Dealing with Big Genomic Data: Towards Predictive & Preventative Medicine

Transcription

1 YOUR LOGO Open Source EHR Summit & Workshop Dealing with Big Genomic Data: Towards Predictive & Preventative Medicine Christophe Lambert, PhD CEO October 18, 2012

2 The challenge How to make a systemic shift to genomic-enabled predictive and preventative medicine? Genetic Research Clinical Decisions Societal Adoption

3 Challenges in managing any system Managing COMPLEXITY Managing UNCERTAINTY Managing CHANGE & CONFLICT

4 COMPLEXITY

5 COMPLEXITY in Genetic Research Twenty years ago, there was one requirement: General knowledge of biology and genome sciences.

6 Conducting Genetic Research Today genetic research is computational, more complex, and requires a vast skillset: Ability to develop software encapsulating new analysis methods. Understanding of relational databases and database architecture. An understanding of parallel computing environments for UNIX clusters. Understanding of a scripting language such as Perl. Knowledge of network-based data storage. General knowledge of biology and genome sciences. An intimate knowledge of UNIXbased operating systems. Ability to seek out and test novel bioinformatics software and analysis routines. Ability to derive data analysis and software requirements from investigators who do not have a sophisticated understanding of information technology. Source: Richter BG, Sexton DP (2009) Managing and Analyzing Next-Generation Sequence Data. PLoS Comput Biol 5(6): e

7 Data Collection is Changing Rapidly Time

8 As Data Collection Costs Decrease, Computational and storage Demands Increase Source: Stein LD. The case for cloud computing in genome informatics. Genome Biol. 2010;11(5):207. Epub 2010 May 5.

9 Dearth of data scientists We are not the first field to face a data deluge Physical infrastructure challenges are solvable albeit expensive The real challenge is insufficient data scientists The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data.

10 Analytics and research productivity VS.

11 Authors/publicaiton Complexity drives increase in collaboration 7 Authors/publication for NIH-sponsored research Year

12 Publications/author/year $/Publication Teamwork vs. Collaboration Impact on research productivity Teamwork = division of labor Collaboration = Teamwork + synthesis NIH sponsored publications / Unique author names NIH budget (year n-4) / NIH sponsored publications $400,000 $350,000 $300,000 $250,000 $200, $150,000 $100,000 $50,000 $0 Year Year

13 Improving collaboration Division of labor - Pro: Allows us to consider the parts independently - Con: Increases the number of interfaces - Con: Loses sight of global properties not present in subsystems Improving integration and synthesis - Interface management, abstraction & modeling - Shared vocabulary and boundary objects - Parity of relative expertise - Have a self-interest in each others success

14 Researchers Dilemma Be a prominent secure scientist Retain autonomy, control and credit Solve complex problems Collaborate less Specialize Collaborate more Synthesize

15 UNCERTAINTY

16 Impact of big genomic data on uncertainty Cytogenetics - 20 years ago: karyotyping and FISH: 3-5% clinical yields. Certain but help few. - Today with microarrays 20%+ clinical yields. Help more but less certain. - Consensus Statement: Chromosomal Microarray Is a First-Tier Clinical Diagnostic Test for Individuals with Developmental Disabilities or Congenital Anomalies. The American Journal of Human Genetics, Volume 86, Issue 5, , 14 May Sequencing - Promises increased clinical yields - Many more signals of unclear significance - Binary certainty a pipe dream

17 Clinical Dilemma Reduce errors of commission Use lower resolution genetic assay Give patient the best treatment Reduce errors of omission Use higher resolution genetic assay

18 Symptoms of the conflict No findings = normal karyotypes Different lab thresholds for excluding deletions and duplications. Varying physician tolerance for known and unknown variants Labs providing varying levels of resolution and/or masking regions to limit uncertainty, with different rules for prenatal testing Imperfect penetrance and interaction effects are both acknowledged and ignored. When a known pathogenic variant is identified, there is a tendency to ignore other variants of less clear significance. Cytogeneticists are conflicted over stating a variant is possibly or probably pathogenic when doctors are then likely to consider the case closed, or parents likely to cling to these judgment calls that may later be determined erroneous.

19 CHANGE & CONFLICT

20 Four aspects of change Overcoming Resistance to Change - Isn't It Obvious?

21 Change management for the patient Genomic-enabled early disease detection and prevention Positive for Patients of deciding to have early disease detection and prevention live longer have less pain and suffering have more time to prepare for death have less illness & more productive life - years protect and prepare your loved ones from your unexpected or premature death spend less on healthcare over the long run gain a longer healthier more secure life have [genomic - enabled] early disease detection and prevention Negative for Patients of deciding to have early disease detection and prevention have increased expenses when healthy be subject to frequent, invasive, and possibly painful testing have to think about health and mortality when not sick or dying become a patient when not sick Positive for Patients of deciding to keep the status quo live life in the moment not worry about the future spend little time and resources on healthcare while healthy keep living short - term and avoiding anxiety about death keep the status quo Negative for Patients of deciding to keep the status quo risk dying from diseases that are caught too late have expenses of late stage disease treatment have suffering from late stage disease treatment keep having avoidable suffering and death

22 Change management for all stakeholders Patients, Medical professionals, Hospitals & Clinics, Insurance providers, Government officials Positive for all of deciding to have early disease detection and prevention Patients : gain a longer healthier more secure life Medical : gain better patient outcomes Hospitals : generate individual health and institutional prosperity Insurance : provide more value/$ for patients Government : improve fiscal and population health gain more individual and institutional health and prosperity have [genomic - enabled] early disease detection and prevention Negative for all of deciding to have early disease detection and prevention Patients : become a patient when not sick Medical : risk loss of identity, status and/or income Hospitals : jeopardize institutional security Insurance : gain financial and regulatory risks Government : supervise huge, expensive, risky, thankless change efforts risk individual and institutional identity and security Positive for all of deciding to keep the status quo Patients : keep living short - term and avoiding anxiety about death Medical : be a hero in the battle against disease Hospitals : be financially stable Insurance : have a stable profitable business Government : retain employment and influence enjoy present individual and institutional health keep the status quo Negative for all of deciding to keep the status quo Patients : keep having avoidable suffering and death Medical : have limited impact on patient health Hospitals : have little leverage to improve patient outcomes Insurance : have limited shareholder growth and security Government : have healthcare & fiscal crises have preventable individual and institutional disease

23 Two fundamental conflicts in change management Security Don t Change Live long and prosper Growth Change Live long and prosper together I/Me Needs Us/We Needs Not Change Change Change Not Change

24 Conclusion Complexity - Beware imposing a false simplicity Uncertainty - Beware imposing a false certainty Change & Conflict - Beware imposing on each other How to make a systemic shift to genomic-enabled predictive and preventative medicine? Genetic Research Paradigm shifts take time Clinical Decisions Societal Adoption