REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation

Area of Science:

• Pharmacology and Drug Development
• Biostatistics
• Computational Biology

Background:

• Accurate dose-response curve estimation is crucial for drug development.
• Existing tools may lack user-friendliness or robust statistical methods.
• REAP-2 addresses these limitations with an updated approach.

Purpose of the Study:

• To introduce REAP-2, an interactive tool for robust and efficient assessment of drug potency.
• To provide user-friendly dose-response curve estimation for in vitro studies.
• To implement an updated estimation method using penalized beta regression.

Main Methods:

• Development of REAP-2 with a redesigned user interface.
• Implementation of penalized beta regression for dose estimation.
• Statistical testing for model comparisons and uncertainty quantification.

Main Results:

• Penalized beta regression demonstrates high reliability and accuracy in dose estimation.
• REAP-2 provides enhanced uncertainty quantification.
• The tool facilitates effective drug comparison through statistical testing.

Conclusions:

• REAP-2 offers a significant advancement in dose-response curve estimation.
• The updated methodology ensures reliable potency assessment and drug comparison.
• The user-friendly interface supports efficient analysis of in vitro drug studies.