References

Abou Ali, Mohamad, Fadi Dornaika, and Jinan Charafeddine. 2026. “Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions.” Artificial Intelligence Review 59: 11. https://doi.org/10.1007/s10462-025-11422-4.
Amershi, Saleema, Dan Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, et al. 2019. “Guidelines for Human-AI Interaction.” In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–13. https://doi.org/10.1145/3290605.3300233.
Anthropic. 2025. “Model Context Protocol: Introduction.” https://modelcontextprotocol.io/docs/getting-started/intro.
Armitage, Peter. 1954. “Sequential Tests in Prophylactic and Therapeutic Trials.” Quarterly Journal of Medicine 23 (91): 255–74.
———. 1960. Sequential Medical Trials. Oxford: Blackwell Scientific Publications.
Association of Clinical Research Organizations. 2024. “ACRO Risk-Based Quality Management Resources.” https://www.acrohealth.org/initiatives-hub/risk-based-quality-management/.
Atkinson, A. C. 2002. “The Comparison of Designs for Sequential Clinical Trials with Covariate Information.” Journal of the Royal Statistical Society: Series A 165 (2): 349–73. https://doi.org/10.1111/1467-985X.00564.
Battisti, William P., Elizabeth Wager, Lara Baltzer, Debra Bridges, Anna Cairns, Christopher I. Carswell, Leslie Citrome, et al. 2022. “Good Publication Practice (GPP) Guidelines for Company-Sponsored Biomedical Research: 2022 Update.” Annals of Internal Medicine. https://doi.org/10.7326/M22-1460.
Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–23. https://doi.org/10.1145/3442188.3445922.
Berkeley Artificial Intelligence Research. 2024. “The Shift from Models to Compound AI Systems.” https://bair.berkeley.edu/blog/2024/02/18/compound-ai-systems/.
Berry Consultants. 2024a. “Administrative Analyses for Funding Decisions in Adaptive Clinical Trials.” https://www.berryconsultants.com/resource/administrative-analyses-for-funding-decisions-in-adaptive-clinical-trials.
———. 2024b. “Berry Consultants Provides Comments on the Draft ICH E20 Harmonised Guideline.” https://www.berryconsultants.com/resource/berry-consultants-provides-comments-on-the-draft-ich-e20-harmonised-guideline.
———. 2024c. “The Rumored Shift to a One-Trial Standard for FDA Substantial Evidence.” https://www.berryconsultants.com/resource/the-rumored-shift-to-a-one-trial-standard-for-fda-substantial-evidence.
Berry, Donald A. 1989. “Monitoring Accumulating Data in a Clinical Trial.” Biometrics 45 (4): 1197–1211. https://doi.org/10.2307/2531771.
———. 2012. “Adaptive Clinical Trials in Oncology.” Nature Reviews Clinical Oncology 9 (4): 199–207. https://doi.org/10.1038/nrclinonc.2011.165.
———. 2025. “Adaptive Bayesian Clinical Trials: The Past, Present, and Future of Clinical Research.” Journal of Clinical Medicine 14 (15): 5267. https://doi.org/10.3390/jcm14155267.
Berry, Scott M., Bradley P. Carlin, J. Jack Lee, and Peter Müller. 2010. Bayesian Adaptive Methods for Clinical Trials. Chapman & Hall/CRC Biostatistics Series. Boca Raton, FL: CRC Press. https://doi.org/10.1201/EBK1439825488.
Biotechnology Innovation Organization, QLS Advisors, and Informa Pharma Intelligence. 2021. “Clinical Development Success Rates 2011-2020.” https://go.bio.org/rs/490-EHZ-999/images/ClinicalDevelopmentSuccessRates2011_2020.pdf.
Cappello, Franck, Sandeep Madireddy, Robert Underwood, Neil Getty, Nicholas Lee-Ping Chia, Nesar Ramachandra, et al. 2025. “EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants.” arXiv Preprint arXiv:2502.20309. https://arxiv.org/abs/2502.20309.
Cemri, Mert, Melissa Z. Pan, Shuyi Yang, Lakshya A. Agrawal, Bhavya Chopra, Rishabh Tiwari, Kurt Keutzer, et al. 2025. “Why Do Multi-Agent LLM Systems Fail?” arXiv Preprint arXiv:2503.13657. https://arxiv.org/abs/2503.13657.
Chan, Jun Shern, Neil Chowdhury, Oliver Jaffe, James Aung, Dane Sherburn, Evan Mays, Giulio Starace, et al. 2024. “MLE-Bench: Evaluating Machine Learning Agents on Machine Learning Engineering.” arXiv Preprint arXiv:2410.07095. https://arxiv.org/abs/2410.07095.
Cheng, Yuheng, Ceyao Zhang, Zhengwen Zhang, Xiangrui Meng, Sirui Hong, Wenhao Li, Zihao Wang, et al. 2024. “Exploring Large Language Model Based Intelligent Agents: Definitions, Methods, and Prospects.” arXiv Preprint arXiv:2401.03428. https://arxiv.org/abs/2401.03428.
Clinical Leader. 2024. “Best Practices for Randomization and Trial Supply Management (RTSM).” https://www.clinicalleader.com/doc/best-practices-for-randomization-and-trial-supply-management-rtsm-0001.
Coart, Elisabeth, Lien Bamps, Elisabeth Quinaux, and Tomasz Burzykowski. 2023. “Minimization in Randomized Clinical Trials.” Statistics in Medicine 42 (28): 5285–5311. https://doi.org/10.1002/sim.9916.
Collins, Gary S. et al. 2024. “TRIPOD+AI Statement: Updated Guidance for Reporting Clinical Prediction Models That Use Regression or Machine Learning Methods.” BMJ. https://www.bmj.com/content/385/bmj-2023-078378.
