ExtractionScore: A Quantitative Framework for Evaluating Synthetic Routes on Predicted Liquid-Liquid Extraction...

Area of Science:

• Computational chemistry
• Chemical synthesis
• Process optimization

Background:

• Computer-aided synthesis planning (CASP) tools lack robust methods for evaluating reaction selectivity and purification challenges.
• Existing metrics do not fully account for side product formation and its impact on downstream processes.
• Accurate scoring of synthetic routes is crucial for identifying efficient and practical chemical pathways.

Purpose of the Study:

• To develop a novel quantitative metric, ExtractionScore, for evaluating synthetic routes in CASP.
• To incorporate the prediction of side products and their separability via liquid-liquid extraction into route scoring.
• To enhance the reliability of retrosynthetic recommendations by considering purification aspects.

Main Methods:

• Developed ExtractionScore, a metric based on predicted side product identities and chemical property predictions for liquid-liquid extraction.
• Evaluated ExtractionScore by comparing industrially practiced routes against CASP-suggested routes for 200 pharmaceutically relevant compounds.
• Integrated side product prediction and separation assessment into the quantitative evaluation of synthetic routes.

Main Results:

• ExtractionScore provides a quantitative evaluation of synthetic routes by considering side product formation and purification.
• The metric demonstrates potential to improve the quality of retrosynthetic recommendations from CASP software.
• Incorporating side product information leads to more realistic and practical synthetic route assessments.

Conclusions:

• ExtractionScore offers a significant advancement in evaluating synthetic routes by addressing limitations in current CASP tools regarding selectivity and purification.
• The novel metric enhances the identification of promising synthetic strategies by factoring in the practical challenges of side product management.
• This approach has the potential to optimize chemical synthesis planning and improve the efficiency of drug discovery and development pipelines.