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Published on: October 29, 2018
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Can a multiple ascending dose study serve as an informative proof-of-concept study?
1Eli Lilly and Company, Indianapolis, Indiana.
Statistics in Medicine
|September 29, 2018
Summary
This study introduces a model-based multiple ascending dose (MAD) design to gather early efficacy data alongside safety information. This approach aims to reduce drug development costs and timelines by improving Phase 2 success rates.
Area of Science:
- Clinical Pharmacology
- Drug Development Strategy
- Biostatistics
Background:
- Drug development is lengthy, expensive, and prone to high failure rates, particularly in Phase 2 and Phase 3 clinical trials.
- Current drug development costs are heavily influenced by the expenses associated with late-stage clinical trials.
- Improving the success rate of Phase 2 trials by obtaining more informative preclinical data can significantly reduce overall development costs.
Purpose of the Study:
- To propose a novel model-based multiple ascending dose (MAD) study design.
- To demonstrate that MAD studies can yield informative efficacy data in addition to safety data.
- To enable early proof-of-concept validation, thereby reducing drug development cycle time and costs.
Main Methods:
- Utilizing parametric models for longitudinal dose-response relationships.
- Incorporating models that describe the impact of dose titration on response variables.
- Applying a model-based approach to the design of multiple ascending dose (MAD) studies.
Main Results:
- The proposed MAD design provides essential safety information.
- The design generates valuable, early-stage efficacy data for specific endpoints and therapeutic areas.
- This approach allows for preliminary proof-of-concept assessment before Phase 2 trials.
Conclusions:
- A model-based MAD design can enhance early drug development by providing both safety and efficacy insights.
- This strategy can serve as an effective proof-of-concept study, informing decisions prior to Phase 2.
- Implementing this design may significantly shorten drug development timelines without escalating Phase 2 risks.
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