Cox, D. R. 1958. Planning of Experiments. New York: John Wiley & Sons.
———. 2009. “Randomization in the Design of Experiments.” International Statistical Review 77 (3): 415–29. https://doi.org/10.1111/j.1751-5823.2009.00084.x.
Deloitte Centre for Health Solutions. 2025. “Measuring the Return from Pharmaceutical Innovation.” https://www2.deloitte.com/us/en/pages/life-sciences-and-health-care/articles/measuring-return-from-pharmaceutical-innovation.html.
DiMasi, Joseph A., Henry G. Grabowski, and Ronald W. Hansen. 2016. “Innovation in the Pharmaceutical Industry: New Estimates of r&d Costs.” Journal of Health Economics 47: 20–33. https://doi.org/10.1016/j.jhealeco.2016.01.012.
Douze, Matthijs, Alexandr Guzhva, Chengqi Deng, Jeff Johnson, Gergely Szilvasy, Pierre-Emmanuel Mazaré, Maria Lomeli, Lucas Hosseini, and Hervé Jégou. 2024. “The Faiss Library.” arXiv Preprint arXiv:2401.08281. https://arxiv.org/abs/2401.08281.
Duke Center for Virtual Imaging Trials. 2024. “Virtual Imaging Trials in Medicine 2024 Summit.” https://cvit.duke.edu/vitm24/.
Dyck, Christopher H. van, Chad J. Swanson, Paul Aisen, Randall J. Bateman, Christopher Chen, Michelle Gee, Michio Kanekiyo, et al. 2023. “Lecanemab in Early Alzheimer’s Disease.” New England Journal of Medicine 388 (1): 9–21. https://doi.org/10.1056/NEJMoa2212948.
Efron, Bradley. 1971. “Forcing a Sequential Experiment to Be Balanced.” Biometrika 58 (3): 403–17. https://doi.org/10.1093/biomet/58.3.403.
Emanuel, Ezekiel J., David Wendler, and Christine Grady. 2000. “What Makes Clinical Research Ethical?” JAMA 283 (20): 2701–11. https://doi.org/10.1001/jama.283.20.2701.
Epperson, Will, Gagan Bansal, Victor Dibia, Adam Fourney, Jack Gerrits, Erkang Zhu, and Saleema Amershi. 2025. “Interactive Debugging and Steering of Multi-Agent AI Systems.” arXiv Preprint arXiv:2503.02068. https://arxiv.org/abs/2503.02068.
European Medicines Agency. 2006. “Guideline on Clinical Trials in Small Populations.” https://www.ema.europa.eu/en/clinical-trials-small-populations-scientific-guideline.
———. 2022. “Clinical Trials Regulation (EU) No 536/2014 and Clinical Trials Information System (CTIS).” https://www.ema.europa.eu/en/human-regulatory/research-development/clinical-trials/clinical-trials-regulation.
———. 2024a. “ICH E6(R3) Good Clinical Practice Guidelines.” https://www.ema.europa.eu/en/ich-e6-good-clinical-practice-scientific-guideline.
———. 2024b. “Reflection Paper on the Use of Artificial Intelligence (AI) in the Lifecycle of Medicinal Products.” https://www.ema.europa.eu/en/documents/scientific-guideline/reflection-paper-use-artificial-intelligence-ai-medicinal-product-lifecycle_en.pdf.
Faro Health. 2024. “Faro Health: AI-Powered Protocol Design.” https://farohealth.com.
Fortune Business Insights. 2024. “AI in Clinical Trials Market Size, Share & Industry Analysis.” https://www.fortunebusinessinsights.com/ai-in-clinical-trials-market-114081.
Gebru, Timnit, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, and Kate Crawford. 2021. “Datasheets for Datasets.” Communications of the ACM 64 (12): 86–92. https://doi.org/10.1145/3458723.
Getz, Kenneth A. 2014. “Protocol Design and Performance Benchmarks by Phase and by Oncology and Rare Disease Subgroups.” https://link.springer.com/article/10.1007/s43441-022-00438-x.
Glickman, Seth W., John G. McHutchison, Eric D. Peterson, Charles B. Cairns, Robert A. Harrington, Robert M. Califf, and Kevin A. Schulman. 2009. “Ethical and Scientific Implications of the Globalization of Clinical Research.” New England Journal of Medicine 360 (8): 816–23. https://doi.org/10.1056/NEJMsb0803929.
Goodman, Steven. 2008. “A Dirty Dozen: Twelve P-Value Misconceptions.” Seminars in Hematology 45 (3): 135–40. https://doi.org/10.1053/j.seminhematol.2008.04.003.
Grand View Research. 2024. “Contract Research Organization Market Size Report.” https://www.grandviewresearch.com/industry-analysis/contract-research-organization-market.
———. 2025. “Clinical Trials Support Software Solutions Market Size, Share & Trends Analysis Report.” https://www.grandviewresearch.com/industry-analysis/clinical-trials-support-software-solutions-market-report.
Granholm, Anders, Aksel Karl Georg Jensen, Theis Lange, Anders Perner, Morten Hylander Møller, and Benjamin Skov Kaas-Hansen. 2025. “Designing and Evaluating Bayesian Advanced Adaptive Randomised Clinical Trials: A Practical Guide.” Pharmaceutical Statistics 24 (6). https://doi.org/10.1002/pst.70042.
H1. 2024. “H1: Healthcare Provider Intelligence Platform.” https://h1.co.
Han, Kiki, Franck Le Deu, Fangning Zhang, and Josie Zhou. 2021. “The Dawn of China Biopharma Innovation.” https://www.mckinsey.com/industries/life-sciences/our-insights/the-dawn-of-china-biopharma-innovation.
