The document discusses the intersection of precision medicine, biomarkers, and healthcare policy. It describes how biomarkers and -omics data can be used for precision medicine to improve diagnostic accuracy, deliver targeted therapies, and stratify patient populations. However, clinical validation of biomarkers now requires large datasets and years of studies due to regulatory and payer requirements. This has reduced incentives for diagnostic innovation. The document also discusses challenges around clinical interpretation of complex multi-omic tests, evolving medical training and workflows, and disconnects between patent and reimbursement policies.
Computational challenges in precision medicine and genomicsGary Bader
Genomics is mapping complex data about human biology and promises major medical advances. In particular, genomics is enabling precision medicine, the use of a patient's genome and physiological state to improve therapeutic efficacy and outcome. However, routine use of genomics data in medical research is in its infancy, due mainly to the challenges of working with "Big data". These data are so complex and large that typical researchers are not able to cope with them. Collectively, these data require an understanding of many aspects of experimental biology and medicine to correctly process and interpret. Data size is also an issue, as individual researchers may need to handle tens of terabytes (genomes from a few hundred patients), which is challenging to download and store on typical workstations. To effectively support precision medicine, scientists from a wide range of disciplines, including computer science, must develop algorithms to improve precision medicine (e.g. diagnostics and prognostics), genome interpretation, raw data processing and secure high performance computing.
Forum on Personalized Medicine: Challenges for the next decadeJoaquin Dopazo
Bioinformatics and Big Data in the era of Personalized Medicine
10th Anniversary Instituto Roche Forum on Personalized Medicine: Challenges for the next decade.
Santiago de Compostela (Spain), September 25th 2014
Towards Digitally Enabled Genomic Medicine: the Patient of The FutureLarry Smarr
12.02.22
Invited Speaker
Hacking Life
TTI/Vanguard Conference
Title: Towards Digitally Enabled Genomic Medicine: the Patient of The Future
San Jose, CA
Computational challenges in precision medicine and genomicsGary Bader
Genomics is mapping complex data about human biology and promises major medical advances. In particular, genomics is enabling precision medicine, the use of a patient's genome and physiological state to improve therapeutic efficacy and outcome. However, routine use of genomics data in medical research is in its infancy, due mainly to the challenges of working with "Big data". These data are so complex and large that typical researchers are not able to cope with them. Collectively, these data require an understanding of many aspects of experimental biology and medicine to correctly process and interpret. Data size is also an issue, as individual researchers may need to handle tens of terabytes (genomes from a few hundred patients), which is challenging to download and store on typical workstations. To effectively support precision medicine, scientists from a wide range of disciplines, including computer science, must develop algorithms to improve precision medicine (e.g. diagnostics and prognostics), genome interpretation, raw data processing and secure high performance computing.
Forum on Personalized Medicine: Challenges for the next decadeJoaquin Dopazo
Bioinformatics and Big Data in the era of Personalized Medicine
10th Anniversary Instituto Roche Forum on Personalized Medicine: Challenges for the next decade.
Santiago de Compostela (Spain), September 25th 2014
Towards Digitally Enabled Genomic Medicine: the Patient of The FutureLarry Smarr
12.02.22
Invited Speaker
Hacking Life
TTI/Vanguard Conference
Title: Towards Digitally Enabled Genomic Medicine: the Patient of The Future
San Jose, CA
Bioinformatics in the Clinical Pipeline: Contribution in Genomic Medicineiosrjce
In this review report we like to focus on the new challenges in methodology of modern biology be
used in medical science. Today human health is a primary issue to cure disease, undoubtedly the answer to this
is bioinformatics or (In-silco) tools has change the concept of treating patients to understand the need of
genomic medicine in use. Those with new modes of action in clinical treatment, is a major health concern in
medical science. On global prospective scientific role in constructing new ideas to remediate health care to
treat disease exciting in nature is challenging task. So awareness needs to accelerate store clinical datasets for
scientific represents to design genomic drugs. This new outline will drive the medical to discover public data
and create a cognitive approach to use technology cheaper at cost effective mode.
The Foundation of P4 Medicine Keynote Presentation as presented by Leroy Hood, M.D., PhD, at the Ohio State University Personalized Health Care National Conference 2010.
Dr. Leroy Hood lectured to a group of Ohio State University College of Medicine students and faculty on May 13, 2010 in advance of an announcement of a partnership between the Ohio State University Medical Center and the Institute for Systems Biology. The partnership will be known as
Big Data and Genomic Medicine by Corey NislowKnome_Inc
View the webinar at: http://www.knome.com/webinar-big-data-genomic-medicine. This presentation covers an overview of genomic medicine, requirements and challenges of next-generation sequencing, bottlenecks to broader healthcare adoption, and why “we want to sequence everyone.”
