In addition to providing pilot grant opportunities, Translational Innovator develops and studies processes for using novel external collaborations to address the bottlenecks that may impede translational success. Translational Innovator together with the Laboratory for Innovation Science at Harvard (LISH) have developed the expertise (in reframing questions, curating data and developing evaluation metrics) needed to allow non-biomedical computational experts to address translational research problems.
We will continue to work to identify algorithmic/computational and other bottlenecks suitable for external input into solutions, and will experiment with their contexts and procedures to improve the understanding and optimize the value of these tools to translational researchers.
Algorithmic Challenge: Lung Cancer
Two-part challenge to create and test automatic delineation algorithms that can improve treatment of cancerous lung tumors.
Ideation Challenge: Cancer
Call for ideas to help cancer patients.
Ideation Challenge: Data
Identifying human health problems that might be resolved using big data and a computational solution.