Economic Impact. IWGSC March 12, Jim Vaught, Ph.D. Jim Vaught, Ph.D. Deputy Director. ESBB Marseille November 2011

Transcription

1 ESBB Marseille November 2011 Biospecimen Collections: Biobank Economic Business Issues Planning and Economic Impact IWGSC March 12, 2009 Jim Vaught, Ph.D. Deputy Director Jim Vaught, Ph.D. November 5, 2007 Office of Biorepositories Lisa B Miranda & Biospecimen Research 1 Deputy U.S. National Director, Cancer Institute, NCI OBBR NIH, DHHS

2 Topics National biospecimen network NCI best practices & business planning Some current biobanking networks Overview of economic issues Value proposition Total cost of ownership Cost recovery Business model Economic impact examples

3 National Biospecimen Network Blueprint Key principles : Standardized biospecimen collection and distribution procedures Standardized data sets and data vocabulary Harmonized approached to ethical and legal issues Standardized consent, MTAs Transparent governance and business models Transparent access policies Large well-designed specimen sets for a variety of research questions

4 Web version of NCI Best Practices

5 From the 2011 NCI Best Practices B Business Planning Business planning can provide justification for financial and institutional commitment and quantification of startup and sustainability costs. Business B i planning should be integrated t into all aspects of operations, biospecimen i resource management, and evaluation. Resources should aim to establish a documented annual business plan developed with department t staff input and aligned with the vision i and mission i of the resource. Business plan items should be specific, measurable, actionable, relevant, and time bound. The resource business plan should also include a formal continuity plan that addresses all possible operational disruptions, including disaster planning. If the resource functions as a service center, the business plan should address issues related to service and revenue generation.

6

7

8 Qualities of well-designed biobanking networks The biobanks outlined in the review, although they operate under a variety of models, share many of the following characteristics, which in most cases are detailed in their web sites: Governance models with clearly stated technical standards, ethical guidelines, access policies and procedures, scientific rationale, and long-term custodianship plans, i.e. assuring that the program is sustainable from a technical and economic perspective. A strong quality assurance/quality control program with clearly defined standard operating gp procedures, and regular audits to assure compliance. A comprehensive business model that, unless it is entirely supported by public funds, has a sustainable cost-recovery yplan, or other means to assure consistent long-term financial support. In general, adherence to a set of best practices governing both technical and ethical/legal issues, such as those published by the International Society for Biological and Environmental Repositories (ISBER and NCI (

9 Business & economic issues being addressed by OBBR Costs of establishing & maintaining biorepositories Recovering costs is full cost recovery possible? What is the value of specimens and data? Costs of implementing best practices? Importance of quality management & evidence-based standard operating procedures Economic benefits: can they be quantified? Efficiencies of scale Benefits of implementing best practices Impact of more efficient informatics systems Economic & scientific value of networks

10 Journal of the National Cancer Institute Monograph June 2011

11

12 Global market demand for biospecimens Figure 1: Global Market Value of the Demand For Human Biospecimens and Related Services $2,500 $2,250 $2,000 $1,750 $1,500 $1,250 $1,000 $750 $500 $250 $- Market Value Growing at 20% 30% Annually ($in millions) From Business Insights March 2009

13 Biobanking Cost Modeling

14 Biobank Total Cost of Ownership Initial Startup Investment t Steady State Phase of Operation osts ($) Annual C Periodic Technology & Equipment Refresh Costs Year of Operation Capital Investment Operating Costs

15 Specimen Catalog Commodities and Service Based Model GTEx PCC Pathology Review Quality Assurance Genotyping Molecular Derivative Isolation Proteomics Analysis Protein Microarrays DNA Expression Profiling Sequencing CTEP (clinical trials) TCGA Advocacy Laboratory Best Practices SOP Training Research Services Sample Orders Managed Collections Center of Excellence Customized Processing Services Data Orders Front Door Concept Training NIH NCI cahub Economic Study

16 Cost Recovery Modeling Based on early NCI cahub planning 1 Cost Recovery Example 1 with Highly Conservative assumptions shows recovering 70% of costs by Year 5: 2 The More Realistic Example 2 uses going-market price data for samples, and demonstrates the potential to achieve Full Cost Recovery by Year 3 just from the sale of commodities alone:

17 Fundamental Factors That Drive Value Fit for Purpose The research application and scientific question being addressed Specifics of the collection protocol Specific project needs (e.g. normal, diseased, d tissue origin, i specimen type, etc.) Sample Quality and Specificity Quality and specificity price drivers: Specimen rarity and size requirements Extent of customized processing requested Clinical parameters (e.g. treatments, etc.), and pathology parameters (e.g. tumor subtype, positive tissue markers) requested Fit for Purpose Quality and Specificity Data Richness Outcomes data are in high demand Comprehensive data sets may double sample price Customized data increases the sample price Data Richness NIH NCI cahub Economic Study