P4 Medicine: A Vision For Your Molecular HealthSachin Rawat
Medicine is undergoing tremendous change. Unlike today, medicine of tomorrow would be pro-active rather than reactive.Medicine would be personalized to individual patient's genome. It would predict, and hence prevent, diseases even before they manifest. Also, this medicine would require active societal participation to bring it from labs to clinics.
FDA NGS and Big Data Conference September 2014Warren Kibbe
Presentation for the FDA NGS and Big Data Conference September 2014 held on the NIH campus. NCI initiatives, including Cancer Genomics Data Commons, NCI Cloud Pilots, big data issues for cancer
National Cancer Data Ecosystem and Data SharingWarren Kibbe
Grand Rounds at the Siteman Cancer Center at Washington University. Highlighting the Genomic Data Commons and the National Cancer Data Ecosystem defined by the Cancer Moonshot Blue Ribbon Panel
Advancing Innovation and Convergence in Cancer Research: US Federal Cancer Mo...Jerry Lee
Special Seminar at the 8th Taiwan Biosignatures Workshop to share overall work of NCI's Center for Strategic Scientific Initiatives since 2003 as well as CSSI's influence on select projects initiated by the 2016 WH Cancer Moonshot Task Force that include Applied Proteogenomics Organizational Learning and Outcomes (APOLLO) network, International Cancer Proteogenome Consortium, and the Blood Profiling Atlas in Cancer (BloodPAC) commons.
Kim Solez Introduction to regenerative medicine Fall 2015Kim Solez ,
Dr. Kim Solez presents "Introduction to Regenerative Medicine" on September 10, 2015 in the Technology and Future of Medicine course LABMP 590 http://www.singularitycourse.com at the University of Alberta in Edmonton, Canada. Copyright (c) 2015, JustMachines Inc.
tranSMART Community Meeting 5-7 Nov 13 - Session 3: The TraIT user stories fo...David Peyruc
tranSMART Community Meeting 5-7 Nov 13 - Session 3: The TraIT user stories for tranSMART
The TraIT user stories for tranSMART
Jan-Willem Boiten, TraIT
The Translational Research IT (TraIT) project in The Netherlands aims to organize, deploy, and manage a nationwide IT infrastructure for data and workflow management targeted specifically at the needs of translational research projects. tranSMART has been selected as the central data integration and browsing solution across the four major domains of translational research: clinical, imaging, biobanking and experimental (any-omics). For this purpose user stories from anticipated user projects are collected and mapped onto the current functionality of tranSMART. The gaps identified in this analysis are being tackled systematically as summarized in the TraIT development roadmap for tranSMART.
tranSMART Community Meeting 5-7 Nov 13 - Session 5: Recent tranSMART Lessons ...David Peyruc
tranSMART Community Meeting 5-7 Nov 13 - Session 5: Recent tranSMART Lessons Learned in Academic and Life Science Settings
Dan Housman, Recombinant by Deloitte
The Recombinant by Deloitte team has worked with organizations such as Kimmel Cancer Center as a model to adapt existing mature i2b2 implementations to meet business and scientific needs. Other organizations are increasingly focused on how to use cloud and high performance computing models to achieve different performance levels. Advanced initiatives are progressing to link commercial tools such as Qlikview to explore tranSMART data and to solve for key gaps in scientific pipelines. Dan will present recent lessons learned, new capabilities, and some of the impact on the path forwards for future tranSMART updates.
Bioinformatics in the Clinical Pipeline: Contribution in Genomic Medicineiosrjce
In this review report we like to focus on the new challenges in methodology of modern biology be
used in medical science. Today human health is a primary issue to cure disease, undoubtedly the answer to this
is bioinformatics or (In-silco) tools has change the concept of treating patients to understand the need of
genomic medicine in use. Those with new modes of action in clinical treatment, is a major health concern in
medical science. On global prospective scientific role in constructing new ideas to remediate health care to
treat disease exciting in nature is challenging task. So awareness needs to accelerate store clinical datasets for
scientific represents to design genomic drugs. This new outline will drive the medical to discover public data
and create a cognitive approach to use technology cheaper at cost effective mode.
The Foundation of P4 Medicine Keynote Presentation as presented by Leroy Hood, M.D., PhD, at the Ohio State University Personalized Health Care National Conference 2010.
