Clinical Pharmacology & Therapeutics最新文献

Cohort Study on Drug Survival and Tolerability of Adalimumab Biosimilar Transitioning: Pharmaceutical Properties Do Matter. 阿达木单抗生物仿制药过渡的药物生存期和耐受性队列研究：药物特性确实重要。

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-23 DOI: 10.1002/cpt.70098

Amy C D Peeters, Maike H M Wientjes, Wieland D Müskens, David F Ten Cate, Laura C Coates, Bart J F van den Bemt, Noortje van Herwaarden, Alfons A den Broeder

{"title":"Cohort Study on Drug Survival and Tolerability of Adalimumab Biosimilar Transitioning: Pharmaceutical Properties Do Matter.","authors":"Amy C D Peeters, Maike H M Wientjes, Wieland D Müskens, David F Ten Cate, Laura C Coates, Bart J F van den Bemt, Noortje van Herwaarden, Alfons A den Broeder","doi":"10.1002/cpt.70098","DOIUrl":"https://doi.org/10.1002/cpt.70098","url":null,"abstract":"There are no clinically meaningful differences between bio-originators (BO) and their biosimilars (BS) in safety and efficacy. However, differences in pharmaceutical properties, such as volume and excipient, can occur. This study aimed to compare outcomes between patients transitioning from the modernized adalimumab BO (0.4 mL/no citrate) to BS1 (0.8 mL/citrate) and from BS1 to BS2 (0.4 mL/no citrate) and outcomes for new starters. In this retrospective exploratory cohort study of RA, PsA, and axial SpA patients receiving adalimumab, the (adjusted) 12-month drug survival rates were compared between the transition from the modernized BO to BS1 (Cohort 1, 2021) and from BS1 to BS2 (Cohort 2, 2023) in existing users, and for adalimumab-naïve new starters of the originator and BS1 and BS2 (Cohorts 3 to 5). Subanalyses included drug survival separately for inefficacy and intolerability. In existing users, 983 patients transitioned to BS1, 1082 patients to BS2, with 659 patients in both cohorts. Drug survival rates at 12 months were 73% (95% CI: 70-76) and 90% (95% CI: 88-92), respectively (P < 0.001), adjusted hazard rate ratio (HRR) 0.32 (95% CI: 0.26-0.40) in favor of BS2. The HRR for discontinuation due to inefficacy and tolerability were 0.50 (95% CI: 0.37-0.67) and 0.20 (95% CI: 0.14-0.28), respectively, both favoring BS2. In adalimumab-naïve new starters also, better survival for the originator and BS2 were seen compared with BS1. In conclusion, adalimumab BS1 showed a significantly lower drug survival than BS2, primarily due to lower tolerability. These findings suggest that pharmaceutical differences can have an important impact on drug survival.","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145342264","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}

引用次数: 0

Erratum to "Relationship between Dose, Factor IX Activity Levels and Bleeding Probability for rIX-FP Prophylaxis in Hemophilia B: A Repeated Time-to-Event Analysis". 对“血友病B中rIX-FP预防的剂量、因子IX活性水平和出血概率之间的关系：一项重复的事件时间分析”的勘误。

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-23 DOI: 10.1002/cpt.70110

引用次数: 0

Information Bias in Electronic Health Records and Administrative Claims Data: A Targeted Review of the Recent Literature. 电子健康记录和行政索赔数据中的信息偏差：近期文献的目标回顾。

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-21 DOI: 10.1002/cpt.70105

Patrick J Arena, Yezhou Sun, Ashley Jaksa, Yu-Han Kao, Lara Yoon, Ke Meng, Arielle Marks-Anglin, Vladimir Turzhitsky

