DEGAS: sharing and tracking target compound ideas with external collaborators.

Area of Science:

• Drug Discovery and Development
• Computational Chemistry
• Clinical Trial Management

Background:

• Drug discovery faces challenges with geographically dispersed teams and the need for high-quality clinical candidates.
• Minimizing clinical trial failure requires selecting active, selective compounds with favorable physicochemical and DMPK properties.

Purpose of the Study:

• To implement DEGAS, a collaborative application for drug discovery teams.
• To improve decision-making regarding compound synthesis and reduce duplicate efforts.
• To ensure scientists have instant access to the same critical data, regardless of location.

Main Methods:

• Development of the DEGAS application for seamless data sharing among internal and external collaborators.
• Integration of physicochemical property calculations and DMPK model predictions within the application.
• Implementation of synthesis progress tracking features for enhanced project oversight.

Main Results:

• DEGAS enables instant, unified data access for geographically distributed drug discovery teams.
• The application facilitates informed decisions on compound prioritization through property and prediction data.
• DEGAS streamlines the drug discovery process, reducing redundant synthesis efforts and improving efficiency.

Conclusions:

• DEGAS enhances collaborative decision-making in drug discovery by providing shared, real-time data and predictive insights.
• The application contributes to minimizing the risk of clinical trial failure by promoting the selection of superior drug candidates.
• Ease of use was a key design principle, facilitating adoption and support for remote users in drug discovery endeavors.