Platform technologies

AI-guided INTENDD^®

AI x INTENDD^® – prediction of activity and beyond –

Small molecules (PPI modulators) designed by AI-guided INTENDD^® will not require further activity optimization

AI-guided INTENDD^® drastically improves drug discovery productivity of hit identification to lead optimization by predicting the binding pose of small molecule to target protein and separating its activity into 8 classes of 3-digits pmol/L to 1-digit mmol/L orders.

Background in silico screening system of AI-guided INTENDD^® is INTENDD^®(SBDD strategy including binding mechanism-based in silico screening; enthalpy and entropy considered screening system). It has a strength of zero to one, so, unnecessary tool or hit information as hint. And it continues to evolve.

Separation of activity into 8 classes by AI-guided INTENDD^® enables to eliminate the need for the enormous cycle of compound synthesis and evaluation in the conventional drug discovery processes. In an improved process by AI-guided INTENDD^®, medicinal chemists can lean activity of designed compounds without those synthesis and evaluation, and for example it is only necessary to synthesize the highly active compounds that are separated into Class 0 to 2. Such approach is expected to contribute to the efficient evaluation for selectivity, toxicity, DMPK and so on.