[Data augmentation in a TTL] - Figure 3 TMAPS // Comparison of USPTO and fictive reactions in terms of chemical space coverage.

Reactions in the US Patent Office (USPTO) are biased towards a few over-represented reaction types, which potentially limits its usefulness for computer-assisted synthesis planning (CASP). To obtain an equilibrated dataset, we applied retrosynthesis templates to USPTO molecules as products (P) to generate starting materials (SM). We then used transformer T2 from our recently reported triple transformer loop (TTL) retrosynthesis model to predict reagents (R) for the SM®P reaction. Finally, we validated the prediction by requesting a high confidence prediction (>95%) for the prediction of P from SM+R by TTL transformer T3. We generated up to 5,000 reactions per template, resulting in 27.5 million validated fictive reactions covering the chemical space of the original UPSTO dataset. To exemplify the use of this dataset, we show that a single-step retrosynthesis transformer model trained with a template equilibrated subset of 1,097,374 fictive reactions outperforms the corresponding model trained on USPTO reactions only.