Digital Twins of Humans to Solve Medicine's Data Availability Problem

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Digital Twins of Humans to Solve Medicine's Data Availability Problem

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Mantis Biotech claims it is developing the solution to fill the data availability gap in medicine. The company's platform first takes data from a variety of sources such as textbooks, motion capture cameras, biometric sensors, training logs, and medical imaging. Then it uses an LLM-based system to route, validate, and render that data into predictive models for how people are going to perform. The physics engine layer is key because it helps the platform enhance the available data and regenerate models. Since Mantis' platform fills gaps in data sources, there is potential for it to be used widely across the biomedical industry where information on procedures or patients can be difficult to access, is unstructured, or siloed. The company is also working to cater to pharmaceutical labs and researchers working on FDA trials. The startup recently raised $7.4 million in seed funding led by Decibel VC, with participation from Y Combinator.

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