Therapeutic innovation & regulatory science最新文献

{"title":"Evaluation of Optimal Cut-Offs and Dichotomous Combinations for Two Biomarkers to Improve Patient Selection.","authors":"Gina D'Angelo, Di Ran, Binbing Yu","doi":"10.1007/s43441-025-00829-4","DOIUrl":"10.1007/s43441-025-00829-4","url":null,"abstract":"<p><p>Identifying the right cut-off for continuous biomarkers in clinical trials is crucial for pinpointing subgroups at higher risk or more likely to benefit from treatments. Although the literature typically focuses on single biomarkers, trials often involve multiple biomarkers. Our first aim was to compare three methods-the Youden index, point closest-to-(0,1) corner on the receiving operating characteristic curve (ER) method, and concordance probability-for finding optimal cut-offs with two biomarkers, employing both empirical and non-empirical approaches. Our second and main objective was to use our proposed logic indicator approach to extend the Youden index and evaluate whether a combination of biomarkers is an improvement over a single biomarker. The indicator approach created combinations of both or either biomarker being positive. Simulation studies revealed that non-empirical methods outperformed empirical ones, where the ER-generalized additive model (GAM) and concordance-GAM performed the best overall in terms of bias and mean squared error. We illustrated these approaches with a prostate cancer study and a simulated phase 2 lung cancer study. Results indicated similar cut-offs across methods, albeit higher with non-empirical approaches. In the lung cancer simulation, cut-off values remained relatively stable. A higher cut-off could lead to fewer candidate patients, impacting study recruitment or a diagnostic tool. These insights assist in assessing whether single or combined biomarkers are more effective for identifying patients who are more likely to respond to treatment, highlighting the significance in personalized medicine, where many treatments may not benefit \"average\" patients.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"1179-1189"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144529663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tracking a Medicine's Regulatory Risk Management Commitments Provides Better Transparency and Oversight.","authors":"Simon Ingate, Kate Bendall, Christopher Long, Kevin Fetterman, Marie Liles-Burden, Carmit Strauss","doi":"10.1007/s43441-025-00825-8","DOIUrl":"10.1007/s43441-025-00825-8","url":null,"abstract":"<p><p>Pharmaceutical companies are required to provide Risk Management Plans (RMPs) to support the marketing authorisation of medicines. These RMPs contain information on efficacy and safety, outline risks or gaps in information, and detail commitments for post-authorisation pharmacovigilance (PV) studies. These plans aim to enhance understanding of a drug's benefit-risk profile and information on risk mitigation and labelling strategies to ensure end-users are aware of the risks that are associated with the product. Per defined health authorities trigger, RMPs are updated with new data such as post-authorisation data and expanded product labels (new indications), leading to multiple versions. When specific risks require additional mitigation beyond product labelling, additional risk minimisation materials (aRMMs) may be applied to educate healthcare professionals (HCPs) and patients. In some cases, more stringent controls on drug use may be necessary. In all cases, these risk management commitments must be implemented in applicable countries where the medicine is marketed following local regulatory requirements. Implementing aRMMs necessitates the distribution of core or EU RMPs and aRMMs to local affiliates for localisation, approval by local health authorities, dissemination, and subsequent collection of effectiveness metrics. Managing multiple versions of core and local RMPs, aRMMs, and associated activities becomes a vital data management issue, requiring efficient tracking of the status of each document and locally agreed activities. This article explores developing and deploying a database-driven RMP and aRMM tracking system. It covers the determination of system requirements, the delivery of the system, and the assessment of its impact on the organisation.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"901-908"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12446136/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in the Burden for Patients Participating in Industry-Funded Clinical Trials.","authors":"Abigail Dirks, Emily Botto, Zachary Smith, Kenneth Getz","doi":"10.1007/s43441-025-00805-y","DOIUrl":"10.1007/s43441-025-00805-y","url":null,"abstract":"<p><strong>Background: </strong>During the past five years, there has been growing interest among pharmaceutical companies in incorporating patient needs and preferences early in the protocol design process. Through individual and larger group studies, the Tufts Center for the Study of Drug Development (Tufts CSDD) has collaborated with 14 pharmaceutical companies in applying a validated approach early in the protocol design process to assess patient participation burden. Data from these assessments has been aggregated to analyze trends in participation burden between 2011 and 2022.