ASKCOS: an open source software suite for synthesis planning
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Abstract (arXiv)
The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. Here, we detail the newest version of ASKCOS, an open source software suite for synthesis planning that makes available several research advances in a freely available, practical tool. Four one-step retrosynthesis models form the basis of both interactive planning and automatic planning modes. Retrosynthetic planning is complemented by other modules for feasibility assessment and pathway evaluation, including reaction condition recommendation, reaction outcome prediction, and auxiliary capabilities such as solubility prediction and quantum mechanical descriptor prediction. ASKCOS has assisted hundreds of medicinal, synthetic, and process chemists in their day-to-day tasks, complementing expert decision making. It is our belief that CASP tools like ASKCOS are an important part of modern chemistry research, and that they offer ever-increasing utility and accessibility.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Jan 2025.
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Citing papers per year: 2025: 3; 2026: 2.
5 papers.
- 2025LLM-Augmented Chemical Synthesis and Design Decision Programscited by 13
- 2025ChemOrch: Empowering LLMs with Chemical Intelligence via Synthetic Instructionscited by 3
- 2025Fast and scalable retrosynthetic planning with a transformer neural network and speculative beam searchcited by 2
- 2026Training Chemical Plausibility-Aware Large Language Models for Single-Step Retrosynthesiscited by 0
- 2026Molecular LLM Agents: From Architectural Design to Scientific Autonomycited by 0
- 2026Molecular LLM Agents: From Architectural Design to Scientific Autonomy24 Aug 2026
- 2026Training Chemical Plausibility-Aware Large Language Models for Single-Step Retrosynthesis19 Aug 2026
- 2025ChemOrch: Empowering LLMs with Chemical Intelligence via Synthetic Instructions20 Sep 2025
- 2025Fast and scalable retrosynthetic planning with a transformer neural network and speculative beam search2 Aug 2025
- 2025LLM-Augmented Chemical Synthesis and Design Decision Programs11 May 2025