Dragonase utilizes machine learning and robotics to rejuvenate bone marrow hematopoietic stem cells in vitro, enhancing their viability and functionality. This technology addresses the decline in stem cell efficacy due to aging or environmental factors, potentially improving outcomes in regenerative medicine and transplantation.
Funding
Funding not disclosed
Founders
Product
Problem
The efficacy of bone marrow hematopoietic stem cells declines due to aging and environmental factors, reducing their viability and functionality. This decline negatively impacts the success of regenerative medicine and transplantation procedures.
Solution
Dragonase employs machine learning and robotics to rejuvenate bone marrow hematopoietic stem cells in vitro. The technology enhances the cells' viability and functionality, counteracting the negative effects of aging and environmental stressors. By improving the quality of stem cells, Dragonase aims to improve outcomes in regenerative medicine and transplantation.
Target Audience
The primary target audience includes researchers and clinicians in regenerative medicine and transplantation, as well as cell therapy companies.
Features
- Machine learning algorithms to identify and optimize rejuvenation protocols.
- Robotic systems for automated cell manipulation and processing.
- In vitro cell rejuvenation process specifically targeting bone marrow hematopoietic stem cells.