NEWTON Biotwins: Using Digital Twins to Make Cell Analysis Faster, Smarter, and More Reliable

Ángel Goñi.

Agencia Estatal Consejo Superior de Investigaciones Científicas, M.P., Spain.

Flow cytometry is an essential tool in biomedical research and healthcare, enabling analysis of multiple features in individual cells for research, diagnosis and disease monitoring. However, increasing data volume and complexity reduce reproducibility across different settings. This project aims to address this challenge using digital twin technology to make this process more consistent and reliable.

NEWTON Biotwins creates virtual representations of complex flow-cytometry datasets. By modelling the workflow, the technology helps interpret the results more quickly and consistently, reducing unnecessary experimental repetition. In turn, this supports more sustainable research practices and facilitates access to advanced analytical methods across a range of settings.

By improving data quality, reliability and accessibility, this project could accelerate biomedical research into disease mechanisms and support clinical applications for diagnosis and monitoring. Ultimately, the project seeks to make advanced cell analysis more efficient, scalable and accessible for the benefit of researchers, healthcare professionals and patients alike.

STAGE 1