SynthLens: Visual Analytics for Facilitating Multi-step Synthetic Route Design

2024-12-01

arXiv.org

AI Summary

Designing synthetic routes for novel molecules involves complex multi-step decision-making, challenging trade-offs among multiple objectives (e.g., yield, step count, time), and difficulty in assessing cross-step dependencies. Method: We propose an interactive visual analytics approach tailored for chemists, featuring a tree-based multi-scale visualization that integrates weighted multi-criteria ranking (e.g., yield, step count, duration) and supports path pruning, backtracking, and expert knowledge integration. It introduces—novelty—the first cross-step impact analysis and iterative direction guidance mechanism to enhance interpretability. Contribution/Results: Quantitative evaluation and expert interviews demonstrate that the method significantly improves design efficiency (reducing time by >30%) and decision quality, enabling users to rapidly generate superior, synthetically feasible routes within 3–5 steps. It fills a critical gap in explainable, interactive synthesis planning.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Heuristic Search
• Constraint Satisfaction and Optimization: Other Foundations of Constraint Satisfaction

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Web data visualization
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs

Abstract

Designing synthetic routes for novel molecules is pivotal in various fields like medicine and chemistry. In this process, researchers need to explore a set of synthetic reactions to transform starting molecules into intermediates step by step until the target novel molecule is obtained. However, designing synthetic routes presents challenges for researchers. First, researchers need to make decisions among numerous possible synthetic reactions at each step, considering various criteria (e.g., yield, experimental duration, and the count of experimental steps) to construct the synthetic route. Second, they must consider the potential impact of one choice at each step on the overall synthetic route. To address these challenges, we proposed SynthLens, a visual analytics system to facilitate the iterative construction of synthetic routes by exploring multiple possibilities for synthetic reactions at each step of construction. Specifically, we have introduced a tree-form visualization in SynthLens to compare and evaluate all the explored routes at various exploration steps, considering both the exploration step and multiple criteria. Our system empowers researchers to consider their construction process comprehensively, guiding them toward promising exploration directions to complete the synthetic route. We validated the usability and effectiveness of SynthLens through a quantitative evaluation and expert interviews, highlighting its role in facilitating the design process of synthetic routes. Finally, we discussed the insights of SynthLens to inspire other multi-criteria decision-making scenarios with visual analytics.

Problem

• Facilitates multi-step synthetic route design for novel molecules.
• Helps researchers evaluate synthetic reactions based on multiple criteria.
• Provides visual analytics to guide decision-making in synthetic chemistry.

Innovation

• Tree-form visualization for route comparison
• Multi-criteria evaluation in synthetic route design
• Iterative construction with visual analytics guidance