Transfer learning across technologies for ATMPs

Purpose and goal:

Advanced Therapy Medical Products (ATMPs), is a field of treatment that is developing very quickly and that is dependent on good quality controls to guarantee the safety and quality of the products. The purpose and goal of the project is to develop an AI-supported platform based on complex RNA sequencing data to be translated into simpler, faster and cheaper analyzes with qPCR in an industrial quality control process.

Expected results and effects:

An important parameter in all drug production is quality controls, but for products based on living cells, or parts of cells, these differ from ordinary chemical drugs. In the process of cell production, it is important to know that the genetic information has not been changed or mutated during the process. This project will develop quality systems and with the help of AI streamline large and complex data down to simpler and cheaper analyses in order to be able to produce safe ATMP products in an industrialised way.

Approach and implementation:

The project have five work packages. WP1 is responsible for general project management, risk management and dissemination. WP2, cultures the human embryonic stem cells that serve as a model product for our platform and generates the sequencing data.

In WP3, the data from WP2 will be processed and the AI method will be developed. In WP4, the advanced model trained on complex data will be transfered to a more simple qPCR system. The qPCR systems are developed and validated in WP4.

In WP5, the develop systems will be commercialised, including both lab kits and software for data interpretation.