Dr. Leroy Hood lectured to a group of Ohio State University College of Medicine students and faculty on May 13, 2010 in advance of an announcement of a partnership between the Ohio State University Medical Center and the Institute for Systems Biology. The partnership will be known as
Big Data and Genomic Medicine by Corey NislowKnome_Inc
View the webinar at: http://www.knome.com/webinar-big-data-genomic-medicine. This presentation covers an overview of genomic medicine, requirements and challenges of next-generation sequencing, bottlenecks to broader healthcare adoption, and why “we want to sequence everyone.”
P4 Medicine: A Vision For Your Molecular HealthSachin Rawat
Medicine is undergoing tremendous change. Unlike today, medicine of tomorrow would be pro-active rather than reactive.Medicine would be personalized to individual patient's genome. It would predict, and hence prevent, diseases even before they manifest. Also, this medicine would require active societal participation to bring it from labs to clinics.
FDA NGS and Big Data Conference September 2014Warren Kibbe
Presentation for the FDA NGS and Big Data Conference September 2014 held on the NIH campus. NCI initiatives, including Cancer Genomics Data Commons, NCI Cloud Pilots, big data issues for cancer
National Cancer Data Ecosystem and Data SharingWarren Kibbe
Grand Rounds at the Siteman Cancer Center at Washington University. Highlighting the Genomic Data Commons and the National Cancer Data Ecosystem defined by the Cancer Moonshot Blue Ribbon Panel
Advancing Innovation and Convergence in Cancer Research: US Federal Cancer Mo...Jerry Lee
Special Seminar at the 8th Taiwan Biosignatures Workshop to share overall work of NCI's Center for Strategic Scientific Initiatives since 2003 as well as CSSI's influence on select projects initiated by the 2016 WH Cancer Moonshot Task Force that include Applied Proteogenomics Organizational Learning and Outcomes (APOLLO) network, International Cancer Proteogenome Consortium, and the Blood Profiling Atlas in Cancer (BloodPAC) commons.
Kim Solez Introduction to regenerative medicine Fall 2015Kim Solez ,
Dr. Kim Solez presents "Introduction to Regenerative Medicine" on September 10, 2015 in the Technology and Future of Medicine course LABMP 590 http://www.singularitycourse.com at the University of Alberta in Edmonton, Canada. Copyright (c) 2015, JustMachines Inc.
tranSMART Community Meeting 5-7 Nov 13 - Session 3: The TraIT user stories fo...David Peyruc
tranSMART Community Meeting 5-7 Nov 13 - Session 3: The TraIT user stories for tranSMART
The TraIT user stories for tranSMART
Jan-Willem Boiten, TraIT
The Translational Research IT (TraIT) project in The Netherlands aims to organize, deploy, and manage a nationwide IT infrastructure for data and workflow management targeted specifically at the needs of translational research projects. tranSMART has been selected as the central data integration and browsing solution across the four major domains of translational research: clinical, imaging, biobanking and experimental (any-omics). For this purpose user stories from anticipated user projects are collected and mapped onto the current functionality of tranSMART. The gaps identified in this analysis are being tackled systematically as summarized in the TraIT development roadmap for tranSMART.
tranSMART Community Meeting 5-7 Nov 13 - Session 5: Recent tranSMART Lessons ...David Peyruc
tranSMART Community Meeting 5-7 Nov 13 - Session 5: Recent tranSMART Lessons Learned in Academic and Life Science Settings
Dan Housman, Recombinant by Deloitte
The Recombinant by Deloitte team has worked with organizations such as Kimmel Cancer Center as a model to adapt existing mature i2b2 implementations to meet business and scientific needs. Other organizations are increasingly focused on how to use cloud and high performance computing models to achieve different performance levels. Advanced initiatives are progressing to link commercial tools such as Qlikview to explore tranSMART data and to solve for key gaps in scientific pipelines. Dan will present recent lessons learned, new capabilities, and some of the impact on the path forwards for future tranSMART updates.
The $1000 genome is here, and the fundamental problems have shifted... it is no longer about shrinking the cost of sequencing but the explosive growth of big data: the downstream analytics with rapidly evolving parameters, data sources and formats; the storage, movement and management of massive datasets and workloads, and the challenge of articulating the results and translating the latest findings directly into improving patient outcomes. This presentation talks to the work Intel Corp. is doing with it's partners to make research and clinical genomics mainstream - "Taking Precision Medicine Mainstream."
The Real Opportunity of Precision Medicine and How to Not Miss OutHealth Catalyst
Precision medicine, defined as a new model of patient-powered research that will give clinicians the ability to select the best treatment for an individual patient, holds the key that will allow health IT to merge advances in genomics research with new methods for managing and analyzing large data sets. This will accelerate research and biomedical discoveries. However, clinical improvements are often designed to reduce variation. So, how do systems balance tailoring medicine to each patient with standardizing care? The answer is precise registries. For example, using registries that can account for the most accurate, specific patients and disease, clinicians can use gene variant knowledge bases to provide personalized care.