{"title":"Information Bias in Electronic Health Records and Administrative Claims Data: A Targeted Review of the Recent Literature.","authors":"Patrick J Arena, Yezhou Sun, Ashley Jaksa, Yu-Han Kao, Lara Yoon, Ke Meng, Arielle Marks-Anglin, Vladimir Turzhitsky","doi":"10.1002/cpt.70105","DOIUrl":"https://doi.org/10.1002/cpt.70105","url":null,"abstract":"Randomized clinical trials represent the primary source of evidence for regulatory and health technology assessment (HTA) decision making; however, the integration of real-world evidence (RWE) has increased in recent years. Despite its utility, RWE is often threatened by information bias, and the literature addressing measurement error in RWE remains underdeveloped. To address this gap, we conducted a targeted literature review to identify and synthesize mitigation measures for information bias in RWE generation among studies using electronic health records (EHRs) and administrative claims data. Our review covered articles published between January 2019 and May 2024 and included real-world data (RWD) investigations with a focus on information bias case studies or review articles; to increase the utility of our results, the Food and Drug Administration's guidance on assessing EHRs and medical claims data was also incorporated. Data elements were extracted and categorized to produce a comprehensive information bias mitigation framework. In total, 38 articles and guidance documents were included, primarily focusing on studies conducted in the United States (n = 25) as well as studies using EHR data (n = 31). Findings were synthesized into 15 general recommendations: six targeting study design, four addressing study variables, and five focused on statistical analyses. Prominent themes included validation, data linkage, and quantitative bias analysis. Overall, our findings underscore the diversity and complexity of the information bias in RWD literature. Our resulting framework offers practical recommendations and complements prior work, providing a foundation for future efforts to enhance the validity of RWE in regulatory/HTA decision making.","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145342337","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}

引用次数: 0

Corrigendum to "Model-Informed Once-Daily Dosing Strategy for Bedaquiline and Delamanid in Children, Adolescents and Adults with Tuberculosis". “贝达喹啉和德拉马尼在儿童、青少年和成人结核病患者中的每日一次给药策略”的修正。

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-21 DOI: 10.1002/cpt.70111

引用次数: 0

Large Language Models for Clinical Trial Protocol Assessments. 临床试验方案评估的大型语言模型。

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-21 DOI: 10.1002/cpt.70096

Euibeom Shin, Amruta Gajanan Bhat, Murali Ramanathan

{"title":"Large Language Models for Clinical Trial Protocol Assessments.","authors":"Euibeom Shin, Amruta Gajanan Bhat, Murali Ramanathan","doi":"10.1002/cpt.70096","DOIUrl":"https://doi.org/10.1002/cpt.70096","url":null,"abstract":"The purpose was to evaluate the utility of large language models (LLMs) for reviewing the statistical analysis plan (SAP) and pharmacokinetics-pharmacodynamics (PK-PD) components of clinical trial protocols. Clinical trial protocols and SAPs were obtained from clinicaltrials.gov for a testbed of 15 small-molecule drugs, biologics, and global antibiotic and public health interventions. The GPT-4o (ChatGPT) LLM was used to elicit study design attributes, relevant guidelines, and detailed SAP evaluations with prompts engineered to the persona of a regulatory expert. The SAP methodology was assessed against the Food and Drug Administration's (FDA) E9 Statistical Principles for Clinical Trials guidance. The SAP evaluation outputs were assessed in post hoc analyses with ChatGPT and Grok, based on a rubric that evaluated the accuracy of primary outcome identification, the correctness of statistical methodology, compliance with the FDA E9 guidance, and clinical interpretability. PK-PD analysis plans were assessed on the accuracy of PK-PD objectives and measures and PK analysis methods. ChatGPT accurately identified the disease, intervention, and comparator groups for all trials, as well as the study sample size for 14 out of 15 trials. The most frequently cited guidelines were the FDA's E9 guidance for SAP and the FDA Guidance for Industry: Population Pharmacokinetics for PK-PD. ChatGPT outputs of the SAP and PK-PD analysis plans were clear and organized, demonstrating a satisfactory ability to extract and summarize technical details; some limitations in contextual accuracy were observed. LLMs can be effective tools for assessing the SAP, PK-PD, and other aspects of clinical trial protocol reviews.","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145342261","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}

引用次数: 0

Unlocking Potential of Generative Large Language Models for Adverse Drug Reaction Relation Prediction in Discharge Summaries: Analysis and Strategy. 释放生成式大语言模型在出院摘要药物不良反应关系预测中的潜力：分析与策略。

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-20 DOI: 10.1002/cpt.70100

Yen Ling Koon, Hui Xing Tan, Desmond Chun Hwee Teo, Jing Wei Neo, Pei San Ang, Celine Wei Ping Loke, Mun Yee Tham, Siew Har Tan, Bee Leng Sally Soh, Pei Qin Belinda Foo, Sreemanee Raaj Dorajoo

