Dynamic Programming for Response-Adaptive Dose-Finding Clinical Trials
Published Online:21 Oct 2021https://doi.org/10.1287/ijoc.2021.1082
References
- (2016) Response-adaptive designs for clinical trials: Simultaneous learning from multiple patients. Eur. J. Oper. Res. 248(2):619–633.Crossref, Google Scholar
- (2009) An Introduction to Optimal Designs for Social and Biomedical Research, vol. 83 (John Wiley & Sons, New York).Crossref, Google Scholar
- (2002) Adaptive Bayesian designs for dose-ranging drug trials. Gatsonis C, Kass RE, Carlin B, Carriquiry A, Gelman A, Verdinelli I, West M, eds. Case Studies in Bayesian Statistics, Lecture Notes in Statistics, vol. 162 (Springer, New York), 99–181.Google Scholar
- (2010) Bayesian Adaptive Methods for Clinical Trials (CRC Press, Boca Raton, FL).Google Scholar
- (2017) A Bayesian decision theoretic model of sequential experimentation with delayed response. J. Roy. Statist. Soc. Ser. B: Statist. Methodology 79(5):1439–1462.Crossref, Google Scholar
- (2016) Handbook of Adaptive Designs in Pharmaceutical and Clinical Development (CRC Press, Boca Raton, FL).Google Scholar
- (2008) Optimal designs for dose-finding studies. J. Amer. Statist. Assoc. 103(483):1225–1237.Crossref, Google Scholar
- Eli Lilly and Company (2018) A study of LY2951742 in participants with mild to moderate osteoarthritis knee pain. Accessed October 1, 2020, https://clinicaltrials.gov/ct2/show/results/NCT02192190.Google Scholar
- (2011) Consistency of sequential Bayesian sampling policies. SIAM J. Control Optim. 49(2):712–731.Crossref, Google Scholar
- (2008) A knowledge-gradient policy for sequential information collection. SIAM J. Control Optim. 47(5):2410–2439.Crossref, Google Scholar
- (2009) The knowledge-gradient policy for correlated normal beliefs. INFORMS J. Comput. 21(4):599–613.Link, Google Scholar
- (1994) Data augmentation and dynamic linear models. J. Time Ser. Anal. 15(2):183–202.Crossref, Google Scholar
- (2015) Computational tools for fitting the Hill equation to dose–response curves. J. Pharmacological Toxicological Methods 71:68–76.Crossref, Google Scholar
- , eds. (2010) Transforming Clinical Research in the United States: Challenges and Opportunities: Workshop Summary (National Academies Press, Washington, DC).Google Scholar
- (1996) Bayesian look ahead one-stage sampling allocations for selection of the best population. J. Statist. Planning Inference 54(2):229–244.Crossref, Google Scholar
- (2014) Clinical development success rates for investigational drugs. Nature Biotechnology 32(1):40–51.Crossref, Google Scholar
- (2010) A Bayesian approach to dose–response assessment and synergy and its application to in vitro dose–response studies. Biometrics 66(4):1275–1283.Crossref, Google Scholar
- (2017) Development of a Bayesian response-adaptive trial design for the Dexamethasone for excessive menstruation study. Statist. Methods Medical Res. 26(6):2681–2699.Crossref, Google Scholar
- (2016) Hierarchical Bayesian inference for ion channel screening dose-response data. Wellcome Open Res. 1–6.Google Scholar
- (2016) Response-guided dosing for rheumatoid arthritis. IIE Trans. Healthcare Systems Engrg. 6(1):1–21.Crossref, Google Scholar
- (2018) Bayesian learning of dose–response parameters from a cohort under response-guided dosing. Eur. J. Oper. Res. 265(1):328–343.Crossref, Google Scholar
- , (2003) Acute stroke therapy by inhibition of neutrophils (ASTIN): An adaptive dose-response study of UK-279, 276 in acute ischemic stroke. Stroke 34(11):2543–2548.Crossref, Google Scholar
