ArticleACS central science2022
Bayesian Optimization of Computer-Proposed Multistep Synthetic Routes on an Automated Robotic Flow Platform.
Article in ACS central science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- Transfer learning for reaction optimisation: overview of its applications and limits.Chemical science · 2026Review
- The past, present and future of self-driving laboratories.Nature reviews. Chemistry · 2026Review
- Combining High-Throughput Experimentation and Automated Flow for Bayesian Optimization of a Metallaphotoredox Reaction.Angewandte Chemie (International ed. in English) · 2026Article
- Encapsulated droplet array for intensified micromole-scale high-throughput reaction screening.Nature communications · 2026Article
- Transforming Molecular Science With Large Language Models: From Molecule Understanding to Autonomous Scientific Discovery.Chemistry, an Asian journal · 2026Review
- Review
- The architecture of computational antiviralism: a multi-scale framework from molecular targeting to viral ecosystem engineering.Molecular diversity · 2026Review
- The Impact of Continuous Flow Technology and Collaboration between Academia and Industry.JACS Au · 2026Review
- Review
- The ADePT framework for assessing autonomous laboratory robotics.Communications chemistry · 2026Review
- Homogeneous catalysis in continuous flow integrating photocatalysis, electrocatalysis, and automation technologies.Communications chemistry · 2025Review
- Article
- Advancing genetic engineering with active learning: theory, implementations and potential opportunities.Briefings in bioinformatics · 2025Review
- IvoryOS: an interoperable web interface for orchestrating Python-based self-driving laboratories.Nature communications · 2025Article
- ASKCOS: Open-Source, Data-Driven Synthesis Planning.Accounts of chemical research · 2025Article
- Uncertainty quantification with graph neural networks for efficient molecular design.Nature communications · 2025Article
- Article
- Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning.Beilstein journal of organic chemistry · 2025Review
- Article
- Advancing Rare-Earth (4ACS sustainable chemistry & engineering · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computer-aided synthesis planning (CASP) tools can propose retrosynthetic pathways and forward reaction conditions for the synthesis of organic compounds, but the limited availability of context-specific data currently necessitates experimental development to fully specify process details. We plan and optimize a CASP-proposed and human-refined multistep synthesis route toward an exemplary small molecule, sonidegib, on a modular, robotic flow synthesis platform with integrated process analytical technology (PAT) for data-rich experimentation. Human insights address catalyst deactivation and improve yield by strategic choices of order of addition. Multi-objective Bayesian optimization identifies optimal values for categorical and continuous process variables in the multistep route involving 3 reactions (including heterogeneous hydrogenation) and 1 separation. The platform's modularity, robotic reconfigurability, and flexibility for convergent synthesis are shown to be essential for allowing variation of downstream residence time in multistep flow processes and controlling the order of addition to minimize undesired reactivity. Overall, the work demonstrates how automation, machine learning, and robotics enhance manual experimentation through assistance with idea generation, experimental design, execution, and optimization.
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Registered trials
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