Harris Interactive. 2004. “Most Physicians Do Not Participate in Clinical Trials Because of Lack of Opportunity, Time, Personnel Support and Resources.” https://www.biospace.com/b-harris-interactive-b-release-most-physicians-do-not-participate-in-clinical-trials-because-of-lack-of-opportunity-time-personnel-support-and-r.
Health Level Seven International. 2024. “HL7 FHIR Bulk Data Access (Flat FHIR).” https://hl7.org/fhir/uv/bulkdata/.
Hripcsak, George, and David J. Albers. 2013. “Next-Generation Phenotyping of Electronic Health Records.” Journal of the American Medical Informatics Association. https://pmc.ncbi.nlm.nih.gov/articles/PMC3555337/.
Hripcsak, George, Jon D. Duke, Nigam H. Shah, Christian G. Reich, Vojtech Huser, Martijn J. Schuemie, Marc A. Suchard, et al. 2015. “Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers.” Studies in Health Technology and Informatics. https://pmc.ncbi.nlm.nih.gov/articles/PMC4815923/.
Hu, Feifang, and William F. Rosenberger. 2006. The Theory of Response-Adaptive Randomization in Clinical Trials. Hoboken, NJ: John Wiley & Sons. https://doi.org/10.1002/047005588X.
International Council for Harmonisation. 1994. “ICH Harmonised Tripartite Guideline: The Extent of Population Exposure to Assess Clinical Safety for Drugs Intended for Long-Term Treatment of Non-Life-Threatening Conditions E1.” https://database.ich.org/sites/default/files/E1_Guideline.pdf.
———. 1995. “ICH Harmonised Tripartite Guideline: Structure and Content of Clinical Study Reports E3.” https://database.ich.org/sites/default/files/E3_Guideline.pdf.
———. 1996. “ICH Harmonised Tripartite Guideline: Guideline for Good Clinical Practice E6(R1).” https://www.ema.europa.eu/en/documents/scientific-guideline/ich-e6-r1-guideline-good-clinical-practice_en.pdf.
———. 1998a. “ICH Harmonised Tripartite Guideline: Ethnic Factors in the Acceptability of Foreign Clinical Data E5(R1).” https://www.ema.europa.eu/en/documents/scientific-guideline/ich-e-5-r1-ethnic-factors-acceptability-foreign-clinical-data-step-5_en.pdf.
———. 1998b. “ICH Harmonised Tripartite Guideline: Statistical Principles for Clinical Trials E9.” https://database.ich.org/sites/default/files/E9_Guideline.pdf.
———. 2016a. ICH E6(R2): Integrated Addendum to ICH E6(R1) - Guideline for Good Clinical Practice.” https://database.ich.org/sites/default/files/E6_R2_Addendum.pdf.
———. 2016b. “ICH M4: Organisation of the Common Technical Document for the Registration of Pharmaceuticals for Human Use.” https://www.ich.org/page/ctd.
———. 2017. “ICH Harmonised Guideline: General Principles for Planning and Design of Multi-Regional Clinical Trials E17.” https://www.ema.europa.eu/en/documents/scientific-guideline/ich-guideline-e17-general-principles-planning-and-design-multi-regional-clinical-trials-step-5-first-version_en.pdf.
———. 2019. ICH E9(R1): Addendum on Estimands and Sensitivity Analysis in Clinical Trials to the Guideline on Statistical Principles for Clinical Trials.” https://database.ich.org/sites/default/files/E9-R1_Step4_Guideline_2019_1203.pdf.
———. 2021. ICH E8(R1): General Considerations for Clinical Studies.” https://database.ich.org/sites/default/files/ICH_E8-R1_Guideline_Step4_2021_1006.pdf.
———. 2024. “ICH E20: Adaptive Clinical Trials.” https://www.ema.europa.eu/en/ich-e20-adaptive-designs-clinical-trials-scientific-guideline.
———. 2025. ICH E6(R3): Guideline for Good Clinical Practice (GCP).” https://database.ich.org/sites/default/files/ICH_E6%28R3%29_Step4_FinalGuideline_2025_0106.pdf.
International Data Corporation. 2024. “IDC MarketScape: Worldwide Cloud-Based Clinical Trials Platforms.” https://www.idc.com/getdoc.jsp?containerId=US51722224.
IQVIA. 2024a. “Decentralized Clinical Trials Solutions.” https://www.iqvia.com/solutions/research-and-development/decentralized-trials.
———. 2024b. “IQVIA Intelligent eTMF.” https://www.iqvia.com/library/fact-sheets/iqvia-intelligent-etmf.
IQVIA Institute for Human Data Science. 2024a. “Global Trends in r&d 2024: Activity, Productivity, and Enablers.” https://www.iqvia.com/insights/the-iqvia-institute/reports-and-publications/reports/global-trends-in-r-and-d-2024-activity-productivity-and-enablers.
———. 2024b. “Global Use of Medicines 2024: Outlook to 2028.” https://www.iqvia.com/insights/the-iqvia-institute/reports-and-publications/reports/the-global-use-of-medicines-2024-outlook-to-2028.
———. 2025. “Global Trends in r&d 2025.” https://iqvia.com/insights/the-iqvia-institute/reports-and-publications/reports/global-trends-in-r-and-d-2025.
Kapoor, Sayash, Benedikt Stroebl, Zachary S. Siegel, Nitya Nadgir, and Arvind Narayanan. 2024. “AI Agents That Matter.” arXiv Preprint arXiv:2407.01502. https://arxiv.org/abs/2407.01502.