- (2015) Adaptive dose-finding phase 2 trial evaluating the safety and efficacy of ABT-089 in mild to moderate Alzheimer disease. Alzheimer Disease Associated Disorders 29(3):192–199.Crossref, Google Scholar
- (2006) A Bayesian decision-theoretic dose-finding trial. Decision Anal. 3(4):197–207.Link, Google Scholar
- (2020) Optimal stopping of adaptive dose-finding trials. Service Sci. 12(2-3):80–99.Link, Google Scholar
- National Institutes of Health (2014) Notice of revised NIH definition of clinical trial. Accessed October 1, 2020, http://grants.nih.gov/grants/guide/notice-files/NOT-OD-15-015.html.Google Scholar
- (2017) Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials (CRC Press, Boca Raton, FL).Crossref, Google Scholar
- (2016) Lot-sizing in sequential auctions while learning bid and demand distributions. 2016 Winter Simulation Conf. (WSC) (IEEE, Piscataway, NJ), 895–906.Google Scholar
- (2012) Optimal Learning, vol. 841 (John Wiley & Sons, New York).Crossref, Google Scholar
- (2009) Bandit solutions provide unified ethical models for randomized clinical trials and comparative effectiveness research. Proc. Natl. Acad. Sci. USA. 106(52):22387–22392.Crossref, Google Scholar
- (1996) New directions in adaptive designs. Statist. Sci. 11(2):137–149.Crossref, Google Scholar
- (2006) Implementation of a Bayesian adaptive design in a proof of concept study. Pharmaceutical. Statist. 5(1):39–50.Crossref, Google Scholar
- (2006) Assessment of futility in clinical trials. Pharmaceutical Statist.: J. Appl. Statist. Pharmaceutical Industry 5(4):273–281.Google Scholar
- The European Medicines Agency (2014) Qualification opinion of MCP-Mod as an efficient statistical methodology for model-based design and analysis of Phase II dose finding studies under model uncertainty. Accessed October 1, 2020, https://www.ema.europa.eu/en/committees/committee-medicinal-products-human-use-chmp.Google Scholar
- Tufts (2014) Cost to develop and win marketing approval for a new drug is $2.6 billion. Accessed October 1, 2020, http://csdd.tufts.edu/news/complete_story/pr_tufts_csdd_2014_cost_study.Google Scholar
- U.S. Food and Drug Administration (2017) The drug development process: Clinical research. Accessed October 1, 2020, https://www.fda.gov/ForPatients/Approvals/Drugs/ucm405622.htm.Google Scholar
- U.S. Food and Drug Administration (2018) Adaptive designs for clinical trials of drugs and biologics: Draft guidance for industry. Accessed October 1, 2020, https://www.fda.gov/downloads/drugs/guidances/ucm201790.pdf.Google Scholar
- (2015) Multi-armed bandit models for the optimal design of clinical trials: Benefits and challenges. Statist. Sci. 30(2):199–215.Crossref, Google Scholar
- (2018) Covariate-adjusted response-adaptive randomization for multi-arm clinical trials using a modified forward looking Gittins index rule. Biometrics 74(1):49–57.Crossref, Google Scholar
- (2016) The knowledge gradient for sequential decision making with stochastic binary feedbacks. Lawrence N, Reid M, eds. Internat. Conf. Machine Learn. (PMLR, New York), 1138–1147.Google Scholar
- (2007) Flexible design and efficient implementation of adaptive dose-finding studies. J. Biopharmaceutical Statist. 17(6):1033–1050.Crossref, Google Scholar
- (1997) Bayesian Forecasting and Dynamic Models (Springer-Verlag, New York).Google Scholar
- (2012) Phase II trial design with Bayesian adaptive randomization and predictive probability. J. Roy. Statist. Soc. Ser. C: Appl. Statist. 61(2):219–235.Crossref, Google Scholar

