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Rare Diseases Drug Development
Published in Wei Zhang, Fangrong Yan, Feng Chen, Shein-Chung Chow, Advanced Statistics in Regulatory Critical Clinical Initiatives, 2022
Shein-Chung Chow, Shutian Zhang, Wei Zhang
In recent years, the n-of-1 trial design has become a very popular design for evaluation of the difference in treatment effect within the same individual when n treatments are administered at different dosing periods. In general, as compared to parallel-group design, n-of-1 trial design requires less subjects for evaluation of the test treatment under investigation. On the other hand, adaptive trial design has the flexibility for modifying the study protocol as it continues after the review of interim data. Clinical trials utilizing adaptive design methods cannot only increase the probability of success of drug development but also shorten the development process.
Selected Statistical Topics of Regulatory Importance
Published in Demissie Alemayehu, Birol Emir, Michael Gaffney, Interface between Regulation and Statistics in Drug Development, 2020
Demissie Alemayehu, Birol Emir, Michael Gaffney
Adaptive designs permit modifications to various attributes of the trial based on analysis of data from subjects in the study, while ensuring that the integrity of the trial is not compromised. The modification may involve study procedures, including eligibility criteria, dose levels and duration of treatment; sample size; or statistical methods. Examples of adaptive design methods include adaptive randomization, group sequential designs, sample size reestimation, adaptive dose-finding designs, as well as adaptive-seamless Phase II/III trial designs (Chow et al. 2005).
Adaptive Threshold Design
Published in Nusrat Rabbee, Biomarker Analysis in Clinical Trials with R, 2020
The Food and Drug Administration (FDA) is increasingly interested in lending its support for properly designed clinical trials, which used adaptive mechanisms (like GSM and other procedures) to bring the right therapy to patients. The current FDA guidance states: an adaptive design is defined as a clinical trial design that allows for prospectively planned modifications to one or more aspects of the design based on accumulating data from subjects in the trial [23].
COURAGE-ALS: a randomized, double-blind phase 3 study designed to improve participant experience and increase the probability of success
Published in Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 2023
Jeremy M. Shefner, Ammar Al-Chalabi, Jinsy A. Andrews, Adriano Chio, Mamede De Carvalho, Bettina M. Cockroft, Philippe Corcia, Philippe Couratier, Merit E. Cudkowicz, Angela Genge, Orla Hardiman, Terry Heiman-Patterson, Robert D. Henderson, Caroline Ingre, Carlayne E. Jackson, Wendy Johnston, Noah Lechtzin, Albert Ludolph, Nicholas J. Maragakis, Timothy M. Miller, Jesus S. Mora Pardina, Susanne Petri, Zachary Simmons, Leonard H. Van Den Berg, Lorne Zinman, Stuart Kupfer, Fady I. Malik, Lisa Meng, Tyrell J. Simkins, Jenny Wei, Andrew A. Wolff, Stacy A. Rudnicki
An independent, unblinded Data Monitoring Committee (DMC) will regularly review the data for safety and will also conduct two planned interim data reviews during this adaptive design study. First, 12 weeks after at least one-third of the planned study population has been randomized, they will assess the effect of reldesemtiv on ALSFRS-R total score change from baseline to week 12. If there appears to be a lack of effect in this first interim analysis, the DMC may recommend stopping the trial due to futility; if futility is not found, the trial will continue. Second, 24 weeks after at least one-third of the planned study population has been randomized, the DMC will assess whether the trial has adequate power to achieve a statistically significant effect on the primary endpoint in the final primary analysis, given the planned enrollment. The DMC may make a recommendation to (1) stop the trial if continuing is futile, (2) to increase the trial by a prespecified fixed number if continuing is promising, or (3) to continue as planned if the interim data do not suggest the first two options. This method is referred to as the CDL adaptive method and was initially proposed by Chen, DeMets, and Lan (17), later extended by Gao, Ware and Mehta (18), and Mehta and Pocock (19).
Tests and classification methods in adaptive designs with applications
Published in Journal of Applied Statistics, 2023
Diana Q. Chen, Si-Qi Mao, Xu-Feng Niu
Clinical trials play an important role in medical research, in which participants (usually human volunteers) receive specific interventions based on the protocol designed by the researchers. The interventions in a clinical trial could be different medical products, such as new drugs, new devices, or new procedures that are compared with a placebo. Adaptive designs in clinical trials were proposed in the 1970s when Efron [11] discussed how to balance a sequential experiment. Wei [34] introduced a class of designs for sequential clinical trials, the biased-coin design, for the purpose of reducing experimental bias and increasing the precision of inference about treatment effects. The main idea of an adaptive design in clinical trials is that the investigator may modify trial and/or statistical procedures based on the review of data from different stages during the experimental process, which may identify clinical benefits of the treatments more efficiently and increase the success probability of the clinical development without undermining the validity and integrity of the trial.
What have we learned from past failures of investigational drugs for Alzheimer’s disease?
Published in Expert Opinion on Investigational Drugs, 2021
Bruno P. Imbimbo, Mark Watling
We recommend adopting simple study designs with traditional parallel groups, rather than innovative and (understandably) attractive new approaches, such as adaptive design. These alternative approaches may introduce uncontrolled biases. One example is a Phase 2 study with lecanemab, where an adaptive design was adopted [39]. Unfortunately, an unforeseen change of the clinical protocol with the exclusion of APOE4 carriers at the highest doses generated an imbalance in the number of APOE4 carriers with only 30% of the treatment cohort composed of APOE4 carriers compared with 71% of the placebo group. Since APOE4 carriers generally experience faster cognitive decline [40], the placebo group would be expected to decline more quickly than the higher dose lecanemab group, thus ‘favoring’ the latter. Despite this potential advantage for lecanemab, the study still did not meet the 12-month primary endpoint. Nevertheless, the authors claimed a consistent reduction of clinical decline across several clinical and biomarker endpoints [41] that is difficult to interpret in view of the above.