</p><p><strong>Methods: </strong>156 phase II and III protocols were analyzed.</p><p><strong>Results: </strong>Overall burden for patients to participate in phase II and III clinical trials has been rising steadily since 2011. Procedures contributing most to participation burden include patient questionnaires, lab and blood work and routine procedures conducted at each planned visit. A notable increase in the average duration of each visit per protocol was observed in large part due to the volume of procedures performed per visit. A growing proportion of procedures contributing to participation burden are those supporting supplementary, tertiary and exploration endpoints. The results of this aggregate analysis demonstrate the value of assessing patient participation burden to inform protocol design optimization.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"893-900"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144249740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-World Evidence in FDA Approvals for Labeling Expansion of Small Molecules and Biologics.","authors":"Yung-Fang Deng, Cynthia J Girman, Mary E Ritchey","doi":"10.1007/s43441-025-00816-9","DOIUrl":"10.1007/s43441-025-00816-9","url":null,"abstract":"<p><strong>Introduction: </strong>Real-world evidence (RWE) can support the evaluation of safety and efficacy for medical products, but its extent of use in labeling expansion submissions remains unclear. This study aimed to characterize the RWE used in labeling expansion or likely used, as identified through literature search, for drugs and biologics.</p><p><strong>Methods: </strong>We identified RWE used in FDA-approved labeling expansion for drug and biologic supplemental applications from January 2022 to May 2024 (Drugs@FDA), using FDA prescribing information and review documents. We also searched ClinicalTrials.gov and PubMed to identify RWE not included in the FDA approval letter and labeling but could have been incorporated into submissions by sponsors. Characteristics of the RWE were extracted and summarized.</p><p><strong>Results: </strong>Among 218 labeling expansions granted, RWE was found in FDA documents for 3 approvals and elsewhere for 52 approvals. The proportion of approvals with RWE was 23.3%, 27.7%, and 23.7% in 2022, 2023, and 2024, respectively. RWE was most commonly found in submissions for oncology (43.6%), infection (9.1%), and dermatology (7.3%). Greater use of RWE was identified in submissions for drugs (69.1%) and to expand indications (78.2%). RWE came from 88 studies, with 48.9% addressing both safety and efficacy. Most of the RWE studies were retrospective (65.9%), employed a cohort study design (87.5%), and used electronic health records (EHR) data (75.0%).</p><p><strong>Conclusion: </strong>We observed limited RWE use in granted labeling expansion, and the reason is unclear due to incomplete FDA documentation of supplemental approvals-RWE may not have been submitted, may have been submitted but determined by FDA to be of limited use, may have contributed substantively to the supplemental approval, or some combination of these across submissions. Improving accessibility and transparency in RWE's acceptability within review documents can enhance our understanding of the extent and quality of RWE used for labeling expansion.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"982-992"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12446098/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144226725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incidence and Characterization of Important Protocol Deviations in Clinical Trials in Argentina.","authors":"F Ibelli, R Bozzo, J Pezzi, I Moledous, G Ojanguren, R Iannantuono","doi":"10.1007/s43441-025-00828-5","DOIUrl":"10.1007/s43441-025-00828-5","url":null,"abstract":"","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"1171-1178"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144333928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Adoption and Use of Artificial Intelligence and Machine Learning in Clinical Development.","authors":"Mary Jo Lamberti, Maria I Florez, Hana Do, Stephanie Rosner, Timothe Menard, Carrie Nielson, Amanda Donovan, Jingjing Ye, Sathish Kaveripakam, Birgit Schoeberl, Alette R Hunt, Helen Yeardley","doi":"10.1007/s43441-025-00803-0","DOIUrl":"10.1007/s43441-025-00803-0","url":null,"abstract":"<p><strong>Background: </strong>The use of artificial intelligence (AI) and machine learning (ML) in drug discovery has been well documented, but measures of levels of adoption, investments, and efficiencies gained from its use in clinical development have not yet been developed, captured or published. AI/ML use in clinical development is expected to increase, but its impact has not yet been systematically measured until now.