IBM Research Europe and Thieme Chemistry have announced a collaboration that will accelerate the discovery and potential synthesis of compounds for organic chemistry. The RXN for Chemistry cloud platform helps synthetic organic chemists in predicting the outcome of chemical reactions using artificial intelligence (AI) which is trained on data. Thus, a prerequisite for optimal prediction results is high-quality datasets. The cooperation between IBM and Thieme Chemistry aims at improving the prediction outcomes using synthesis data from Thieme's expertly curated digital publication source for organic chemistry - Science of Synthesis.
IBM launched RXN for Chemistry in 2018. The cloud platform uses an AI model called Molecular Transformer which applies neural machine translation models to predict the outcome of a chemical reaction and thus, improve synthesis planning in organic chemistry.
Dr Teodoro Laino, distinguished scientist at IBM Research Europe comments: ‘The challenge for organic chemists is that there are hundreds of thousands of possible reactions of organic compounds. To address this, we used natural language processing models for all RXN prediction tasks. The RXN models have no built-in chemistry and are not based on codified rules. Every chemical prediction is based on the knowledge learned from the data during training. With AI, cloud and automation, today we can accelerate discovery in organic chemistry by a factor of ten.’
Driving technical innovation with high-quality, diverse, and well-structured data
Dr Alain Vaucher, research scientist at IBM added: ‘Tools for translating from one language to another are only as good as the data on which the algorithms are trained. Our assumption is that this is also true for predicting chemical synthesis results: the results depend very much on the underlying data.’
Earlier this year IBM Research and Thieme Chemistry incorporated expert synthesis data from Thieme's expert curated digital publication source on organic chemistry – Science of Synthesis – into RXN for Chemistry and initial results show that Thieme-trained models predict correct reactions twice as often as baseline models when tested on Science of Synthesis chemistry.
Dr Fiona Shortt de Hernandez, senior director product management, strategic partnerships and Science of Synthesis at Thieme Chemistry commented on the collaboration and how the use of AI will benefit scientists. ‘We are pleased to be directly involved in this innovative project, which is of high importance for the chemistry community says Hernandez.
‘Six highly-renowned organic synthesis experts and their groups have agreed to test the retrained models. Together this collaboration will help drive the development of state-of-the-art custom-fit tools for organic chemists,’ Shortt affirms.
‘The collaboration with Thieme is an important landmark between AI solution providers and domain specific data publishers, with important business opportunities for both,’ adds Laino. ‘I am very excited to share these preliminary results and curious to see how they will lead in the next months to an improved AI experience for synthetic organic chemists.’
RXN for Chemistry is available to download for free.