Precision Medicine: Opportunities and Challenges for Clinical TrialsMedpace
The momentum and muscle behind "finding the right drug for the right patient at the right dose" has further escalated with President Barack Obama’s announcement of a $215 million dollar Precision Medicine Initiative earlier this year. In this webinar, Dr. Frank Smith will explore advances in precision medicine and how it is affecting clinical research. As a pediatric hematologist/oncologist, he will use his extensive clinical and research background as a backdrop for the discussion.
Topics will include:
The evolution of "personalized medicine" to "precision medicine"
How state-of-the-art molecular biology is creating new diagnostic and prognostic strategies
How these new strategies are helping inform the design of clinical trials
Case study: How precision medicine is improving clinical trials in hematology and oncology
Going Beyond Genomics in Precision Medicine: What's NextHealth Catalyst
Precision medicine processes, while involving genomics, are not confined to working with data about an individual’s genes, environment, and lifestyle. Precision medicine also means putting patients on the right path of care, taking into consideration other individual tolerances, such as participation and cost. Precision medicine processes incorporate data beyond the individual, pulling in socio-economic data, as well as relevant internal and external data, to create an entire patient data ecosystem. With reusable data modules, this information is processed within a closed-loop analytics framework to facilitate clinical decision making at the point of care. This optimizes clinical workflow, thus leading to more precise medicine.
Find out about collaboration and partnership opportunities with the Wellcome Sanger Institute that aims to create exceptional healthcare opportunities for everyone from extraordinary science.
We can aid decision making from the pre-clinical to the clinical setting, supporting line of sight to the clinic, by identifying and translating crucial biomarker approaches into the real world.
A recognized expert with 16 years of experience on translational bioinformatics, genomics, and genetics, specialized on developing databases, genome repositories, pipeline, clinical application, and commercial products to analyze next generation sequencing data, and interpret personal genomes and electronic medical records for clinical diagnosis, therapeutics, precision medicine, and predictive disease risk.
5 years of “Rare” Progress Research: Cheryl Rockman-Greenberg, Max Rady College of Medicine, University of Manitoba
Rare Disease Day Conference 2020 March 9-10
Data sharing drivers in precision oncology, biomedical research, and healthcare. Accelerating discovery, innovation, providing credit for all stakeholders - patients, researchers, care providers, payers.
1. Rick Silva, PhD
Executive Director
Biomedical Corporate Alliances
Office of the Senior Vice President
for Health Sciences
A program powered by:
( Office: (520) 621-4789
* RickSilva@email.arizona.edu
Precision medicine and biomarkers: intersection of the -
omics ecosystem and healthcare policy
2. Ken Ramos, MD, PhD, PharmB
Associate Vice President for Precision Health Sciences
Director, Center for Applied Genetics and Genomic Medicine
Director, MD-PhD Program
Professor of Medicine
Elected Member of the National Academy of Medicine
A major driver for the shift from volume-based to value-based healthcare has been the sobering reality
that healthcare, as we know it today, will not be sustainable in the long term without novel approaches
that help to:
• augment diagnostic accuracy and precision;
• deliver targeted therapies that improve efficacy and decrease toxicity;
• stratify populations into sub-populations that more closely align with established guidelines.
4. BIOMARKERS, -OMICS, and PRECISION MEDICINE
National Institutes of Health Biomarkers Definitions Working Group defined a
biomarker as “a characteristic that is objectively measured and evaluated as an
indicator of normal biological processes, pathogenic processes, or pharmacologic
responses to a therapeutic intervention.”
Precision medicine is delivering the right treatment to the right patient at the
right time through early diagnosis and individually tailored treatments....
From the Oxford English dictionary, the suffix “-ome”: in cellular and
molecular biology, forming nouns with the sense "all constituents
considered collectively“. Usually in reference to the interrogation of the
metabolome, kinome, proteome, glycome, transcriptome, or genome (as
a field of study, as in “genomics”).
