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AI and machine learning (ML) are transforming drug discovery by making it possible to infer the generalisable principles governing the relationships of protein sequence, structure, and function directly from data. This is the foundational concept of generative biology. Using these principles, it is possible to program novel medicines – proteins that have never existed before – that can treat a variety of diseases in a way that has eluded traditional drug discovery efforts. Recently, the field has advanced significantly with the publication and release of multiple generative diffusion-based models, including Generate:Biomedicines' Chroma model, which enables us to design vastly greater numbers of new proteins and program them for optimum combinations of symmetry, shape, binding affinity, potency, and developability. Generating potential new therapeutics de novo is just the beginning of the cycle of innovation. 
Generate:Biomedicines is combining these designs from our dry lab with data produced in our wet lab from technologies such as cryo-electron microscopy (cryo-EM, to observe the structure in near real time) as well as an array of high-throughput methods focused on assessing functional and biophysical properties. The combination of ML with robust systems for producing and managing terabytes of empirical data, then feeding these results back into The Generate Platform for continuous learning at unprecedented speed and scale, changes the paradigm of drug development. 
In this webinar you’ll discover how the capability to program novel proteins holds promise for bringing new medicines to patients faster, cheaper, and better tailored to their specific conditions and unmet medical needs than before.

An audience Q&A session with the presenter follows the webinar presentation.
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