{"title":"Unlocking Potential of Generative Large Language Models for Adverse Drug Reaction Relation Prediction in Discharge Summaries: Analysis and Strategy.","authors":"Yen Ling Koon, Hui Xing Tan, Desmond Chun Hwee Teo, Jing Wei Neo, Pei San Ang, Celine Wei Ping Loke, Mun Yee Tham, Siew Har Tan, Bee Leng Sally Soh, Pei Qin Belinda Foo, Sreemanee Raaj Dorajoo","doi":"10.1002/cpt.70100","DOIUrl":"https://doi.org/10.1002/cpt.70100","url":null,"abstract":"We present a comparative analysis of generative large language models (LLMs) for predicting causal relationships between drugs and adverse events found in text segments from discharge summaries. Despite lacking prior training for identifying related drug-adverse event pairs, generative LLMs demonstrate exceptional performance as recall-optimized models, achieving F1 scores comparable to those of fine-tuned models. Notably, on the MIMIC-Unrestricted dataset, Gemini 1.5 Pro and Llama 3.1 405B outperform our in-house fine-tuned BioM-ELECTRA-Large, with Gemini 1.5 Pro showing a 19.2% (0.724-0.863) improvement in F1 score and a 39.7% (0.675-0.943) increase in recall, while Llama 3.1 405B exhibits a 12.4% (0.724-0.814) improvement in F1 and a 40.4% (0.675-0.948) boost in recall. Additionally, we propose a hybrid approach that integrates BioM-ELECTRA-Large with generative LLMs, resulting in enhanced performance over the individual models. Our hybrid model achieves F1 score improvements ranging from 0.8% to 18.5% (0.005-0.133) over BioM-ELECTRA-Large in the validation set, primarily due to increased precision, albeit with a decrease in recall compared with the original generative LLM. Importantly, this approach yields substantial computational resource savings, as BioM-ELECTRA-Large selects only a subset of segments-ranging from 19.7% to 73.4% across our datasets-for downstream prediction by generative LLMs. By harnessing the strengths of generative LLMs as recall-optimized models and combining them with fine-tuned models, we can unlock the full potential of artificial intelligence in predicting adverse drug reaction relations, ultimately enhancing patient safety.","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145327919","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}

引用次数: 0

Clinical and Quantitative Pharmacology Considerations of mRNA Therapeutics and Vaccine Development: Bridging Translational and Platform Gaps for Enhanced Decision Making. mRNA治疗和疫苗开发的临床和定量药理学考虑：弥合翻译和平台差距以增强决策。

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-14 DOI: 10.1002/cpt.70085

Linh M Van, Nancy Chen, Kenji Miyazawa, Miao Zhang, Cornelia B Landersdorfer, Carl M Kirkpatrick, Jason Pennucci, Patrick Finn, Christine K Ward, Wei Gao

{"title":"Clinical and Quantitative Pharmacology Considerations of mRNA Therapeutics and Vaccine Development: Bridging Translational and Platform Gaps for Enhanced Decision Making.","authors":"Linh M Van, Nancy Chen, Kenji Miyazawa, Miao Zhang, Cornelia B Landersdorfer, Carl M Kirkpatrick, Jason Pennucci, Patrick Finn, Christine K Ward, Wei Gao","doi":"10.1002/cpt.70085","DOIUrl":"https://doi.org/10.1002/cpt.70085","url":null,"abstract":"Messenger RNA (mRNA) technology has emerged as a transformative modality in modern therapeutics and vaccine development, offering a versatile platform for targeted protein expression. This manuscript proposes a clinical and quantitative pharmacology framework to facilitate the development of mRNA therapies from preclinical research to clinical development. We discuss the unique pharmacological and ADME properties of mRNA and its lipid nanoparticle (LNP) delivery system, along with key bioanalytical and regulatory considerations. Specific clinical pharmacology strategies and quantitative approaches are illustrated through real-world examples in oncology, rare metabolic diseases, and vaccines. Finally, we propose a forward-looking clinical and quantitative pharmacology framework that integrates translational modeling, population modeling, physiological-based pharmacokinetic (PBPK), quantitative systems pharmacology (QSP), and Artificial Intelligence (AI)/Machine Learning (ML)-assisted predictive modeling. This integrated approach aims to build platform knowledge of mRNA-based therapies and inform decision making across the drug discovery and development lifecycle in an evolving regulatory landscape.","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145285029","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}