• Metabolite
• DNA
• RNA
• Protein
• Imaging
• Presence/absence of disease
• Stage of disease
• Prognosis and risk
• Prediction and/or readout of drug response
• Adverse event
5. HOMOCYSTEINE AS A BIOMARKER CASE STUDY
• First publication on homocysteine as a biomarker for B-vitamin deficiency (and
cardiovascular disease) in 1985
• 1st homocysteine patent filed (US 4,940,658) by R. Allen and Univ CO in 1986
• Metabolite Laboratories formed in partnership with the Univ CO 1988
• First patent on homocysteine as a biomarker issues in 1990
• Metabolite sued Labcorp for infringement of ‘658 patent in (after initially taking a license
and making royalty payments, then stopping) 1999
• United States Court of Appeals Federal Circuit issues a judgment against Labcorp for willful
infringement; all other diagnostic labs doing homocysteine assays enter into a license
agreement 2004
• SCOTUS agrees to hear the case on appeal, then later dismisses in 2006
• ‘658 patent expired July 10, 2007
6. • Eugene Meyers pioneered the bioinformatics tools enabling genome alignment (BLAST) and
in silico genome reassembly
• He left University of Arizona in 1998 to found Celera with Craig Venter
• Open innovation model used- enabled accelerated completion the human genome project
• Was not a corporate collaboration with the University of Arizona. (Could it have been?)
• Celera business model was predicated on the annotated genome (we will revisit this later)
Human Genome Map
Science 16 Feb 2001:
Vol. 291, Issue 5507, pp. 1218
Public project was anonymous individuals
from Buffalo NY. Celera project was 3 men, 2
women (including Craig Venter). In a 2001
reference genome sequenced and published
representing these individuals. No individual
variation or clinical information analyzed-
$4.8B ($2016) for that first genome.
…but we knew little about individual differences and similarities in disease populations.
CLINICAL ANNOTATION IS CRITICAL TO UNDERSTANDING DISEASE AT THE GENOMIC LEVEL
THE HGP (v 1.0) AS AN OPEN INNOVATION CASE STUDY
Capture?
Own?
Control?
10. 343 genes
commonly mutated in cancers
(about 0.00082% of the
genome). Targeting sequencing
is absolutely practical for
known diseases with genetic
drivers (cancer).
Not so fast….
• For statistical reasons, and for some applications, “reads” must cover 7-8 X scans, some up to 100X
coverage or 330 billion bases- elimination of errors when the genome is reassembled in silico.
• Some cancers have several heterogeneous tumor cell lineages; e.g. multiple genomes in a tumor.
• As we age, our genome is somewhat plastic and evolves in response to toxins and stress, some tissues
more than others.
THE HUMAN GENOME AND THE REAL WORLD
…..so what does it all mean? Interpretation is HIGHLY specialized
A full human genome is 3.3
billion base pairs (6.6 B letters
in diploid) and now obtainable
for a cost bearable by most
healthcare payers (but not
generally reimbursed yet), and
many self-pay and retail
patients.
Whole exome sequencing reads all
coding regions, aka genes- about
21,000 genes (about 5% of the
genome or 165 M base pairs).
Ignores the increasingly important
dark matter of the genome.
v.4 chip looks for
602k variations -
0.018 % of the genome
(targeted genome analysis,
not full genome sequencing).
You are paying for the report.
The TruGenome Undiagnosed Disease Test covers 90% of the germline genome at 30X
coverage. Costs $9,500; $17,500 if both parents are included.
11. Interpretation: Has two
different point mutations. Not
an actionable mutation
Interpretation: Among several
hundred gene loci sequenced
that had no detected (or known)
tumor-driving mutations.
Interpretation: DO NOT treat
with mabs against EGFr, even
though approved for colon
cancer
12. • Launched in Nov 2013
• Illumina will sequence and individuals genome in a CAP-CLIA sequencing lab
• 18 events held or planned around the world as of Jan 2016
• Allows longitudinal engagement with the participants (vs. a one time snapshot of
health and genome)
• Initially, these folks were prominent and expected to be leaders and evangelists for
precision medicine
• These participants are uber-research subjects
• Is this a new model for grateful patient and benefactor engagement as well?
“About 60 people paid $5,000 each to have their genome sequenced. The attendees, a mix of
doctors, scientists, genetic counselors, and the curious, gathered for two days of lectures and
personal DNA exploration. They got white gift bags that contained an iPad tied with a gold bow, a
framed glass slide of their DNA sample, a hard drive holding their entire DNA sequence, and a
binder with a clinical report disclosing which markers are tied to which conditions.”
January 16, 2014
PATIENT ENGAGEMENT
13. • $25,000-50,000 for COMPLETE genome sequence (30X), full body scan, and
physician consultation.
• Plan for sequencing 40,000 genomes per year.
• Have a partnership model with AstraZeneca on clinical trials and academic
medical centers accessing clinical cases (and clinical annotation), UC San Diego
• Longer term strategy is enabling population health by revealing a trove of
genomic determinants of specific and actionable health and disease outcomes
(like every company seeking to collect and analyze mass genomic data).
