STRATEGIC AI DISCOVERY ALLIANCE PROPOSAL

Quantum Where It Creates Value

innov’SAR Platform: Tools, Libraries, and Capabilities

How INTEGRATES INTO YOUR REAL-WORLD ENVIRONMENTS

The innov’SAR core approach is interpolative, extrapolative and predicts outside-the-box, not found in other state-of-the-art Machine Learning or Deep Learning approaches. The comparison of innov’SAR core with 14 other methods shows that it outperforms these SOTA ML & DL methods in terms of hit rate (81%).

Figure S2: https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/cbic.202000612

Relationship between the hit rate normalized to the log10 number of functionally characterized mutants used for training and the size of the search region explored: comparison of 15 studies. Turquoise blue square: assuming a non-normalized hit rate of maximum value of 1 (incomplete data to have the exact hit rate from the paper) for the CNN model proposed by Xu et al (2020). Purple diamond: The hit rate indicated in the Attention-Based Neural Networks model proposed by Wu et al (2020) is used for comparison.