引用次数: 0

Patient Perceptions of and Experiences with Risk Evaluation and Mitigation Strategies. 患者对风险评估和缓解策略的认知和经验。

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-11 DOI: 10.1002/cpt.70091

Ameet Sarpatwari, Su Been Lee, Heidi Zakoul, Winta Tekle, Ariel Freedman, Shruti Belitkar, Gita A Toyserkani, Cynthia LaCivita, Esther H Zhou, Kate Heinrich Oswell, Gerald J Dal Pan, Aaron S Kesselheim

{"title":"Patient Perceptions of and Experiences with Risk Evaluation and Mitigation Strategies.","authors":"Ameet Sarpatwari, Su Been Lee, Heidi Zakoul, Winta Tekle, Ariel Freedman, Shruti Belitkar, Gita A Toyserkani, Cynthia LaCivita, Esther H Zhou, Kate Heinrich Oswell, Gerald J Dal Pan, Aaron S Kesselheim","doi":"10.1002/cpt.70091","DOIUrl":"https://doi.org/10.1002/cpt.70091","url":null,"abstract":"Risk Evaluation and Mitigation Strategy (REMS) programs mandated by the US Food and Drug Administration involve special interventions such as education or documentation of laboratory testing to ensure that the benefits of certain drugs outweigh their risks. To understand patients' and caregivers' perception of and experiences with REMS programs with elements to assure safe use, we conducted semi-structured interviews from March 2022 to July 2023 with 135 patients or caregivers of patients who had used alemtuzumab (Lemtrada), ambrisentan (Letairis), clozapine (Clozaril), isotretinoin (Accutane), lenalidomide (Revlimid), pegvaliase (Palynziq), or sodium oxybate (Xyrem/Xywav). Participants were recruited through national and regional patient volunteer registries, social media, and patient support groups. Interviews focused on patients' and caregivers' knowledge about the REMS program and REMS-related side effects, treatment initiation, medication access and adherence, pandemic policies, and overall perspectives. Among 135 participants, five key themes emerged: (1) Participants were knowledgeable about REMS-associated drug risks and requirements; (2) some participants had difficulty finding prescribers, particularly for clozapine; (3) administrative burdens related to REMS implementation were a source of frustration, with satisfaction higher when care coordination support was provided; (4) emotional and logistical challenges were identified with pregnancy- and clozapine-related testing; and (5) participants desired similar engagement around risks not covered in REMS materials. Optimizing system-level implementation can help improve REMS implementation.","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273185","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}

引用次数: 0

Ocular Complications of SGLT-2 Inhibitors, GLP-1 Receptor Agonists, and DPP-4 Inhibitors in T2DM Treatments: A Retrospective Real-World Cohort Study. 2型糖尿病治疗中SGLT-2抑制剂、GLP-1受体激动剂和DPP-4抑制剂的眼部并发症：一项回顾性现实世界队列研究

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-11 DOI: 10.1002/cpt.70087

Lee-Yuan Lin, Jie-Syuan Wu, Wei-Jung Jeng, Chen-Hsin Tsai, Jia-Wei Sun, Cheng-Hao Kuo, Fara Silvia Yuliani, Shyh-Hsiang Lin