Khattab, Omar, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, et al. 2023. “DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines.” arXiv Preprint arXiv:2310.03714. https://arxiv.org/abs/2310.03714.
Kim, Edward S., Roy S. Herbst, Ignacio I. Wistuba, J. Jack Lee, George R. Blumenschein, Anne Tsao, David J. Stewart, et al. 2011. “The BATTLE Trial: Personalizing Therapy for Lung Cancer.” Cancer Discovery 1 (1): 44–53. https://doi.org/10.1158/2159-8274.CD-10-0010.
Lamberti, Mary Jo, Abigail Dirks, Nicholas Kikuchi, Neha Patel Cervantes, and Kenneth Getz. 2024a. “Benchmarking Site Activation and Patient Enrollment.” Therapeutic Innovation & Regulatory Science 58 (4): 696–703. https://doi.org/10.1007/s43441-024-00638-1.
———. 2024b. “Benchmarking Site Activation and Patient Enrollment.” Therapeutic Innovation & Regulatory Science 58 (4): 696–703. https://doi.org/10.1007/s43441-024-00638-1.
Laranjo, Liliana, Adam G. Dunn, Huong Ly Tong, A. Baki Kocaballi, Jessica Chen, Rabia Bashir, Didi Surian, et al. 2018. “Conversational Agents in Healthcare: A Systematic Review.” Journal of the American Medical Informatics Association. https://pmc.ncbi.nlm.nih.gov/articles/PMC6118869/.
Laubenbacher, Reinhard, James P. Sluka, and James A. Glazier. 2021. “Using Digital Twins in Viral Infection.” Science 371 (6534): 1105–6. https://doi.org/10.1126/science.abf3370.
Lewis, Patrick, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, et al. 2020. “Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.” Advances in Neural Information Processing Systems 33: 9459–74. https://arxiv.org/abs/2005.11401.
Lin, Yunzhi, Mumu Zhu, and Zheng Su. 2015. “The Pursuit of Balance: An Overview of Covariate-Adaptive Randomization Techniques in Clinical Trials.” Contemporary Clinical Trials 45: 21–25. https://doi.org/10.1016/j.cct.2015.07.011.
Liu, Xiaoxuan et al. 2020. “CONSORT-AI Extension: Reporting Guidelines for Clinical Trials Evaluating Artificial Intelligence Interventions.” BMJ. https://www.bmj.com/content/370/bmj.m3164.
Ma, Wei, Peng Li, Li-Xin Zhang, and Feifang Hu. 2022. “A New and Unified Family of Covariate Adaptive Randomization Procedures and Their Properties.” Journal of the American Statistical Association 117 (539): 1503–19. https://doi.org/10.1080/01621459.2022.2102986.
Mandel, Joshua C., David A. Kreda, Kenneth D. Mandl, Isaac S. Kohane, and Rachel B. Ramoni. 2016. “SMART on FHIR: A Standards-Based, Interoperable Apps Platform for Electronic Health Records.” Journal of the American Medical Informatics Association. https://pmc.ncbi.nlm.nih.gov/articles/PMC4997036/.
Marion, Joe, Elizabeth Lorenzi, Cora Allen-Savietta, Scott Berry, and Kert Viele. 2025. “Predictive Probabilities Made Simple: A Fast and Accurate Method for Clinical Trial Decision-Making.” Statistics in Medicine 44 (13-14): e70120. https://doi.org/10.1002/sim.70120.
MarketsandMarkets. 2024. “Electronic Trial Master File System Market.” https://www.marketsandmarkets.com/Market-Reports/electronic-trial-master-file-system-market-94357456.html.
McKinsey & Company. 2024. “How Artificial Intelligence Can Power Clinical Development.” https://www.mckinsey.com/industries/life-sciences/our-insights/how-artificial-intelligence-can-power-clinical-development.
Medable. 2024a. “Medable Releases New AI Agent to Automate Trial Master File Processing.” https://www.biopharmatrend.com/news/medable-releases-new-ai-agent-to-automate-trial-master-file-processing-1447/.
———. 2024b. “Medable: Decentralized Clinical Trial Platform.” https://www.medable.com.
———. 2026. “Medable Clinical Trial Platform.” https://www.medable.com.
Medicines and Healthcare products Regulatory Agency. 2025. “MHRA Draft Guideline on the Use of External Control Arms Based on Real-World Data to Support Regulatory Decisions.” https://www.gov.uk/government/consultations/mhra-draft-guideline-on-the-use-of-external-control-arms-based-on-real-world-data-to-support-regulatory-decisions.
Medidata Solutions. 2024a. “Everest Group EDC PEAK Matrix Assessment.” https://www.medidata.com/en/everest-group-edc-peak-matrix/.
———. 2024b. “Medidata Rave EDC.” https://www.medidata.com/en/clinical-trial-products/clinical-data-management/edc-systems.
———. 2024c. “Medidata Synthetic Control Arm.” https://medidata.com/en/clinical-trial-products/medidata-ai/real-world-data/synthetic-control-arm.
Mei, Kai, Xi Zhu, Wujiang Xu, Wenyue Hua, Mingyu Jin, Zelong Li, Shuyuan Xu, Ruosong Ye, Yingqiang Ge, and Yongfeng Zhang. 2024. “AIOS: LLM Agent Operating System.” arXiv Preprint arXiv:2403.16971. https://arxiv.org/abs/2403.16971.
Meinert, Curtis L. 2013. Clinical Trials Handbook: Design and Conduct. Hoboken, NJ: John Wiley & Sons.
Messeri, Lisa, and M. J. Crockett. 2024. “Artificial Intelligence and Illusions of Understanding in Scientific Research.” Nature. https://www.nature.com/articles/s41586-024-07146-0.
