Timely experimental confirmation of predictions from our AI-driven Centaur system is critical for success. Only with continual feedback between experiment and prediction can Machine Learned models be refined and projects progressed.
Our systems have been built with the flexibility to incorporate a range of experimental data. Here we describe three areas of particular interest; Exscientia’s in-house biophysical fragment screening using Surface Plasmon Resonance, application to 3D structure enabled projects and opportunities for high-content Phenotypic drug discovery.