We are excited to be attending the Partnership for Cures conference this week with one of our best client partners and advisors, Dr. Mike Berens of TGen. Mike has led the Ivy Genomics Based Medicine project (funded by the Ben and Catherine Ivy Foundation) over the last two years, which has influenced our understanding of the future of science and medicine and given evidence to what we had believed for quite a while in terms of the role of technology.
First, the practice of trying to accumulate all the people, tools and data in one place to drive research to improve health has proven to at least be suspect and completely without ability to scale - even for the largest pharmaceuticals, government agencies, and academic institutions. The Internet and an assortment of underlying technologies have opened the door for overcoming the barriers of scale to create novel pipelines that allow for greater visibility and talent to contribute to the precision necessary to realize personalized medicine.
Second, there is an ebb and flow to what's needed, when. This is a complex project, involving nine institutions, that seeks to understand how genetic differences in individual brain tumors can inform the most effective treatment options. They're looking for fast answers. (More info.) For our own part, in building the technology to support the project, we went through intense iterations with the very different end users over about the first 9 months, to establish the workflows and build the required front-and back-end interfaces. We moved to integrating with data sources, starting first with those institutions that had significant systems where it was more cost effective to integrate (vs. building systems for those who needed them). We then moved to a maintenance mode to let the data flow until the next significant stage, where more direct interaction with patients and their providers will change what we need to do as we drive toward answering the following questions for the next patient with brain cancer:
For our part, we look forward to being part of the teams that will use state of the art platforms to deliver the information needed to inform the participants above about how to treat and ultimately cure glioblastoma. There is no time like the present.
First, the practice of trying to accumulate all the people, tools and data in one place to drive research to improve health has proven to at least be suspect and completely without ability to scale - even for the largest pharmaceuticals, government agencies, and academic institutions. The Internet and an assortment of underlying technologies have opened the door for overcoming the barriers of scale to create novel pipelines that allow for greater visibility and talent to contribute to the precision necessary to realize personalized medicine.
Second, there is an ebb and flow to what's needed, when. This is a complex project, involving nine institutions, that seeks to understand how genetic differences in individual brain tumors can inform the most effective treatment options. They're looking for fast answers. (More info.) For our own part, in building the technology to support the project, we went through intense iterations with the very different end users over about the first 9 months, to establish the workflows and build the required front-and back-end interfaces. We moved to integrating with data sources, starting first with those institutions that had significant systems where it was more cost effective to integrate (vs. building systems for those who needed them). We then moved to a maintenance mode to let the data flow until the next significant stage, where more direct interaction with patients and their providers will change what we need to do as we drive toward answering the following questions for the next patient with brain cancer:
- Glioma Patient: “Is that the best you have to offer me?”
- Neuro-Oncologist: "How do I select the best treatment for my patients?"
- BioPharma: “Of the promising new agents, which should we put into the foreground? Which patients should get our drugs?”
- Clinical Trialist: “How can we prioritize phase I/II agents? Could we stratify our enrolled patients into tailored clinical trials?”
- Academician: “I need relevant disease models and well-validated molecular probes.”
For our part, we look forward to being part of the teams that will use state of the art platforms to deliver the information needed to inform the participants above about how to treat and ultimately cure glioblastoma. There is no time like the present.