Mitchell, Margaret, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru. 2019. “Model Cards for Model Reporting.” In Proceedings of the Conference on Fairness, Accountability, and Transparency, 220–29. https://doi.org/10.1145/3287560.3287596.
Muss, Hyman B., Donald A. Berry, Constance T. Cirrincione, Maria Theodoulou, Ann M. Mauer, Alice B. Kornblith, Ann H. Partridge, et al. 2009. “Adjuvant Chemotherapy in Older Women with Early-Stage Breast Cancer.” New England Journal of Medicine 360 (20): 2055–65. https://doi.org/10.1056/NEJMoa0810266.
National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. 1979. “The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects of Research.” https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html.
National Institute for Health and Care Excellence. 2022. NICE Technology Appraisal and Highly Specialised Technologies Guidance: The Manual.” https://www.nice.org.uk/process/pmg36.
National Institute of Standards and Technology. 2023. “Artificial Intelligence Risk Management Framework (AI RMF 1.0).” https://www.nist.gov/itl/ai-risk-management-framework.
National Institutes of Health. 2023. “NIH Policy for Data Management and Sharing.” https://sharing.nih.gov/data-management-and-sharing-policy/about-data-management-and-sharing-policies.
NextTrial. 2024. “NextTrial AI: Clinical Trial Intelligence.” https://www.nexttrial.ai.
Nuremberg Military Tribunal. 1949. “The Nuremberg Code.” https://collections.nlm.nih.gov/catalog/nlm:nlmuid-01130400RX2-mvpart.
Obermeyer, Ziad, Brian Powers, Christine Vogeli, and Sendhil Mullainathan. 2019. “Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations.” Science 366 (6464): 447–53. https://doi.org/10.1126/science.aax2342.
Octozi. 2024. “Octozi: AI for Clinical Operations.” https://www.octozi.com.
Overhage, J. Marc, Patrick B. Ryan, Christian G. Reich, Arthur G. Harber, and Martijn J. Schuemie. 2012. “Validation of a Common Data Model for Active Safety Surveillance Research.” Journal of the American Medical Informatics Association. https://pmc.ncbi.nlm.nih.gov/articles/PMC3240764/.
Owkin. 2024. “Owkin: Federated Learning for Healthcare.” https://www.owkin.com.
Pallmann, Philip, Alun W. Bedding, Babak Choodari-Oskooei, Munyaradzi Dimairo, Laura Flight, Lisa V. Hampson, Jane Holmes, et al. 2018. “Adaptive Enrichment Designs in Clinical Trials.” Therapeutic Innovation & Regulatory Science 52 (3): 323–43. https://doi.org/10.1186/s12916-018-1017-7.
Park, John W., Minetta C. Liu, Douglas Yee, Christina Yau, Laura J. van ’t Veer, W. Fraser Symmans, Melissa Paoloni, et al. 2016. “Adaptive Randomization of Neratinib in Early Breast Cancer.” New England Journal of Medicine 375 (1): 11–22. https://doi.org/10.1056/NEJMoa1513750.
Park, John W., Minetta C. Liu, Douglas Yee, Christina Yau, Laura J. van ’t Veer, W. Fraser Symmans, Melissa Paoloni, et al. 2019. I-SPY 2: A Neoadjuvant Adaptive Clinical Trial Designed to Improve Outcomes in High-Risk Breast Cancer.” Current Breast Cancer Reports 11 (4): 303–10. https://doi.org/10.1007/s12609-019-00334-2.
Pharmaceutical Research and Manufacturers of America. 2024. “The Economic Impact of the u.s. Biopharmaceutical Industry.” https://phrma.org/resource-center/topics/economic-impact/industry-economic-impact.
Phlexglobal. 2024. “Phlexglobal eTMF Software.” https://www.phlexglobal.com/etmf-software.
Pocock, Stuart J., and Richard Simon. 1975. “Sequential Treatment Assignment with Balancing for Prognostic Factors in the Controlled Clinical Trial.” Biometrics 31 (1): 103–15. https://doi.org/10.2307/2529712.
Prorelix Research. 2024. “Phase-by-Phase Clinical Trial Costs: What Every Sponsor Needs to Know.” https://prorelixresearch.com/phase-by-phase-clinical-trial-costs-what-every-sponsor-needs-to-know/.
Redman, Mary W., Vassiliki A. Papadimitrakopoulou, Glenwood D. Goss, et al. 2020. “Biomarker-Driven Therapies for Previously Treated Squamous Non-Small-Cell Lung Cancer (Lung-MAP SWOG S1400): A Biomarker-Driven Master Protocol.” The Lancet Oncology 21 (12): 1589–1601. https://doi.org/10.1016/S1470-2045(20)30475-7.
Renfro, Lindsay A., and Daniel J. Sargent. 2017. “Statistical Controversies in Clinical Research: Basket Trials, Umbrella Trials, and Other Master Protocols: A Review and Examples.” Annals of Oncology 28 (1): 34–43. https://doi.org/10.1093/annonc/mdw413.
Rivera, Samantha Cruz et al. 2020. “SPIRIT-AI Extension: Guidance for Clinical Trial Protocols for Interventions Involving Artificial Intelligence.” BMJ. https://www.bmj.com/content/370/bmj.m3210.
Rosenberger, William F., and John M. Lachin. 2016. Randomization in Clinical Trials: Theory and Practice. 2nd ed. Hoboken, NJ: John Wiley & Sons.
Ross, Jessica L., Arman Sabbaghi, Run Zhuang, and Daniele Bertolini. 2024. “Enhancing Longitudinal Clinical Trial Efficiency with Digital Twins and Prognostic Covariate-Adjusted Mixed Models for Repeated Measures (PROCOVA-MMRM).” arXiv Preprint arXiv:2404.17576. https://arxiv.org/abs/2404.17576.
