Recently, CIMS Global founder Dr. Tai Xie presented at the Innovative Trial Design Symposium in Beijing. His talk, titled Dynamic Adaptive Design and Dynamic Data Monitoring, focused on how machine learning and artificial intelligence can reshape the future of clinical trials.
By using a new approach called Dynamic Adaptive Design, (DAD), supported by real-time patient data, sponsors are now able to
- Continuously monitor on-going data
- Deploy data-guided (trend-based) adaptation
- Use the “tend analysis” to detect whether the trial is “promising” or “hopeless”
These concepts can dramatically improve the effectiveness of phase 2 and phase 3 studies. This revolutionary new clinical trial design and dynamic data monitoring technology eliminates the need for
- a human to unblind the data for computing the efficacy/safety scores
- an IDMC to review and make a decision on “go/no go” without knowing the trend of the trial
- at least 3-6 months for planning, data cleaning and statistical analysis to support Independent Data Monitoring Committee (IDMC) review
The ability for early termination of “hopeless” trials avoids unethical patient suffering and financial waste. This approach and new technology can also be used for
- Monitoring drug safety and signal detection in real-time
- Performing a formal futility analysis, or other adaptive procedures such as population enrichment, or sample size modification
- Intelligently estimating an optimal sample size for a trial and thus maximizing the probability of success of the trial
- Enabling a seamless, optimal phase 2/3 combination trial by identifying most potential doses for phase 3
- Intelligently identifying the subpopulation in which the drug is most effective
- Checking and verifying the assumptions set prior to initiation of the trial
- Optimizing on-going trials to maximize success
Dynamic Adaptive Design and Dynamic Data Monitoring
Here is Dr. Xie’s presentation for download:
Dynamic Adaptive Design and Dynamic Data Monitoring
Contact us to learn more about the potential applications of this technology for your clinical research.
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