Adaptive design (medicine)
Adaptions may include modifications to: dosage, sample size, drug undergoing trial, patient selection criteria and/or "cocktail" mix.
It also attempted to offer flexibility to investigators to find the optimal clinical benefit without affecting the study's validity.
[7] In 2012, the President's Council of Advisors on Science and Technology (PCAST) recommended that the FDA "run pilot projects to explore adaptive approval mechanisms to generate evidence across the lifecycle of a drug from the pre-market through the post-market phase."
"[9] By 2019, the FDA updated their 2010 recommendations and issued "Adaptive Design Clinical Trials for Drugs and Biologics Guidance".
[10] In October of 2021, the FDA Center for Veterinary Medicine issued the Guidance Document "Adaptive and Other Innovative Designs for Effectiveness Studies of New Animal Drugs".
[8] Phase I of clinical research focuses on selecting a particular dose of a drug to carry forward into future trials.
At each interim analysis, investigators will use the current data to decide whether the trial should either stop or should continue to recruit more participants.
[22] Mander and Thomson also proposed a design with a single interim analysis, at which point the trial could stop for either futility or benefit.
Planning to stop a trial when the probability of success, based on the results so far, is either above or below a certain threshold is called stochastic curtailment.
[27][28][29][30] The US National Institute of Allergy and Infectious Diseases (NIAID) initiated an adaptive design, international Phase III trial (called "ACTT") to involve up to 800 hospitalized COVID‑19 people at 100 sites in multiple countries.
[31] An adaptive trial design enabled two experimental breast cancer drugs to deliver promising results after just six months of testing, far shorter than usual.
Researchers assessed the results while the trial was in process and found that cancer had been eradicated in more than half of one group of patients.
Additionally, its shared database has furthered the understanding of drug response and generated new targets and agents for subsequent testing.
[32] I-SPY 2 is an adaptive clinical trial of multiple Phase 2 treatment regimens combined with standard chemotherapy.
I-SPY 2 was designed to explore the hypothesis that different combinations of cancer therapies have varying degrees of success for different patients.
Treatments that show positive effects for a patient group can be ushered to confirmatory clinical trials, while those that do not can be rapidly sidelined.
I-SPY 2 can simultaneously evaluate candidates developed by multiple companies, escalating or eliminating drugs based on immediate results.
[34] Researchers under the EPAD project by the Innovative Medicines Initiative are utilizing an adaptive trial design to help speed development of Alzheimer's disease treatments, with a budget of 53 million euros.
[36] The EPAD project plans to use the results from this study and other data to inform 1,500 person selected adaptive clinical trials of drugs to prevent Alzheimer's.
In other words, the Bayesian designs for the regulatory submission need to satisfy the type I and II error requirement in most cases in the frequentist sense.
Some exception may happen in the context of external data borrowing where the type I error rate requirement can be relaxed to some degree depending on the confidence of the historical information.
According to PCAST "One approach is to focus studies on specific subsets of patients most likely to benefit, identified based on validated biomarkers.