Saama Technologies. 2024. “Saama: Life Sciences Analytics Cloud.” https://www.saama.com.
Saleiro, Pedro, Benedict Kuester, Loren Hinkson, Jesse London, Abby Stevens, Ari Anisfeld, Kit T. Rodolfa, and Rayid Ghani. 2018. “Aequitas: A Bias and Fairness Audit Toolkit.” arXiv Preprint arXiv:1811.05577. https://arxiv.org/abs/1811.05577.
Scott, Neil W., Gladys C. McPherson, Craig R. Ramsay, and Marion K. Campbell. 2002. “The Method of Minimization for Allocation to Clinical Trials: A Review.” Controlled Clinical Trials 23 (6): 662–74. https://doi.org/10.1016/S0197-2456(02)00242-8.
Sel, Kaan, Andrea Hawkins-Daarud, Roozbeh Jafari, et al. 2025. “Survey and Perspective on Verification, Validation, and Uncertainty Quantification of Digital Twins for Precision Medicine.” Npj Digital Medicine 8: 40. https://doi.org/10.1038/s41746-025-01447-y.
Shiryaev, Albert N. 1978. Optimal Stopping Rules. Berlin: Springer-Verlag.
Simon, Noah, and Richard Simon. 2013. “Adaptive Enrichment Designs for Clinical Trials.” Biostatistics 14 (4): 613–25. https://doi.org/10.1093/biostatistics/kxt010.
Smith, Zachary P., Joseph A. DiMasi, and Kenneth A. Getz. 2024. “New Estimates on the Cost of a Delay Day in Drug Development.” Therapeutic Innovation & Regulatory Science 58 (5): 855–62. https://doi.org/10.1007/s43441-024-00667-w.
Stein, Charles. 1956. “Inadmissibility of the Usual Estimator for the Mean of a Multivariate Normal Distribution.” In Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, 1:197–206. https://www.degruyter.com/document/doi/10.1525/9780520313880-018/html.
Struebing, Alessandria, Chelsea McKibbon, Haoyao Ruan, Emma Mackay, Natalie Dennis, Russanthy Velummailum, Philip He, et al. 2024. “Augmenting External Control Arms Using Bayesian Borrowing: A Case Study in First-Line Non-Small Cell Lung Cancer.” Journal of Comparative Effectiveness Research 13 (5). https://doi.org/10.57264/cer-2023-0175.
Taves, Donald R. 1974. “Minimization: A New Method of Assigning Patients to Treatment and Control Groups.” Clinical Pharmacology & Therapeutics 15 (5): 443–53. https://doi.org/10.1002/cpt1974155443.
Thompson, William R. 1933. “On the Likelihood That One Unknown Probability Exceeds Another in View of the Evidence of Two Samples.” Biometrika 25 (3/4): 285–94. https://doi.org/10.2307/2332286.
TMF Reference Model Initiative. 2024. “Trial Master File Reference Model.” https://tmfrefmodel.com/.
Tufts Center for the Study of Drug Development. 2021a. “Site Startup Costs and Cycle Time Benchmarks.” https://csdd.tufts.edu/publications/impact-reports.
———. 2021b. “Tufts Center for the Study of Drug Development Impact Reports.” https://csdd.tufts.edu/publications/impact-reports.
———. 2024a. “Clinical Trial Management System Benchmarks.” https://csdd.tufts.edu/publications/impact-reports.
———. 2024b. “Site Performance Metrics and Benchmarks.” https://csdd.tufts.edu/publications/impact-reports.
Unger, Joseph M., Barbara L. McAneny, and Raymond U. Osarogiagbon. 2025. “Cancer in Rural America: Improving Access to Clinical Trials and Quality of Oncologic Care.” CA: A Cancer Journal for Clinicians 75 (4): 341–61. https://doi.org/10.3322/caac.70006.
Unger, Joseph M., Adrienne Moseley, Beulah Symington, Mariana Chavez-MacGregor, Scott D. Ramsey, and Dawn L. Hershman. 2018. “Geographic Distribution and Survival Outcomes for Rural Patients with Cancer Treated in Clinical Trials.” JAMA Network Open 1 (4): e181235. https://doi.org/10.1001/jamanetworkopen.2018.1235.
University of North Carolina at Chapel Hill. 2024. “Nuremberg Code.” https://research.unc.edu/human-research-ethics/resources/ccm3_019064/.
Unlearn.AI. 2024. “Unlearn.AI: Digital Twins for Clinical Trials.” https://www.unlearn.ai.
———. 2025. “A Risk-Based Approach for Leveraging AI in Clinical Trials.” https://www.unlearn.ai/blog/how-unlearn-boosts-trial-power-using-the-fdas-ai-framework.
U.S. Congress. 2022. “Food and Drug Omnibus Reform Act (FDORA) of 2022.” https://www.fda.gov/regulatory-information/selected-amendments-fdc-act/food-and-drug-omnibus-reform-act-fdora-2022.
U.S. Department of Agriculture. 1937. “Report of the Secretary of Agriculture on Deaths Due to Elixir Sulfanilamide-Massengill.”
U.S. Department of Health and Human Services. 2024. “45 CFR Part 46: Protection of Human Subjects (Common Rule).” https://www.ecfr.gov/current/title-45/subtitle-A/subchapter-A/part-46.
U.S. Food and Drug Administration. 2005. “CDER Report on Safety Surveillance.”
———. 2014. “Expedited Programs for Serious Conditions – Drugs and Biologics: Guidance for Industry.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/expedited-programs-serious-conditions-drugs-and-biologics.
