Computer-designed repurposing of chemical wastes into drugs

Area of Science:

• Chemical Engineering
• Computational Chemistry
• Green Chemistry

Background:

• The chemical industry generates significant waste, necessitating circular chemistry approaches for waste valorization.
• Current waste-to-product strategies are fragmented and limited to well-established chemical classes.
• Analyzing vast synthetic possibilities from diverse chemical wastes is computationally challenging for human chemists.

Purpose of the Study:

• To develop and demonstrate a computational method for identifying viable synthetic routes from chemical waste to valuable products.
• To leverage artificial intelligence and extensive synthetic knowledge for comprehensive waste valorization.

Main Methods:

• Utilized the Allchemy forward-synthesis platform to generate extensive synthetic networks from approximately 200 commercial-scale waste chemicals.
• Retrieved tens of thousands of synthetic routes leading to approximately 300 valuable drugs and agrochemicals.
• Algorithmically ranked synthetic routes based on sustainable chemistry metrics and validated selected routes experimentally, including a flow-chemistry demonstration.

Main Results:

• Generated massive synthetic networks mapping potential transformations of industrial chemical wastes.
• Identified thousands of viable synthesis routes from waste chemicals to valuable pharmaceuticals and agrochemicals.
• Experimental validation confirmed the feasibility of computer-generated waste-to-value chemical syntheses.

Conclusions:

• Computerized systems can effectively navigate complex synthetic networks to discover novel waste-to-value pathways.
• This approach accelerates the productive reuse of chemical waste, offering economic and environmental benefits.
• Widespread adoption of these algorithms can significantly advance circular economy principles in the chemical industry.