A Smart Platform for Prodrug Design to Make a Good Drug Better
What's new about AI4Prodrug?
AI4Prodrug is an innovative platform being established by building a comprehensive prodrug database and utilizing retro-path algorithms to assist in 'silico' prodrug design from the chemical structure, achieving the optimal performance of a drug or drug candidate.
With our database, an AI-based retrosynthesis algorithm collects related information and suggests several reliable virtual prodrugs to be considered for development. The comprehensive prodrug data would benefit to gain information for prodrug design and/or predict potential performance of the drug/prodrug candidates.
An innovative approach for prodrug design relies on the buildup of a database that includes all the comprehensive information and knowledge about prodrugs. Our prodrug reaction database accomplishes this, allowing users to obtain the information they need.
A retrosynthesis concept can be applied to the prodrug design to focus on a specific purpose, e.g. solubility, permeability, stability improvement or targeted delivery. Our platform can make the design smarter in order to achieve better pharmaceutical properties, reduce manufacture cost and minimize the drug development risks.
Why is this necessary?
Prodrugs are designed in order to improve pharmaceutical properties, with approximately 10% of all marketed drugs worldwide being considered as prodrugs. However, there has been a lack of a systematic platform for designing prodrugs. Currently, most are designed by experience-based or examples-based approaches.
The success of a prodrug has depended on the scientist's knowledge, skill, accessible information and efforts. Thus, there are some potential human mistakes in prodrug design that lead to failures in design or missing opportunities to identify a better optimal prodrug.