</p><p><strong>Methods: </strong>The Tufts Center for the Study of Drug Development conducted a global online survey among pharmaceutical and biotechnology companies, contract research organizations (CROs), and data and technology vendors servicing drug developers. The survey gathered 302 responses assessing levels of AI/ML implementation across 36 distinct clinical trial planning and design, trial execution, and regulatory submission activities. The survey collected data on US dollar investment, time savings, and challenges and opportunities of AI/ML use in clinical development.</p><p><strong>Results: </strong>Approximately one-third of the sample (36.9%) was not yet using or implementing AI/ML across 36 design and planning, execution, and regulatory submission activities; another 30.3% was beginning their AI/ML implementation (or piloting), 22.1% was partially implementing (or moving beyond pilots), and on average only 10.7% had fully implemented AI/ML (i.e., uses AI in most trials employing a repeatable process).</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"1074-1086"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144174985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of Japanese Risk Management Plans after 10 Years of Implementation: 2013-2023.","authors":"Sono Sawada, Keiko Asao, Ryohei Kobayashi, Jaclyn Bosco, Hideki Maeda","doi":"10.1007/s43441-025-00818-7","DOIUrl":"10.1007/s43441-025-00818-7","url":null,"abstract":"<p><strong>Background: </strong>A decade since Japan introduced risk management plans offers an opportunity to analyze their characteristics and support future pharmacovigilance efforts.</p><p><strong>Objectives: </strong>To describe (1) the types of post-marketing studies (PMSs) and the number of safety concerns and efficacy concerns by drug classification and (2) the distribution of important identified and important potential risks by type of safety concern.</p><p><strong>Methods: </strong>We extracted data and examined the characteristics of the Japanese risk management plans (J-RMP). The following information from J-RMPs available as of May 2023 and the corresponding package inserts of the drugs was extracted: the brand name, the active ingredient, the first submission and the last update dates of J-RMP, safety concerns with their safety specifications, efficacy concerns, the type of PMSs, and the drug classification codes.</p><p><strong>Results: </strong>A total of 637 J-RMPs were included in the analysis. The median number of safety and efficacy concerns per J-RMP was 8, with category-specific medians as follows: 4 important identified risks, 2 important potential risks, 0 important missing information, and 1 efficacy concerns. Among the 481 J-RMPs listing at least one PMS, 86.5% included only use-result surveys (primary data collection), 9.4% included only database PMSs, and 4.2% included both. Safety concerns related to neoplasms and pregnancy/birth defects were most commonly listed as important potential risks.</p><p><strong>Conclusions: </strong>Japanese PMSs more commonly rely on primary data collection. Adverse events with delayed effects tend to be classified as important potential risks. The information contained in J-RMPs is valuable for gaining insights into pharmacovigilance activities.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"1117-1128"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144216946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semantic Search of FDA Guidance Documents Using Generative AI.","authors":"Scott Proestel, Linda J B Jeng, Christopher Smith, Matthew Deady, Omar Amer, Mohamed Ahmed, Sarah Rodgers","doi":"10.1007/s43441-025-00798-8","DOIUrl":"10.1007/s43441-025-00798-8","url":null,"abstract":"<p><strong>Introduction: </strong>Generative artificial intelligence (AI) has the potential to transform and accelerate how information is accessed during the regulation of human drug and biologic products.</p><p><strong>Objectives: </strong>Determine whether a generative AI-supported application with retrieval-augmented generation (RAG) architecture can be used to correctly answer questions about the information contained in FDA guidance documents.</p><p><strong>Methods: </strong>Five large language models (LLMs): Flan-UL2, GPT-3.5 Turbo, GPT-4 Turbo, Granite, and Llama 2, were evaluated in conjunction with the RAG application Golden Retriever to assess their ability to answer questions about the information contained in clinically oriented FDA guidance documents. Models were configured to precise mode with a low temperature parameter setting to generate precise, non-creative answers, ensuring reliable clinical regulatory review guidance for users.</p><p><strong>Results: </strong>During preliminary testing, GPT-4 Turbo was the highest performing LLM. It was therefore selected for additional evaluation where it generated a correct response with additional helpful information 33.9% of the time, a correct response 35.7% of the time, a response with some of the required correct information 17.0% of the time, and a response with any incorrect information 13.4% of the time. The RAG application was able to cite the correct source document 89.2% of the time.