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

LabGenius使用机器人自动化、合成生物学和先进的机器学习来探索蛋白质适应性景观，同时改善多种药物特性。LabGenius的使命是通过开拓智能机器人平台（EVA）的开发来加速下一代治疗性抗体的发现，该平台能够设计、实施并从自己的实验中学习。目前** *先进的**是顺序优化，耗时长，效率较低。目前还没有其他公司使用数据为主导的方法来优化TCE， LabGenius的多学科数据科学家团队以及机器人设备的能力远远领先于其他公司。然而，他们目前无法优化t细胞接合域，因为培训和开发这种能力需要大量的数据（内部收集，大量的团队和资源）。

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.