Accelerating the discovery of next-generation cancer therapeutics through exploring protein fitness landscapes using a machine learning-driven evolution engine

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LabGenius uses robotic automation, synthetic biology and advanced machine learning to explore protein fitness landscapes and improve multiple drug properties simultaneously. LabGenius' mission is to accelerate the discovery of next-generation therapeutic antibodies by pioneering the development of a smart robotic platform ('EVA') that is capable of designing, conducting and, critically, learning from its own experiments.The current **state-of-the-art** is sequential optimisation, which takes a long time and is less effective. No-one else is currently using a data-led approach to TCE optimisation and LabGenius' highly multidisciplinary team of data-scientists alongside the robotics set-up are well ahead of others' capabilities. However, they are currently not able to optimise T-cell engaging domains because large amounts of data (gathered in-house, drawing heavily on team and resources) are required for training and developing this capability.