PharmDE: A new expert system for drug-excipient compatibility evaluation

Area of Science:

• Pharmaceutical Sciences
• Computational Chemistry
• Drug Delivery Systems

Background:

• Drug-excipient compatibility is crucial for pre-formulation and pharmaceutical Quality by Design (QbD).
• Existing methods for assessing drug-excipient interactions are often inconvenient and data is scattered.
• A need exists for an efficient system to manage and utilize drug-excipient incompatibility data.

Purpose of the Study:

• To develop an AI-driven expert system, PharmDE, for evaluating drug-excipient incompatibility risks.
• To create a centralized database and rule-based system for predicting interactions.
• To provide researchers with a tool for rational compatibility experimental design.

Main Methods:

• Developed an information-rich database with 532 data items from 228 articles.
• Created 60 drug-excipient interaction rules based on expert knowledge.
• Integrated database searching and rule-based prediction into an expert system with four functionalities.

Main Results:

• PharmDE integrates a comprehensive incompatibility database and expert rules.
• The system offers functionalities for basic search, similarity matching, and risk evaluation.
• Successfully processed 532 incompatibility data points from 228 scientific articles.

Conclusions:

• PharmDE serves as a valuable tool for drug-excipient compatibility studies.
• The system is expected to accelerate drug formulation design and pre-formulation stages.
• PharmDE is freely available online to support pharmaceutical research.