#AGBTPH – John Mattison, The last mile of precision medicine: Big challenges, big opportunities

[John Mattison is from Kaiser Permenante.  I had the opportunity to meet him at lunch today, and was blown away by his perspective, which is really broad and not what I expected from someone at an insurance company.  I also learned about “sitting is the new cancer” from him.  Lots of food for thought.]

Audience questions, who’s downloaded their own EHR? Used Open Notes?  Sequenced Exome? Sequenced Gnoe?  Donated to open research project? 50% of physicians are burned out?  Understand what potentially actionable variants means to physicians? Did you know that Genome research, PHR and bitcoin all share a technology.

Thee natural metaphors:

  • Big Bang:  data expanding at ever increasing rates.
  • Meiosis: an incredible innovation engine. (massive mash up of ideas)
  • Tropical Rainforrest: very poor soil, but have maximum genetic diversity and maximum on conversion/capture of sunlight.

Human Microbiolme Complexity  – BIG part of little data.  100 diseases with microbiologic signatures.  It’s all connected and will be medically relevant.  No such things as a “common” disease.

So many -OMES!   And whole ecosystem of platforms from data, to economic and cognitive… all share exponential growth, but synergistic and convergence.  Have to put all of the data together, and linked for common individual – if you don’t work out how to associate together to make sense of them, you’re losing out.

How many genomes to we need to get to the bottom of disease? More viable genomes that are possible than there are people who have walked on earth.  There is no such thing as a cohort large enough to solve everything.   Example with Autism and speculation about a Homeobox.. neat but too much to jot down.

How do we achieve interoperability, given that there are too many standards?  There are families of use cases that need different representations.  we probably have 10x as many representation than we need.  May need some Darwinian evolution to winnow down.

How do we exploit evidence based practice and practice based evidence?  All about accelerating learning and cycle times.  Clinical practice and data capture -> Analytics modelling and Simulation -> Decision support -> back to clinical practice.  Genetics is only 33%  of early death. [?]

How do we integrate genetic decision support with other -omics without further burning out physicians?  Have to have a really functional and effective integration with EHRs.

Truly informed consent:  Pet issue – GINA left out insurance industry and long term care and disability.    Need to go back an put that in – people who consent for genomic sequencing, and have genomic issues may legally be discriminated against by those industries.

Social aspects – 3 conversations that need to happen:

  • Patient and professional heath care team (inc. genetic councillor)
  • Person with Personal Care team.
  • Patient with the person that houses the patient persona. “Person-centricity”

(Diabetes example.  How does treatment happen? Drugs, vs lifestyle, how do we include genomics?)

Geo-fencing -> Geno-fencing. [New term for me!]

The future: Child gets sick, parents swab child and sequence the DNA of the virus or bacteria, and then get a prescription that targets the exact agent… and medicine is delivered by drone.

Global Alliance for Genomics & Health.  If you aren’t involved, you should be.  Work together for better data sharing.  Slides available on the Github for the Global Alliance.

They use blockchain – can be used to identify cohort, and then trace back to institute and consent agreement.  Hash is one way, of course, so ID is impossible to decrypt.  Can be used by physicians to see everything that’s currently known about people who share a single variant. Public data open and available to all, not corruptible.

Spread like the internet: Every additional node increases the value of the network.

Data can come from anywhere – participant works with a trusted steward to get data into project.

We need this because trust is local. Very efficient, effective low cost way to do research and work with patient.  Can’t be owned by single government.  Makes everything public, but without central authority or government control.

[Awesome visionary talk! One of my favourites from the day.]

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