</p><p><strong>Conclusion: </strong>The ability of the generative AI application to identify the correct guidance document and answer questions could significantly reduce the time in finding the correct answer for questions about FDA guidance documents. However, as the information in FDA guidance documents may be relied on by sponsors and FDA staff to guide important drug development decisions, the use of incorrect information could have a significantly negative impact on the drug development process. Based on our results, the correct citation documents can be used to reduce the time in finding the correct document that contains the information, but further research into the refinement of generative AI will likely be required before this tool can be relied on to answer questions about information contained in FDA guidance documents. Rephrasing questions by including additional context information, reconfiguring the embedding and chunking parameters, and other prompt engineering techniques may improve the rate of fully correct and complete responses.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"1148-1159"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12446095/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144294884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strengthening the Use of International Collaborative Regulatory Assessments and Regulatory Alignment- Implications for Global Convergence.","authors":"John H Skerritt, Mark Mayer, Jeffrey Francer","doi":"10.1007/s43441-025-00817-8","DOIUrl":"10.1007/s43441-025-00817-8","url":null,"abstract":"<p><p>There has been a significant growth in international regulatory information-sharing and work-sharing initiatives in recent years, leading to reductions in submission lag and regulatory review timeframes. However, regulatory approvals in some major countries can still lag by months or years after the first global approval, with impacts on availability of new medicines for patients. This review assesses the impact of current international collaborative initiatives and proposes some options for their advancement. It also explores the potential impact of other factors such as greater alignment and collaboration on facilitated pathways, Good Manufacturing Practice) GMP inspections on regulatory timeframes and makes suggestions for improvements of regulatory convergence, collaboration, reliance and administrative procedures. While international collaborative regulatory assessments are still relatively new, in the following years, we consider that these pathways will become even more routine and impactful, especially if they can be further adapted.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"993-1003"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12446123/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144249739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome Editing in Gynecological Oncology: The Emerging Role of CRISPR/Cas9 in Precision Cancer Therapy.","authors":"Naina Kumar","doi":"10.1007/s43441-025-00807-w","DOIUrl":"10.1007/s43441-025-00807-w","url":null,"abstract":"<p><strong>Introduction: </strong>Gynecological cancers, including cervical, ovarian, and endometrial cancers, represent a significant global health challenge due to their high prevalence and profound impact on mortality and quality of life. This narrative review explores the transformative capability of genome editing, specifically clustered regularly interspaced short palindromic repeats (CRISPR/Cas9) technology, in advancing the management of these cancers. Genome editing offers great opportunities to develop targeted therapies by enabling precise modifications of genes involved in cancer initiation, progression, and chemoresistance.</p><p><strong>Methodology: </strong>A comprehensive literature search was conducted from October 2004 to October 2024. Only peer-reviewed relevant English articles with substantial insights into the impact of genome editing on cancer therapies were considered using keywords such as \"CRISPR/Cas9,\" \"genome editing,\" \"gynecological cancers,\" and specific cancer types like \"cervical cancer,\" \"ovarian cancer,\" and \"endometrial cancer.\"</p><p><strong>Conclusion: </strong>Genome editing, particularly CRISPR/Cas9, holds substantial capacity for revolutionizing the treatment landscape of gynecological cancers by enabling highly specific, gene-targeted therapies that can overcome conventional treatment limitations such as chemoresistance and tumor recurrence. Emerging preclinical studies demonstrate the feasibility of correcting oncogenic mutations and enhancing the sensitivity of tumors to existing therapies. However, before clinical translation can be realized, critical challenges-including off-target effects, delivery system optimization, and immune responses-must be systematically addressed through rigorous research and clinical trials. Advancing these solutions will be essential for safely integrating CRISPR-based interventions into personalized medicine approaches for gynecological malignancies.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"937-948"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144111996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}