Edited by Chance Lai
______
Taiwan is strengthening its regenerative medicine ecosystem through a new partnership between the Taiwan Regenerative Medicine Alliance (TRMA) and National Yang Ming Chiao Tung University (NYCU), bringing together expertise in biomedical engineering, artificial intelligence, clinical medicine, and semiconductor technologies to accelerate next-generation healthcare innovation.
The two organizations recently signed a memorandum of understanding (MOU), marking a new phase of collaboration across academia, industry, research institutions, and healthcare providers. Witnessed by the Taiwan Institute of Economic Research (TIER), the agreement aims to build a more integrated innovation ecosystem that translates scientific discoveries into clinical and industrial applications while enhancing Taiwan’s international competitiveness.
Integrating Engineering and Medicine
Since the 2021 merger of National Yang-Ming University and National Chiao Tung University, NYCU has combined its strengths in medicine, life sciences, engineering, and information and communication technologies to develop innovative healthcare solutions.
NYCU President Chi-Hung Lin said the university continues to leverage this interdisciplinary foundation to advance smart healthcare, biomedical engineering, and regenerative medicine.
“By integrating engineering, medicine, and digital technologies, NYCU is creating new opportunities for innovation in regenerative medicine,” Lin said. “Through collaboration with industry and research partners, we hope to accelerate technological translation, cultivate future talent, and strengthen Taiwan’s global competitiveness.”
As one of the alliance’s key academic partners, NYCU will contribute expertise in BioICT biomedical chips, AI-enabled healthcare, automated stem cell manufacturing, and translational biomedical research.
Among its flagship technologies is a semiconductor-based BioICT platform that integrates microfluidics, capacitive sensing, temperature control, and microscopic imaging onto a single chip. Designed using Taiwan’s semiconductor manufacturing technologies, the platform enables automated cell quality analysis while improving production efficiency and reducing manufacturing costs.
The technology has already been adopted by the CiRA Foundation at Kyoto University in Japan for automated quality assessment of induced pluripotent stem (iPS) cells, highlighting its potential for international regenerative medicine applications.
Building the Next Generation of Smart Biobanking
A major focus of the partnership will be developing a Next-Generation Intelligent Biobank (NGIB) capable of storing up to 500,000 biological samples.
Unlike conventional biobanks that rely heavily on manual operation, the proposed platform combines fully automated ultra-low-temperature storage with NYCU’s proprietary BioICT Quality Control (QC) Chip and AI-powered predictive maintenance technologies. The system is expected to improve storage efficiency, quality management, and long-term reliability while transforming Taiwan’s semiconductor expertise into advanced biomedical infrastructure for regenerative medicine.
The collaboration will also expand AI-assisted drug discovery through NYCU’s College of Pharmaceutical Sciences, where researchers use biomedical databases and machine learning algorithms to predict interactions between therapeutic compounds and biological targets, helping shorten the early stages of drug development.
In parallel, NYCU Hospital will work toward developing clinical operations that align with international ISO certification and PIC/S Good Manufacturing Practice (GMP) standards, laying the foundation for future international collaboration in regenerative medicine.
Bringing Semiconductor Innovation to Regenerative Medicine
One of NYCU’s key contributions to the alliance will be its semiconductor-based biomedical chip technologies.
Developed using Taiwan Semiconductor Manufacturing Company (TSMC)’s standard semiconductor fabrication process, the BioICT platform integrates microfluidics, capacitive sensing, temperature control, and microscopic imaging into a single chip. The technology enables automated cell quality analysis while improving manufacturing efficiency and reducing production costs.