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We focus on a world where biomedical research is about to fundamentally change. We think it will be often conducted in an open, collaborative way where teams of teams far beyond the current guilds of experts will contribute to making better, faster, relevant discoveries
helping data users work together, when they don’t work together.
TCGA Pan-Cancer Consortium
doi:10.7303/syn1710680.4
TCGA Pan-Cancer Consortium
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Selected Hosted Consortia and Projects
DREAM challenges
NIH-Alzheimers Accelerating Medicines Partnership
Common Mind Consortium
Cancer Genome Atlas Pan-Cancer Consortium
Colorectal Cancer Subtyping Consortium
1.
machine learning is coming for research…
a different approach to hypothesis formation…
requires sample scale, longitudinally…
To predict whether or not we’ll click on ads, Facebook / Amazon / Google use sample sizes in the hundreds of thousands.
To predict whether or not we’ll click on ads, Facebook / Amazon / Google have longitudinal data on individuals.
where i’ve been, where i’m going
689,003 people
from 1800 to 100,000
individual progression
high-dimension “medical thing” data
62 y old Man 67 y old Woman
same medicine, different impacts
“loads and reliefs” affect the efficacy of medication on individual levels
radical honesty > radical restrictions
informed consent is the key.
2.
how can we increase informedness in mobile or
digital consent?
(not informed consent)
comprehensionlanguagetimeformat
regulatoryliability
1. series of interviews and requirements gathering
2. interaction design process and prototyping
3. consent development
gaitbalancevoicetapping
1. tiered information access by participants
2. “pictorial” dominant on first information tier
3. text dominant on second information tier
4. require perfect score on short assessment
initial metaphor
mPower (Parkinsons Disease)
Share the Journey (Breast Cancer Survivor)
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study “narrative”
screen structure
navigation to/from reinforces concept
changeable by participant
>70,000 enrolled since 9 March
(~75% choose to share broadly)
iconographic representations of key concepts in informed consent
open source methods
design layouts
workflows
web templates and assets
3.
implications for practitioners
is a design illuminating, or obscuring?
drawing eyes to second cheapest
ticket
where’s the line between hope and hype?
where’s the line between patient engagement and targeting?