18

19 Benefits framework for centralized biobank Best Practices Stronger Clinical Correlation Decrease in time spent processing samples in order to meet research requirements Avoided cost of having to replenish samples because of higher sample quality Improves Lean abilities to avoid redundant processing costs Higher annotated data promotes improved data sets and more accurate modeling Avoids re-collection of data, saving time and cost Infrastructure Leverage More Efficient Research Job Creation Impact on Economy Clinical Trials Cost Savings Improved Patient Diagnosis and Therapeutic Care Smaller research organizations can leverage storage and bioinformatics system infrastructure, reducing the need to purchase their own Reduction in re-experimentation due to higher quality samples Avoided cost of having to replenish samples because of higher sample quality New jobs created with the potential to spur an increase in certified biobanking professional opportunities, and the resultant economic impact Higher quality specimens reduce clinical trials timeframes and cost Higher quality samples advance biomarker research Improved specimen handling standards reduce the risk of misdiagnosis Reduction in adverse impacts and loss of human life Savings to patients and healthcare providers

20 Biobank Economic Benefits Impact Economic o c Benefits e Impact Category Annual Vl Value 10-Year Value (Discounted) 1. Reductions in the Cost of Clinical Trials $116.8 $ Patient Diagnosis and Therapeutic Care $48.5 $ Efficiencies from Leveraging Infrastructure $14.8 $ Avoidance of Repeat Experimentation $4.2 $ Benefits Due to Implementation of Best Practices $2.4 $ Industry Job Creation Impact on Economy $0.1 $ Improved Modeling of Clinical Data $0.5 $1.5 Total Estimated Economic Benefits $187.3 $701.7 Savings are rough estimates case studies with actual data needed

21 HER2 assay issues: Quantifiable Economic Benefits of Standardization HER2 (ERBB2) gene is amplified in ~ 20% of breast cancers HER2 positive status is an important measure of clinical i l outcome and recommended therapy Positive result triggers therapy: ~$55K/year False-positive: risk of cardiotoxicity, no clinical benefit stressful for patient False-negative: missing potentially beneficial treatment Up to 5,000 false positives and 7,000 false negatives occur per year resulting in millions of dollars wasted Problems with testing start with variability in the way specimens are collected and processed ASCO/CAP recommendations to revise specimen handling to improve assay reliability published in 2007: J. Clinical Oncology, Archives Pathol Lab Med

22 TCGA: The Cancer Genome Atlas Tissue Sample GDAC Pathology QC Sequencing DNA & RNA Isolation, QC Expression, CNA & LOH, Epigenetics Data and Results Storage & QC Integrative Analysis Comprehensive Characterization of a Cancer Genome = Process = Data = Results = BCR = GSCs = CGCCs = DCC = GDACs

23 TCGA: Example of benefit of implementing best practices Tissue quality parameters set by the technical demands of the molecular analysis platforms All 10 analysis centers would analyze exactly the same molecules from the same samples from the same patient - all data directly comparable Sufficient quantity to satisfy all platforms Sufficient quality to yield interpretable data on all platforms The target number of 500 cases per tumor type (lung, glioblastoma, ovary) in the pilot study: defined depth of analysis and probability bilit of finding genomic changes that t occur infrequently (3% level)

24 Early failures in sample quality from existing collections Early quality failure rate was over 70% at cost of over $2000 per case (tumor, normal tissue or blood, data, personnel costs) and failed cases had to be replaced to reach target 500 cases/tumor. # Frozen samples logged in collection # Samples meeting spec upon detailed review of inventory Repository 1 Repository 2 (Major (Major Academic Site) Academic Site) Before full pathology review # Samples meeting physical/pathological specs

25 The Cancer Genome Atlas (TCGA): Where Samples Fail Most TCGA slides courtesy of Dr. Kenna Shaw, TCGA Program Director

26 Pass rate improves as prospective collection using best practices/sops implemented % Retrospective % pass rate 60% pass rate ~80% pass rate % Prospective /16/2007 5/16/2007 7/16/2007 9/16/ /16/2007 1/16/2008 3/16/2008 5/16/2008 7/16/2008 9/16/ /16/2008 1/16/2009 3/16/2009 5/16/2009 7/16/2009 9/16/ /16/2009 1/16/2010 3/16/2010 5/16/2010 7/16/2010 9/16/ /16/2010 1/16/2011 3/16/2011 5/16/2011

27 Current TCGA Qualification Rates by Tumor Type 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Pass Rate of the Future? 30% 60%: $4,800,000 70%: $3,400,000 80%: $2.570,000 LUSC LUAD READ BLCA COAD GBM KIRC OV COAD READ UCEC STAD HNSC PRAD CESC SALD BRCA DLBC PAAD LGG THCA KIRP LIHC Savings achieved with higher future pass rates for ALL cases in the project

28 Economic Analyses Next steps for OBBR Refine the cahub program cost and pricing models through fine- tuning of: Annual accrual of cases Types of cases to be collected for various partners Specimen processing protocols and downstream analyses Outsourcing plans for cahub Pilot period and beyond Adjust cost recovery targets as more detailed information is received and further guidance provided on NIH funding mechanisms, timing, etc. Develop use cases/studies to detail and document the economic benefits that the cahub will create for research in the areas of biospecimen i quality; processing protocols; infrastructure leveraging Develop a cost analysis and tracking tool and resulting price schedule for the commodities and services of cahub

29 Special thanks to Joyce Rogers, OBBR TddC Todd Carolin &Business Analytics lti Team, Booz-Allen-Hamilton Jff Jeffrey Furman, economist, itboston University Ui it All contributors to: 2008 NCI BioEconomics workshop 2011 JNCI Monograph

30 i

31