———. 2016. “Use of Electronic Informed Consent in Clinical Investigations: Questions and Answers.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/use-electronic-informed-consent-clinical-investigations-questions-and-answers.
———. 2018a. “Framework for FDA’s Real-World Evidence Program.” https://www.fda.gov/media/120060/download.
———. 2018b. “The Drug Development Process.” https://www.fda.gov/patients/learn-about-drug-and-device-approvals/drug-development-process.
———. 2018c. “Use of Electronic Health Record Data in Clinical Investigations: Guidance for Industry.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/use-electronic-health-record-data-clinical-investigations-guidance-industry.
———. 2019a. “Adaptive Designs for Clinical Trials of Drugs and Biologics: Guidance for Industry.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/adaptive-design-clinical-trials-drugs-and-biologics-guidance-industry.
———. 2019b. “Enrichment Strategies for Clinical Trials to Support Approval of Human Drugs and Biological Products.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/enrichment-strategies-clinical-trials-support-approval-human-drugs-and-biological-products.
———. 2022. “Master Protocols: Efficient Clinical Trial Design Strategies to Expedite Development of Oncology Drugs and Biologics.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/master-protocols-efficient-clinical-trial-design-strategies-expedite-development-oncology-drugs-and.
———. 2023a. “21 CFR Part 11: Electronic Records; Electronic Signatures.” https://www.ecfr.gov/current/title-21/chapter-I/subchapter-A/part-11.
———. 2023b. “21 CFR Part 11: Electronic Records; Electronic Signatures.” https://www.ecfr.gov/current/title-21/chapter-I/subchapter-A/part-11.
———. 2023c. “21 CFR Part 50: Protection of Human Subjects.” https://www.ecfr.gov/current/title-21/chapter-I/subchapter-A/part-50.
———. 2023d. “21 CFR Part 56: Institutional Review Boards.” https://www.ecfr.gov/current/title-21/chapter-I/subchapter-A/part-56.
———. 2023e. “Considerations for the Design and Conduct of Externally Controlled Trials for Drug and Biological Products.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-design-and-conduct-externally-controlled-trials-drug-and-biological-products.
———. 2023f. “Considerations for the Use of Real-World Data and Real-World Evidence to Support Regulatory Decision-Making for Drug and Biological Products.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-use-real-world-data-and-real-world-evidence-support-regulatory-decision-making-drug.
———. 2023g. “COVID-19: Developing Drugs and Biological Products for Treatment or Prevention.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/covid-19-developing-drugs-and-biological-products-treatment-or-prevention.
———. 2023h. “Digital Health Technologies for Remote Data Acquisition in Clinical Investigations.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/digital-health-technologies-remote-data-acquisition-clinical-investigations.
———. 2023i. “Digital Health Technologies for Remote Data Acquisition in Clinical Investigations: Guidance for Industry, Investigators, and Other Stakeholders.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/digital-health-technologies-remote-data-acquisition-clinical-investigations.
———. 2023j. “Master Protocols for Drug and Biological Product Development: Guidance for Industry.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/master-protocols-drug-and-biological-product-development.
———. 2023k. “Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments into Endpoints for Regulatory Decision-Making.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-focused-drug-development-incorporating-clinical-outcome-assessments-endpoints-regulatory.
———. 2023l. “Adjusting for Covariates in Randomized Clinical Trials for Drugs and Biological Products: Guidance for Industry.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/adjusting-covariates-randomized-clinical-trials-drugs-and-biological-products.
———. 2024a. “21 CFR Part 312: Investigational New Drug Application.” https://www.ecfr.gov/current/title-21/chapter-I/subchapter-D/part-312.
———. 2024b. “Clinical Pharmacology Guidance Documents.” https://www.fda.gov/drugs/guidance-compliance-regulatory-information/guidances-drugs.
———. 2024c. “Decentralized Clinical Trials for Drugs, Biological Products, and Devices.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/decentralized-clinical-trials-drugs-biological-products-and-devices.
———. 2024d. “Diversity Action Plans to Improve Enrollment of Participants from Underrepresented Populations in Clinical Studies.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/diversity-action-plans-improve-enrollment-participants-underrepresented-populations-clinical-studies.
———. 2024e. “Diversity Action Plans to Improve Enrollment of Participants from Underrepresented Populations in Clinical Studies: Guidance for Industry.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/diversity-action-plans-improve-enrollment-participants-underrepresented-populations-clinical-studies.
———. 2024f. “Electronic Systems, Electronic Records, and Electronic Signatures in Clinical Investigations: Questions and Answers.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/electronic-systems-electronic-records-and-electronic-signatures-clinical-investigations-questions.
———. 2024g. “FDA Organization.” https://www.fda.gov/about-fda/fda-organization.
———. 2024h. “Real-World Data: Assessing Electronic Health Records and Medical Claims Data to Support Regulatory Decision-Making for Drug and Biological Products.” https://www.fda.gov/regulatory-information/search-fda-guidance-documents/real-world-data-assessing-electronic-health-records-and-medical-claims-data-support-regulatory.
———. 2024i. “Risk Evaluation and Mitigation Strategies (REMS).” https://www.fda.gov/drugs/drug-safety-and-availability/risk-evaluation-and-mitigation-strategies-rems.
———. 2025a. “Bayesian Statistics in Medical Device Clinical Trials: Guidance for Industry and FDA Staff.” https://www.fda.gov/media/190505/download.
———. 2025b. “CDER/CBER Rare Disease Evidence Principles (RDEP).” https://www.fda.gov/industry/fda-rare-disease-innovation-hub/cdercber-rare-disease-evidence-principles-rdep.
