;John Campbell,&nbsp;Emily Smith,&nbsp;Randall W. Knoebel,&nbsp;David George,&nbsp;Larry House,&nbsp;Kiang-Teck J. Yeo,&nbsp;Theodore Karrison,&nbsp;Samuel L. Volchenboum,&nbsp;David O. Meltzer,&nbsp;Russell Z. Szmulewitz,&nbsp;Everett E. Vokes,&nbsp;Mark J. Ratain,&nbsp;Peter H. O'Donnell","doi":"10.1002/cpt.3747","DOIUrl":"10.1002/cpt.3747","url":null,"abstract":"<p>Germline pharmacogenetics (PGx) is increasingly used to tailor medication selection/dosing. However, existing systems primarily communicate PGx results to providers, limiting direct patient engagement. To address this, we developed YourPGx Oncology, an innovative patient-facing portal that delivers multi-gene PGx results (<i>CYP2D6</i>, <i>UGT1A1</i>, <i>DPYD</i>) through 33 unique, patient-friendly summaries. The utility of this tool was prospectively evaluated in an oncology population, where these pharmacogenes impact high-stakes treatments. Patients enrolled in the PhOCus study (NCT04541381) participated in single-session evaluations of the tool in-person or via videoconference, with a pharmacist available for questions and administering pre- and post-surveys that assessed educational impact. Each patient viewed their own previously obtained PGx results. Of 190 eligible patients, 70 responded to solicitations via email, phone, and in-person, of whom 51 (73%) completed an observed session and completed surveys. Patients spent a median of 13.4 minutes (range 8.1–21.0) navigating YourPGx Oncology. After portal interaction, patients' ability to identify individual efficacy and safety estimates for chemotherapies and pain medications significantly improved, with the proportion accurately recognizing PGx-informed drug efficacy likelihoods rising from 32% to 72% (Odds Ratio [OR] = 5.8 for the shift from discordant to concordant efficacy knowledge, <i>P</i> &lt; 0.001), and PGx-related toxicity recognition increasing from 31% to 57% (OR = 3.2, <i>P</i> = 0.01). Our findings show that a customized patient-facing PGx results portal enhances patient understanding of individual medication efficacy and toxicity likelihoods, highlighting the potential key role of direct-to-patient PGx tools to facilitate optimized treatment-informed care and promote genetically guided shared decision-making.</p>","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":"118 4","pages":"906-916"},"PeriodicalIF":5.5,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12439013/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144525711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}