Drug discovery still relies heavily on animal models and endpoint assays that poorly predict human response and miss time-resolved biology. This leads to high failure rates in clinical trials, long development cycles, and costly late-stage attrition. What's missing is scalable, standardised human-relevant data that captures organoid behaviour over time and can power predictive, AI-ready models.
Our founding team combines organoid biology, automation/data engineering, and early-stage venture experience. We build a high throughput, scalable organoid data platform that automates time-series phenotyping and turns experiments into structured datasets and predictive models. We target the multi-billion-dollar drug discovery and preclinical testing market.