———. 2025c. “Pediatric Labeling Changes.” https://www.fda.gov/science-research/pediatrics/pediatric-labeling-changes.
U.S. Food and Drug Administration, and European Medicines Agency. 2026. “Guiding Principles of Good AI Practice in Drug Development.” https://www.fda.gov/media/189581/download.
U.S. Food and Drug Administration, Health Canada, and UK Medicines and Healthcare products Regulatory Agency. 2021. “Good Machine Learning Practice for Medical Device Development: Guiding Principles.” https://www.fda.gov/medical-devices/software-medical-device-samd/good-machine-learning-practice-medical-device-development-guiding-principles.
Veeva Systems. 2024a. “Veeva TMF Intake Agent and Quality Check Agent.” https://www.veeva.com/resources/tmf-intake-agent-and-quality-check-agent/.
———. 2024b. “Veeva Vault Clinical Suite.” https://www.veeva.com/products/vault-clinical/.
Venkatesh, Kaushik P., Marium M. Raza, and Joseph C. Kvedar. 2022. “Health Digital Twins as Tools for Precision Medicine: Considerations for Computation, Implementation, and Regulation.” Npj Digital Medicine 5: 150. https://doi.org/10.1038/s41746-022-00694-7.
Wagner, John, Andrew M. Dahlem, Lynn D. Hudson, Sharon F. Terry, Russ B. Altman, C. Taylor Gilliland, Christopher DeFeo, and Christopher P. Austin. 2018. “A Dynamic Map for Learning, Communicating, Navigating and Improving Therapeutic Development.” Nature Reviews Drug Discovery 17 (2): 150. https://doi.org/10.1038/nrd.2017.217.
Wald, Abraham. 1947. Sequential Analysis. New York: John Wiley & Sons.
Wang, Lei, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, Zhiyuan Chen, et al. 2024. “A Survey on Large Language Model Based Autonomous Agents.” Frontiers of Computer Science 18 (6): 186345. https://arxiv.org/abs/2308.11432.
Wang, Zifeng, Junyi Gao, Benjamin Danek, Brandon Theodorou, Ruba Shaik, Shivashankar Thati, Seunghyun Won, and Jimeng Sun. 2025. “Compliance and Factuality of Large Language Models for Clinical Research Document Generation.” Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocaf174.
Warraich, Haider J., Troy Tazbaz, and Robert M. Califf. 2024. “FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine.” JAMA. https://doi.org/10.1001/jama.2024.21451.
Wasserstein, Ronald L., and Nicole A. Lazar. 2016. “The ASA Statement on p-Values: Context, Process, and Purpose.” The American Statistician 70 (2): 129–33. https://doi.org/10.1080/00031305.2016.1154108.
WCG Clinical. 2024. “2024 Clinical Research Site Challenges Report: Data-Driven Insights on Current Site Challenges and Strategic Recommendations to Overcome Barriers and Boost Clinical Trial Efficiency.” https://www.wcgclinical.com/wp-content/uploads/2024/10/WCG_2024_Clinical_Research_Site_Challenges_Report.pdf.
Wei, Jason, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou. 2022. “Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.” Advances in Neural Information Processing Systems 35: 24824–37. https://arxiv.org/abs/2201.11903.
Wei, L. J., and S. Durham. 1978. “The Randomized Play-the-Winner Rule in Medical Trials.” Journal of the American Statistical Association 73 (364): 840–43. https://doi.org/10.1080/01621459.1978.10480109.
Wong, Chi Heem, Kien Wei Siah, and Andrew W. Lo. 2019. “Estimation of Clinical Trial Success Rates and Related Parameters.” Biostatistics 20 (2): 273–86. https://doi.org/10.1093/biostatistics/kxx069.
World Health Organization. 2021. “Ethics and Governance of Artificial Intelligence for Health.” https://iris.who.int/handle/10665/341996.
World Medical Association. 2013. “Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects.” https://www.wma.net/policies-post/wma-declaration-of-helsinki/.
———. 2024. “World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects.” JAMA 333 (1): 71–74. https://doi.org/10.1001/jama.2024.21972.
Wu, Qingyun, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang Zhu, Li Jiang, et al. 2023. “AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.” arXiv Preprint arXiv:2308.08155. https://arxiv.org/abs/2308.08155.
Yao, Shunyu, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2023. “ReAct: Synergizing Reasoning and Acting in Language Models.” International Conference on Learning Representations. https://arxiv.org/abs/2210.03629.
Zafar, S. Yousuf, David C. Currow, Nathan Cherny, Florian Strasser, Robert Fowler, and Amy P. Abernethy. 2012. “Self-Reported Conflicts of Interest of Authors, Trial Sponsorship, and the Interpretation of Editorials and Related Phase III Trials in Oncology.” Journal of Clinical Oncology 30 (28): 3552–57. https://doi.org/10.1200/JCO.2012.46.6706.
Zarin, Wei, Ying Jiang, Yuan Gao, et al. 2020. “Characteristics and Trends of Clinical Studies Primarily Sponsored by China in WHO Primary Registries Between 2009 and 2018: A Cross-Sectional Survey.” BMJ Open 10 (11): e037262. https://doi.org/10.1136/bmjopen-2020-037262.
Zhang, Ashley Ge, Yan Chen, and Steve Oney. 2023. “VizProg: Identifying Misunderstandings by Visualizing Students’ Coding Progress.” In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3544548.3581516.
Zhou, Xin, Suyu Liu, Edward S. Kim, Roy S. Herbst, and J. Jack Lee. 2015. “A Bayesian Adaptive Design for Biomarker Trials with Linked Treatments.” British Journal of Cancer 113: 716–23. https://doi.org/10.1038/bjc.2015.278.