From Feasible to Practical: Pareto-Optimal Synthesis Planning

Researchers introduce MORetro*, a multi-objective optimization algorithm for computer-aided synthesis planning that generates Pareto-optimal routes balancing cost, sustainability, toxicity, and yield. This approach moves beyond single-route solutions to provide chemists with practical trade-off alternatives aligned with real-world industrial decision-making.

MORetro* represents a meaningful shift in how computational chemistry approaches retrosynthesis planning. Traditional CASP methods optimize for single metrics like convergence or shortest path length, treating synthesis planning as solved once any viable route emerges. The research demonstrates this assumption misses critical real-world constraints chemists navigate daily—balancing material costs against environmental impact, toxicity profiles against production yield, and sustainability metrics against timeline feasibility.

This work builds on established multi-objective optimization literature, adapting A*-search principles to chemistry's combinatorial complexity. The algorithm uses weighted scalarization and Bayesian optimization-informed sampling to efficiently explore vast route spaces, generating Pareto fronts that explicitly visualize trade-offs rather than forcing artificial prioritization. The theoretical contribution includes optimality guarantees for recovering true Pareto fronts given fixed single-step models, grounding the approach in mathematical rigor.

For pharmaceutical and chemical manufacturing industries, this capability directly addresses industrial workflow requirements. Rather than presenting a single recommendation, MORetro* enables chemists to visualize cost-sustainability-toxicity landscapes and select routes matching specific project constraints. Benchmark evaluations across multiple retrosynthesis datasets confirm the approach identifies high-quality solutions overlooked by conventional single-objective methods.

The practical implications extend beyond academic interest. As regulatory pressure increases around green chemistry and supply chain optimization, tools enabling rapid multi-criteria evaluation gain competitive value. Future development likely includes integration with commercial synthesis planning platforms and expansion to handle additional objective functions specific to particular industries or regulatory frameworks.

• →MORetro* generates Pareto-optimal synthesis routes balancing multiple competing objectives like cost, sustainability, and toxicity
• →Multi-objective formulation better aligns computational chemistry tools with actual industrial decision-making processes
• →Algorithm provides mathematical optimality guarantees for recovering true Pareto fronts in synthesis planning
• →Approach identifies high-quality solutions single-objective methods overlook across multiple retrosynthesis benchmarks
• →Framework enables rapid evaluation of trade-offs critical for pharmaceutical and chemical manufacturing workflows