Dynamic Trial Design
Overcome the drawbacks of traditional GS and AGS.
A Breakthrough in Clinical Trial Design
69.3% of Phase II studies don’t make it to Phase III. 41.9% of Phase III studies don’t make it to NDA.
The majority of drugs studied under traditional design with one final analysis turn out either short of positive or negative. Because of these high failure rates, there is an urgent need to dramatically improve study design and implement today’s advanced technology during the clinical trials process.
Dynamic Trial Design eliminates the time constraints caused by Group Sequential Design (GSD) and Adaptive Group Sequential Design (AGSD) by leveraging Machine Learning and AI to turn Adaptive Group Sequential Design into a dynamic, real-time study evaluation.
How it Works
Adaptive Group Sequential Design (AGSD) improves upon traditional Group Sequential Design (GSD) by adding pre-planned success criteria and penalties based on limited prior information on efficacy/safety of the drug. However, this still requires:
- 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
Dynamic Trial Design works by integrating this innovative study design with the CIMS Dynamic Data Monitoring (DDM) platform and full EDC/eClinical platform with Interactive Web Response System (IWRS).
Dynamic Trial Design removes the time constraints of Adaptive Group Sequential Design, allowing biotech and pharmaceutical companies to:
- Dynamically monitor clinical trials without using an Independent Data Monitoring Committee (IDMC)
- Display a complete trace of treatment effect along the information time axis
- Allow clinical trials to be adjusted without imposing pre-specified statistical penalty
- Optimize clinical trials to maximize its chances of success
- End “hopeless” trials to avoid unethical patient suffering and multi-million dollar financial waste
FDA Guidance & Statistical Methods
The FDA issued guidance on the category of Adaptive Designs for Clinical Trials, which Support Independent Data Monitoring Committee (IDMC) with DDM.
Our publication explains the statistical methods used to execute Dynamic Trial Design.
How to Implement
CIMS offers variety of services and solutions for customers.
The Complete Suite
The suite consists of the CIMS EDC, IWRS and DDM engine. These three components are seamlessly integrated with internal I/O to each component.
Standalone DDM Engine
We provide API version of DDM engine which can be integrated with any EDC/IWRS system through our proprietary blockchain technology.
Contact us for DDM API.
We also provide a broad range of statistical consultation:
- Sample size estimation
- Group Sequential Design
- Dynamic Trial Design
- Seamless phase 2/3 combination design
- DDM planning, implementation and execution
- Support Independent Data Monitoring Committee (IDMC) with DDM
- FDA/EMA interaction about DDM
Please contact us for a quick call.
This is the Dynamic Data Monitoring engine at work – the machine intelligence and AI.
See Dynamic Data Monitoring in action