Imagine being able to turn your own skin cells into a master key that can become any other cell in your body. Right now, making these 'master cells' is slow, expensive, and inconsistent. This project builds a smart, automated machine that uses AI to grow these cells perfectly every time, making personalized medicine much cheaper and faster.
Current autologous iPSC production is too expensive and lacks standardization, leading to high failure rates and limited patient access to personalized regenerative therapies.
An AI-guided microfluidic device for GMP production and a bioinformatics database for selecting high-quality cell clones.
If you are a clinic dealing with high costs and rejection risks in cancer treatments — this project developed an AI-guided microfluidic device that produces personalized iPSCs for autologous adoptive cancer immunotherapies. This allows for mass production of patient-specific cells at a fraction of current costs.
If you are a startup dealing with the lack of standardization in stem cell growth — this project developed a platform that standardizes GMP production. This ensures high-quality clones meet clinical standards for tissue regeneration.
If you are a manufacturer dealing with the inefficiency of manual cell sorting — this project developed AI software and a database to identify the highest quality cell clones. This automates the selection process for hematopoietic stem cell transplantation.
The project aims to produce personalized iPSCs at a fraction of the current cost by using an AI-guided microfluidic device and automation.
Yes, the objective is to enable the mass production of personalized iPSCs through a standardized, automated platform.
Based on available project data, the consortium has created a concrete exploitation plan to develop the technology for implementation in cancer therapy and regenerative medicine.
The platform is specifically designed to standardize GMP (Good Manufacturing Practice) production of autologous iPSCs.
The project period runs from 2022-09-01 to 2026-08-31.
The consortium is heavily industry-weighted with an 80% industry ratio, consisting of 4 companies (including 2 SMEs) and 1 university across 4 countries. This composition suggests a strong focus on commercial viability and translation, led by MIDA BIOTECH BV, combining microfluidics engineering with AI and bioinformatics expertise.
Contact MIDA BIOTECH BV in the Netherlands
Contact us to explore licensing opportunities for the AI-guided microfluidic prototype.