HGP (v. 2.0) AS A BIG DATA CASE STUDY
In the era of Big Data
14. Sequenced 160,00
Icelanders, identified
8000 variants of 1171
genes knocked out in
2600 Icelanders (deCODE
Genetics sequenced tens
of thousands). Looking to
expand to new
populations and disease
specific cohorts.
July 22, 2015
SEEKING CLINICAL CASES….
Population scale genome sequencing
NIH + White House
funded Precision
Medicine Initiative to
enroll 1 million patients
and study clinical
parameters with
lifestyle, -omic, and
health outcome
parameters.
Looking for genetic
variants with frequencies
of >1% in UK populations
at 4x coverage.
These Superhumans Are Real and Their DNA Could Be Worth Billions
Longevity, Inc.
sequencing 200,000
genomes through
collaborations over next 5
years and announced a
10 year partnership with
AstraZeneca to sequence
up to 500,000 DNA
samples from
AstraZeneca clinical trials.
The insights from the
collaboration will be
added to the HLI
Knowledgebase™,
building upon what is
already the most
comprehensive database
of its kind.
In 2014 Regeneron
enters into an alliance
with Geisinger Health
System to recruit
250,000 DNA donors
to identify genes
associated with
susceptibility or
resilience to disease.
Artificial intelligence platforms-as-a
service (Watson,Predix) will be
reliant on “training data” from in-
the-wild clinical cases, allowing
identification of complex patterns
of genomic information correlated
with clinical patterns. Collaboration
models with AMCs will inform those
platforms and guide use cases.
1,000,000 patients
45 M GB = 45 Petabytes = 600years of HD video
Big Science & really, really Big Data
*@ high coverage- 30X
100,000 patients
4.5 M GB = 4.5 Petabytes = 75 years of HD video
200,000 patients
11 M GB = 11 Petabytes = 1.5 centuries of HD video
500,000 patients
23 M GB = 23 Petabytes = 3 centuries of HD video
200,000 patients
9 M GB = 9 Petabytes = 12 years of HD video
100 Petabytes = 3 centuries of HD video or all the
internet traffic in the year 2000
160,000 patients
6.8 M GB = 6.8 Petabytes = 75 years of HD video
15. The fading healthcare model
PATIENTS PROVIDERS PAYERS
Get sick
Get reimbursed
for
services/drugs
Pay for services
to sick people
PHARMA
Sell drugs
16. What does the sub-$1000 genome mean for healthcare?
PATIENTS PROVIDERS PAYERS
DNA & Health Data Clinical decision
tools
Population
outcome data
PHARMA
Safety + Efficacy
+ Cost
17. Clinical decision
tools
What does the sub-$1000 genome mean for healthcare?
We are in it together
PATIENTS PROVIDERS
PAYERS
PHARMA
ACOs
PAY-FOR-
PERFORM
ANCE
Wellness
ownership
Risk
sharing
Population
outcome data
Adaptive clinical
trialsCost
effectiveness
Tools and outcome measures by which to quantify risk, and reward, will alter decision
making across the healthcare continuum.
19. POLICY & POLITICAL HEADWINDS FOR PRECISION MEDICINE
UC Davis Law Review, Vol. 49, June 2016. p. 1881-1940
Changes in innovation incentives
• Reduced patent scope and enforceability
• Reduced reimbursement rates
• Increased regulation of LDTs
• ACA Medical Device Tax (suspended through 2017)
• Commoditization of NGS analytics
• Slow adaptation of CPT codes for new technologies
• Higher bar for clinical validation/evidence by payers
• Refined standard clinical decision practices
…in short, reduced incentives to invest in clinical
validation at a time when more clinical evidence is
required by payers and regulators.
20. • Labcorp vs Metabolite Labs Inc
• Mayo Collaborative Services vs Prometheus Laboratories Inc
• Association for Molecular Pathology vs Myriad Genetics Inc
• Vanada Pharmaceuticals Inc vs Roxane Labs Inc
• Ameritox LTD vs. MilleniumHealth Inc
• Genetic Veterinary Sciences Inc vs Canine EIC Genetics LLC
• Endo Pharm Inc vs Actavis Inc
• EsoterixGenetic Lab LLC vs. Qiagen LTD
• Cleveland Clinic Foundation vs True Health Diagnostic LLC
• Rutgers vs Qiagen Inc
• IdexxLab Inc v. Charles River Labs Inc
• Oxford Immunotec Ltd. vs Qiagen Inc
• Ariosa Diagnostics Inc vs Sequenom Inc
Patent protecting key elements of a molecular test has become very difficult
under US patent law. Recent cases have done little to distinguish and clarify
natural law, application of that law, abstract idea, or a universal inventive step
that might clarify
See for review: Diagnostics Need Not Apply. R. Eisenberg. Journal of Science & Technology law, vol.