{"title":"Ocular Complications of SGLT-2 Inhibitors, GLP-1 Receptor Agonists, and DPP-4 Inhibitors in T2DM Treatments: A Retrospective Real-World Cohort Study.","authors":"Lee-Yuan Lin, Jie-Syuan Wu, Wei-Jung Jeng, Chen-Hsin Tsai, Jia-Wei Sun, Cheng-Hao Kuo, Fara Silvia Yuliani, Shyh-Hsiang Lin","doi":"10.1002/cpt.70087","DOIUrl":"https://doi.org/10.1002/cpt.70087","url":null,"abstract":"Glaucoma is a leading cause of irreversible vision loss worldwide, and type 2 diabetes mellitus (T2DM) is increasingly recognized as a risk factor for glaucoma. This study compared the effects of 3 classes of antidiabetic drugs-sodium-glucose cotransporter 2 inhibitors (SGLT-2is), glucagon-like peptide-1 receptor agonists (GLP-1 RAs), and dipeptidyl peptidase 4 inhibitors (DPP-4is)-on ocular and systemic complications in adults with T2DM. Using the TriNetX database from 2015 to 2025, adults aged ≥ 40 years initiating SGLT-2is, GLP-1 RAs, or DPP-4is were identified and matched through propensity score methods to create three cohorts. The primary outcomes included open-angle glaucoma and ocular hypertension, with secondary outcomes of cataract, diabetic retinopathy, macular edema, and various systemic events. The matched cohorts included 68,283 patients (SGLT-2is vs. GLP-1 RAs), 69,765 patients (SGLT-2is vs. DPP-4is), and 55,760 patients (GLP-1 RAs vs. DPP-4is). Compared with GLP-1 RAs and DPP-4is, SGLT-2i use was associated with significantly lower risks of open-angle glaucoma (HR: 0.88 and 0.90), ocular hypertension (HR: 0.78 and 0.90), cataract (HR: 0.84 and 0.87), diabetic retinopathy (HR: 0.84 and 0.87), and macular edema (HR: 0.77 and 0.71). Conversely, GLP-1 RAs demonstrated stronger protective effects against systemic complications, such as diabetic nephropathy or chronic kidney disease, liver cirrhosis, dementia, cerebral infarction, and ischemic heart disease. These findings suggest that SGLT-2is may be prioritized in T2DM patients at higher risk for ocular complications, while GLP-1 RAs may be preferred when systemic risk reduction is the primary therapeutic goal.","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273133","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}

引用次数: 0

Electronic Patient File-Embedded Model-Informed Precision Dosing Compared with Physician Dosing of Tacrolimus in Kidney Transplantation. 电子患者文件嵌入模型信息的精确给药与医生给药他克莫司在肾移植中的比较。

IF 5.5 2区医学

Clinical Pharmacology & Therapeutics Pub Date : 2025-10-11 DOI: 10.1002/cpt.70090

Dirk R J Kuypers, Pieter Annaert, Borefore Jallah, Maarten Naesens, Maxine Teuns, Annouschka Laenen, Ruben Faelens

{"title":"Electronic Patient File-Embedded Model-Informed Precision Dosing Compared with Physician Dosing of Tacrolimus in Kidney Transplantation.","authors":"Dirk R J Kuypers, Pieter Annaert, Borefore Jallah, Maarten Naesens, Maxine Teuns, Annouschka Laenen, Ruben Faelens","doi":"10.1002/cpt.70090","DOIUrl":"https://doi.org/10.1002/cpt.70090","url":null,"abstract":"Model-informed precision dosing (MIPD) of tacrolimus in renal allograft recipients, evaluated in silico, demonstrated improved (time to and) probability of target concentration attainment and smaller deviations from target range. Using simulated tacrolimus concentration-time profiles, a study of 200 patients was predicted to have sufficient power to demonstrate superior performance of MIPD for these exposure end points compared with physician-based dosing. A fully automated tacrolimus MIPD application integrated in the electronic patient file was tested in 293 de novo recipients in the first 14 days after transplantation in a prospective randomized controlled clinical validation study. More patients dosed with the MIPD application reached the primary study end point of three in-target tacrolimus pre-dose trough concentrations by Day 8, compared with physician-dosed patients: 52.2% (95% CI: 45.3-59.6) vs. 35.7% (95% CI: 27.4-45.6); HR: 1.64 (95% CI: 1.10-2.43) (P = 0.015). The mean fraction of samples per patient in target during the complete study period was higher in the MIPD arm: 0.38 ± 0.14 compared with the physician-dosed arm: 0.28 ± 0.14 (P < 0.001). The mean distance from target window was significantly lower in MIPD-treated patients: 0.022 (95% CI: 0.019-0.024) vs. 0.040 (95% CI: 0.036-0.044) (P < 0.001). On 19 occasions (< 1%), MIPD tacrolimus dose suggestions were actively overruled by physicians. A fully automated MIPD application for tacrolimus in de novo renal recipients, integrated in the electronic patient file, demonstrated superior performance in achieving tacrolimus exposure targets with limited active overruling of MIPD dose executions by physicians. Automated MIPD can be tested in larger trials to evaluate the impact of dosing decision support on clinical outcomes after renal transplantation.","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273152","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}

引用次数: 0