Personalization Of Healthcare & Medicine With Data & AI
Our recorded panel with MD Anderson Cancer Center’s Chief Technology Officer and Chair of Genomic Medicine.
On October 7, Darling Ventures partnered with The Hive to host part two of our three-part series examining the role of data and AI in transforming the US healthcare industry. Part II: Personalization of Healthcare & Medicine with Data & AI (watch our video recording of the panel) featured an expert discussion from two leading innovators from world renowned medical institution MD Anderson Cancer Center:
Andrew Futreal, Ph.D. — Chair of Genomic Medicine, serves vital research initiatives as co-leader of the Translational Research Accelerator, the Cancer Genomics Laboratory and the Adaptive Patient-Oriented Longitudinal Learning and Optimization (APOLLO) platforms. A core focus of Dr Futreal’s is facilitating advanced medical research driven by big data. He has published over 230 papers.
David Jaffray, Ph.D. — SVP and Chief Technology & Digital Officer, the first person to hold that position at the institution Dr Jaffray directs the strategic design, management and implementation of enterprise-wide technology infrastructure at MD Anderson. He draws on two decades of industry experience advancing the digital transformation and innovation across major healthcare institutions in North America, including a prior role as EVP of Technology & Innovation at the University Health Network / Princess Margaret Cancer Centre in Toronto. Dr Jaffray has authored more than 275 publications and is a professor of Radiation Physics.
The panel was moderated by Darling Ventures Managing Partner, Daniel Darling, who sits on MD Anderson’s Advance Team Board.
MD Anderson is a globally significant institution and one of the most innovative forces in advanced medical care. 22,000 employees interact with 1.5M patients each year. Last year alone, the the institution invested over $900M in medical research, conducted approximately 1,400 clinical trails and completed more than 13M lab tests.
The panelists spent the hour discussing the need for personalization in cancer care, what advances are being made in the field that can be applied to the wider healthcare industry and how MD Anderson is leveraging advances in data and AI to innovate and drive groundbreaking outcomes for its patients. Some of our key takeaways include the following:
- Fighting cancer requires personalization as each case presents unique patient DNA, tumor DNA and microbiome
In cancer care we treat one person the same as the next person, to the best of our ability, yet we get a different result…we’re trying to understand what is the cause of that variability.
2. Could our immune system hold the holy grail of personalized treatment?
How do you leverage all of them (targeted therapies) in combination to let the immune system do its best job…and have the patients response system target and eliminate.
3. We are moving toward continuous DNA sequencing and sequencing at birth
It is inevitable…we have to develop the dimensionality and think about this as an ongoing inquisition into the system.
The scale is really substantial from a computing perspective, from a data collection perspective, from an optimization perspective…these are complex and dynamic systems.
4. Achieving data collection integrity and consistency so to expose the precise differences in biology
Standardized data generation so the output is comparable not only within tumor types but across tumor types.
5. Leveraging AI on historical data to drive new insights
Human minds have their limits…we need computers to start to look for correlations across observations…they (computers) are changing the way we look across the data.
6. Using computers to simulate a patients outcome
Detailed computational models is the way to go, like used in the weather paradigm today, but for individual patients is the exciting frontier.
7. Transformative shift in healthcare were more data will be collected outside of a medical institution than within it
How do we collaborate and digitally engage with patients…see them contributing their own information so we can better guide their care…we need new approaches and new technologies.
We’re moving into this era where the patient is a partner in their own care.
8. Internal innovation, external innovation and partnering with the startup ecosystem
How do we bring substantial computation power and models to this problem? We have to partner…industry partners and academic partners.
Put together a framework that makes it clear what the architecture is at an organization for data flow…creates an opportunity to “click-in” different technologies…or “click-out”.