21.2 Summer 2015
POLICY & POLITICAL HEADWINDS FOR PRECISION MEDICINE
21. • Is often the first to reimburse, and is the largest payer (it is really 7
centers and 7 payers) covering 100 million people, so their
reimbursement decision are a major driver of medical innovation.
• Oversees CLIA standards; focused on analytic standards, not clinical.
• The clinical evidence standard for 510(k) and LDTs is rising with CMS, so
regulatory clearance is really no longer a critical commercialization
milestone, CMS reimbursement is the value driving milestone.
• The Bundled Payments for Care Improvement (BPCI) Initiative was
established by the Affordable Care Act and is a move toward value-based
payment models to reward outcomes for episodes of care, instead of ala
carte service.
• Medicare’s Date of Service Rule has had the unintended consequence of delaying delivery
of test information to clinicians, by many days, if not weeks. This has encumbered
utilization molecular diagnostic testing to it’s full potential.
POLICY & POLITICAL HEADWINDS FOR PRECISION MEDICINE
22. • FDA has very recently begun to exercise it’s long standing
statutory authority to regulate LDTs, in part to establish
standards for the use of NGS in clinical decision making.
• In fall of 2014 release draft oversight framework for Premarket
Approval of High-Risk Laboratory Developed Tests.
• In July 2016 releases draft oversight framework for Next Gen
Sequencing in Diagnosing Germline diseases (noncancer).
• Issued guidance for an Expedited Access Program for De Novo
Medical Devices; parallel CMS and FDA review also possible;
predicated on a clinical data development plan.
These frameworks all strive to clarify clinical decision making
standards, NGS specific analytic standards (coverage) as well as
general analytic standards (accuracy, precision, repeatability,
reproducibility, detection limits, analytic specificity).
POLICY & POLITICAL HEADWINDS FOR PRECISION MEDICINE
23. GRAND CHALLENGES IN PRECISION MEDICINE TO BE SOLVED
Policy disconnects have
diminished investment
incentives for diagnostic
innovation at a time when
clinical validation is
increasingly important.
Specific policy fixes for
diagnostics are a major
theme in healthcare
innovation policy circles.
The use of biomarkers in
clinical decision making,
now requires years and
hundreds of clinical
cases of validation to
drive clinical adoption,
regardless of whether
IVD, CLIA/LDT, or other
and large –omic data
sets. Regulatory and
payer requirements
demand more clinical
evidence (peer reviewed
observation and/or
prospective clinical
trials) for use
(reimbursement) of a
test. Clinical actionability
has become critically
important for
commercial investment,
and accordingly,
reimbursement.
Payer cost management
and quality accountability
will drive increased
consumption of diagnostic
information, at least in
volume, perhaps not in
dollars. Reimbursement
models must evolve to
enable the use of valuable
new outcome measures,
lest their adoption be
neglected.
The discovery, validation,
and clinical deployment
of multianaltye –omics
tests will require a
significant step-up in
medical specialization.
Interpretation of the
clinical sequencing assay
reports requires expertise
that is presently rare
among clinicians, and
predominantly resides in
major academic medical
centers. -omic
information is
increasingly less human
readable and it’s use
highly specialized, and
workflows, dashboards,
and clinical decision rules
must adapt to enable it’s
use.
US patent case law for
biomarker technologies
has sharply reduced the
utility of patents as a
tool to promote
investment in clinical
validation and
commercial
development of
biomarkers.
Clinical workflows and
medical training need
to adapt to rapidly
accelerating changes in
medical practice,
decision making, and
payment models.
Teams of specialists
will increasingly need
to share information
and insights across the
care continuum.
24. PUNCHLINE
• The cost of DNA sequencing has fallen much faster than the rate Moore’s Law would
indicate.
• High throughput biology, cloud computing, and computational advances are rapidly
being commoditized and transforming clinical decision making by delivering
individualized molecular information to the point of care at a practical pricepoint.
• As a result, these technologies are finally allowing us to understand molecular basis
for difference in disease in individuals by studying these differences in populations.
• Our armamentarium of therapeutics is rapidly accumulating agents designed to
address disease at the molecular level, so more biomarkers are actionable than 10
years ago.
• However, rigid clinical workflows, policy constructs, regulatory pathways,
reimbursement based on old technologies represent frictions to investment in and
adoption of new practices.
