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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Adaptive design (medicine) | 3/4 | https://en.wikipedia.org/wiki/Adaptive_design_(medicine) | reference | science, encyclopedia | 2026-05-05T09:48:46.125163+00:00 | kb-cron |
==== I-SPY 1 ==== For its predecessor I-SPY 1, 10 cancer centers and the National Cancer Institute (NCI SPORE program and the NCI Cooperative groups) collaborated to identify response indicators that would best predict survival for women with high-risk breast cancer. During 2002–2006, the study monitored 237 patients undergoing neoadjuvant therapy before surgery. Iterative MRI and tissue samples monitored the biology of patients to chemotherapy given in a neoadjuvant setting, or presurgical setting. Evaluating chemotherapy's direct impact on tumor tissue took much less time than monitoring outcomes in thousands of patients over long time periods. The approach helped to standardize the imaging and tumor sampling processes, and led to miniaturized assays. Key findings included that tumor response was a good predictor of patient survival, and that tumor shrinkage during treatment was a good predictor of long-term outcome. Importantly, the vast majority of tumors identified as high risk by molecular signature. However, heterogeneity within this group of women and measuring response within tumor subtypes was more informative than viewing the group as a whole. Within genetic signatures, level of response to treatment appears to be a reasonable predictor of outcome. Additionally, its shared database has furthered the understanding of drug response and generated new targets and agents for subsequent testing.
==== I-SPY 2 ==== I-SPY 2 is an adaptive clinical trial of multiple Phase 2 treatment regimens combined with standard chemotherapy. I-SPY 2 linked 19 academic cancer centers, two community centers, the FDA, the NCI, pharmaceutical and biotech companies, patient advocates and philanthropic partners. The trial is sponsored by the Biomarker Consortium of the Foundation for the NIH (FNIH), and is co-managed by the FNIH and QuantumLeap Healthcare Collaborative. I-SPY 2 was designed to explore the hypothesis that different combinations of cancer therapies have varying degrees of success for different patients. Conventional clinical trials that evaluate post-surgical tumor response require a separate trial with long intervals and large populations to test each combination. Instead, I-SPY 2 is organized as a continuous process. It efficiently evaluates multiple therapy regimes by relying on the predictors developed in I-SPY 1 that help quickly determine whether patients with a particular genetic signature will respond to a given treatment regime. The trial is adaptive in that the investigators learn as they go, and do not continue treatments that appear to be ineffective. All patients are categorized based on tissue and imaging markers collected early and iteratively (a patient's markers may change over time) throughout the trial, so that early insights can guide treatments for later 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. Importantly, confirmatory trials can serve as a pathway for FDA Accelerated Approval. I-SPY 2 can simultaneously evaluate candidates developed by multiple companies, escalating or eliminating drugs based on immediate results. Using a single standard arm for comparison for all candidates in the trial saves significant costs over individual Phase 3 trials. All data are shared across the industry. As of January 2016 I-SPY 2 is comparing 11 new treatments against 'standard therapy', and is estimated to complete in Sept 2017. By mid 2016 several treatments had been selected for later stage trials.
=== Alzheimer's ===
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. The first trial under the initiative was expected to begin in 2015 and to involve about a dozen companies. As of 2020, 2,000 people over the age of 50 have been recruited across Europe for a long term study on the earliest stages of Alzheimer's. 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.
== Bayesian designs == The adjustable nature of adaptive trials inherently suggests the use of Bayesian statistical analysis. Bayesian statistics inherently address updating information such as that seen in adaptive trials that change from updated information derived from interim analysis. The problem of adaptive clinical trial design is more or less exactly the bandit problem as studied in the field of reinforcement learning. According to FDA guidelines, an adaptive Bayesian clinical trial can involve:
Interim looks to stop or to adjust patient accrual Interim looks to assess stopping the trial early either for success, futility or harm Reversing the hypothesis of non-inferiority to superiority or vice versa Dropping arms or doses or adjusting doses Modification of the randomization rate to increase the probability that a patient is allocated to the most appropriate treatment (or arm in the multi-armed bandit model) The Bayesian framework Continuous Individualized Risk Index which is based on dynamic measurements from cancer patients can be effectively used for adaptive trial designs. Platform trials rely heavily on Bayesian designs.