national cancer policy forum summit - warren kibbe keynote november 2013
DESCRIPTION
Discussion of national policy issues relevant for cancer research. Consent, data access, privacy.TRANSCRIPT
Opportuni)es for Posi)vely Impac)ng Cancer Care – an informa)cs perspec)ve
Warren A. Kibbe, PhD [email protected] Center for Biomedical Informa)cs and Informa)on Technology Na)onal Cancer Ins)tute
hHp://wiki.bioinforma)cs.northwestern.edu/index.php/Warren_Kibbe
Three policy issues • Informed Consent – what should it enable? Does it?
• Iden)fica)on of specimens and data. What is privacy? How do we share appropriately? Is that a consent issue?
• Open access to data – how can we respect the desire of pa)ents to share their specimens and data to make truly transforma)ve inference and observa)ons?
Outline
Disrup)ve technologies GeQng social What is big data? Open access to data
Disrup2ve Technologies
• Printing
Access to knowledge – democra)za)on of learning
Disrup2ve Technologies
• Printing • Steam power
Move from human power or animal power to hundreds of horsepower per person
Disrup2ve Technologies
• Printing • Steam power • Transportation
Easy distribu)on of goods
Disrup2ve Technologies
• Printing • Steam power • Transportation • Electricity
Easy distribu)on of energy
Disrup2ve Technologies
• Printing • Steam power • Transportation • Electricity • Antibiotics Reduced the impact of secondary
infec)ons. Huge change in life expectancy
Disrup2ve Technologies
• Printing • Steam power • Transportation • Electricity • Antibiotics • Semiconductors &VLSI design
Digital Compu)ng Density of devices
Disrup2ve Technologies
• Printing • Steam power • Transportation • Electricity • Antibiotics • Semiconductors &VLSI design • http
Hyperlinking!
Disrup2ve Technologies
• Printing • Steam power • Transportation • Electricity • Antibiotics • Semiconductors &VLSI design • http • High throughput biology
Systems view -‐ end of reduc)onism?
Disrup2ve Technologies
• Printing • Steam power • Transportation • Electricity • Antibiotics • Semiconductors &VLSI design • http • High throughput biology • Ubiquitous computing Everyone is a data provider
Data immersion
6.6B ac2ve mobile contracts 1.9B smart phone contracts 1.1B land lines
US: 345M ac2ve mobile contracts 287M smart phone contracts
GeIng Social • Measuring behavior across a population • Understanding behavior – can we provide better
risk estimates for individuals? • Social media is a big data opportunity – what are
the ethics of big data? • Synergize with the energy and immediacy of
patient advocates • Patients want more data sharing – how can we
facilitate that appropriately? This changes trial design – sta)s)cs un)l now has been focused on how to design an appropriate sample so that the sample can be generalized to the popula)on – what happens when we measure the ENTIRE popula)on ??
Big Data
• To me, Big Data is about emergent proper)es • Big Data with social media changes the sta)s)cal paradigm – rather than modeling if a given sample is representa)ve of the popula)on, you have all the data from the popula)on!!
• To accelerate solving real problems in cancer we must combine systems biology, social data (behavior and exposure) with clinical care and outcomes from healthcare providers
The future
• Elastic computing ‘clouds’ • Social networks • Big Data analytics • Precision medicine • Measuring health • Practicing protective medicine
Learning systems that enable learning from every cancer patient
Seman)c and synop)c data
Intervening before health is compromised
Open Data Access
• We need to provide data access to people outside of biomedicine who have the skills and training to mine and analyze data
• More access will mean more innova2on
Precision Oncology
• The era of precision medicine and precision oncology is predicated on the integra)on of research, care, and molecular medicine and the availability of data for modeling, risk analysis, and op)mal care
How do we re-‐engineer transla8onal research policies that will enable a true learning
healthcare system?
Consent • In a learning healthcare system, we ‘learn’ from every pa)ent who comes in for treatment. What is consent in this model? What is research?
• What role is there for standardized consent? • Are there ways to reimagine transla)onal research without consent? Would that help us?
Iden2fying informa2on • Equa)ng genomic data with a fingerprint is appropriate
• Privacy needs to be respected • If a pa)ent consents to release genomic data, how can we lower the barriers to accessing and analyzing their data and genomes?
Data access • How do we lower the barriers for accessing research data, including molecular informa)on?
• Much clinical data belongs to the pa)ent, but pa)ents should have the right to provide data and specimens for the public good. How can we honor that request? Is this a way to promote appropriate, low barrier data access? If we can provide pa)ents with the ability to change their level of approval over )me, how does that impact consent?
Ques2ons • Are there beHer models for standardized consent? Are there ways to reimagine transla)onal research without consent
• If pa)ents consent to release genomic data, how can we lower the barriers to accessing and analyzing their data and genomes? These data are inherently iden)fying.
• How do we lower the barriers for accessing research data? Access to individual-‐level data is cri)cal for precision medicine, but is mired in regula)ons even with appropriate consents are in place.