25. Rick Silva, PhD
Executive Director
Biomedical Corporate Alliances
Office of the Senior Vice President
for Health Sciences
A program powered by:
( Office: (520) 621-4789
* RickSilva@email.arizona.edu
Precision medicine and biomarkers: intersection of the -
omics ecosystem and healthcare policy
Editor's Notes
Biomarkers are basically chemical analytes from the body. The presence, absence or level of one or more biomarkers might be a reliable indicator of health or disease, or a change therein. One of the more interesting and impactful case studies is cholesterol, identified as a biomarker of cardiovascular disease risk in the Framingham heart studies. It is perhaps the first longitudinal study of clinical utility of a biomarker in a population health context when launched in the late 1940s. It is still ongoing.
High throughput biology technology has increased the stakes. Microarrays (aka gene chips), next generation sequencing, and to a lesser extent mass spec based proteomics and metabolomics, have all become cost-practical in a clinical setting (though reimbursement is a different matter). In theory, multiple analytes would reveal clues and potential interventions for more complex or intractable diseases like cancer or Alzheimers. The promise of Precision Medicine is the promise of making use of the many, many more biomarkers and significant advances in computational technology (AI, machine learning, assisted cognition) to understand and confront complex disease.
The reality however is that there any many very challenging practical hurdles that must be addressed. Policy and clinical practice have not yet caught up with technology. But we are getting closer…
This case study is one that is familiar to me and illustrates some of the challenges keeping biomarker innovations in the lab and out of the clinic. Significant clinical adoption (ordering the tst by doctors and reimbursement by insurers) of homocyusteine testing did not occur until the late 90s, more than a decade after the first publications. An accumulation of clinical evidence for use of a biomarker is a first, and usually long first step toward clinical use.
This case study represents an interesting dichotomy in the business models and IP implications of lab developed tests vs. in vitro diagnostics.
The government, corporate, and academic ecosystems were very separate in those days. In The Genome Wars, it was postulated NIH was uninterested in supporting Meyers’ work. Academic peer reviewers were uninterested in publishing it. A software trick that manipulates genetic code, a very, very niche market at the time, didn’t fit the patent-and-license model of technology transfer- it was not going to be productized. It was questionable whether it could be owed (or at least controlled) with patents. Making it a black box technology was at odds with the ethos of the bioinformatics community at the time (and still today). BLAST was put on the public commons and made available to the entire research community free of charge in the mid-90s. It however was a profoundly important in enabling technology for the largest Big Science project since the Manhattan Project. By the time sequencing was ubiquitous and a meaningful market. In short, open innovation enabled the human genome project.
A little about entrepreneurial ecosystems. Illumina was a typical product of the academic-biotech-venture capital ecosystem- a rollup of technology from Tufts and technology spun out of Cambridge University, and a product of several collaborations of necessity. Ultimately, it brought cost effective genome sequencing to most medical researchers. It soon bring cost effective genome sequencing to most clinicians and patients. However, general healthcare establishment may not yet be prepared for the coming data deluge.
A little about entrepreneurial ecosystems. Illumina was a typical product of the academic-biotech-venture capital ecosystem- a rollup of technology from Tufts and technology spun out of Cambridge University, and a product of several collaborations of necessity. Ultimately, it brought cost effective genome sequencing to most medical researchers. It soon bring cost effective genome sequencing to most clinicians and patients. However, general healthcare establishment may not yet be prepared for the coming data deluge.
The clinic and clinician will tell you things a DNA sequence or a computer can’t, particularly insights related to similarities and differences throughout populations.
Diagnostics is moving away from assays for specific genetic defects and toward. An integrated clinical, information technology, and clinical diagnostic ecosystem is necessary to utilize genetic sequence information. Retail and superficial sequencing services that lack the clinical insight and annotation of an academic physician scientists, are unlikely to be impactful as
Raw genetic info, it turns out, is not generally inherently any more useful to my physician than my 3rd grader. Insight is key, and that comes from analytics with in-the-wild clinical cases. Most clinical test available commercially have a report that extracts insights that have 1) a degree of clinical validation in the scientific literature, or 2) FDA-approved interventions/decision rules and will note which
This may look different in a recurring tumor that an initial tumor in a given patient, due to genome instability and tumor heterogeneity.
First, our work is rarely going to involve the limited data set the $1000 genome provides, physician scientists will often need more statistically robust and deeper sequencing.
First, our work is rarely going to involve the limited data set the $1000 genome provides, physician scientists will often need more statistically robust and deeper sequencing.
The additional data –omics and other flavors of precision medicine data will need to be consumed across the healthcare continuum.