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Drug Safety Management Safety is good business.

Life Sciences Research Office Evaluating Adverse Event Systems for Dietary Supplements. Drug Safety Management Safety is good business. Potential for Extracting Data from Sample Databases January 31, 2003 Y. Renee Lewis, Chief Operating Officer. Agenda. About QED Solutions, Inc.

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Drug Safety Management Safety is good business.

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  1. Life Sciences Research OfficeEvaluating Adverse Event Systems for Dietary Supplements Drug Safety ManagementSafety is good business. Potential for Extracting Data from Sample Databases January 31, 2003 Y. Renee Lewis, Chief Operating Officer

  2. Agenda • About QED Solutions, Inc. • Data Considerations • Analyzing the Data • Research Capabilities • Summary Company Proprietary2

  3. About QED Solutions

  4. QED Overview • Company Focus: Web-based Drug Safety Management Solutions – product with supporting services. • Sophisticated analytical tools that support pharmacovigilance and safety surveillance investigations • Research capabilities to aid medical professionals in finding and understanding patterns of drug behavior provided in details of adverse event data • Services: Implementation, application hosting, data validation, data extraction/aggregation, data extensions, limited research (primarily with partners) • Client-base: 22 major pharmaceutical and bio-technology firms. • Primarily Global Safety Office, Medical Affairs or Epidemiology. Company Proprietary4

  5. Product Overview - QscanTM • Products: One research solution, access multiple data sets • QscanTM FDA – subscription service to AE data released from the FDA through FOIA • QscanTM World – subscription service to AE’s received by the WHO at Uppsala Monitoring Center representing 67 countries (CIOMs and MedWatch forms) • QscanTM PRO – internal application to review data collected at a pharmaceutical company • Statistics: Proportional analysis, frequency profiling, correlations, comparisons • Others: Automatic detection alerts to simplify monitoring of hypothesis • Research capabilities to aggregate independent cases into series for analysis Company Proprietary5

  6. Product Maturity • 12/1998 Founded by Victor Gogolak to develop solutions for pharmacovigilance • 10/1999 Begin development of first product (data and application • 06/2000 QscanTM Alpha released at DIA conference, Glaxo first Alpha customer • 10/2000 QscanTM FDA 1.0 released to public • 12/2000 Roche purchased – first production customer • 06/2001 QscanTM FDA 1.2 released • 09/2001* QscanTM FDA 1.5 released (General Release Product) • 02/2002 QscanTM FDA 1.6 released • 04/2002 QscanTM FDA 1.6.1 released • 06/2002 QscanTM World alpha released • 08/2002* QscanTM World 1.7 released • 09/2002 QscanTM FDA 1.7 released • 03/2003 QscanTM FDA 2.0 and World 2.0 • Aggressive release schedule includes: • Data manipulation features • Analytic techniques • Data sets or updates Company Proprietary6

  7. Using Tools • What you can do with tools: • Monitor and detect requested patterns in the data • Research general patterns and trends • Probe and analyze hypothesis • Show how the reported data compares consistent with proposed populations • Identify strength of association between elements in a set of cases • Compare two different sets of data • Store saved results and data for future review, comparison • Export data for additional analysis or reporting • What QscanTMdoes not do: • Provide “answers” – medical judgment is required • Show causality – must use other methods • Directly support regulatory reporting process Company Proprietary7

  8. Data Considerations

  9. Data Issues - General • Data Availability – no “good source” for herbals, vitamins or OTC’s • No regulation to drive data collection – voluntary • No regulation around data review or analysis • No source specific to this domain • Safety is a public policy issue • Does data makes a company possibly vulnerable OR does it provide a competitive advantage? • Data Quality • Limited training on data collection for these items – data collected by accident! • Data collection poor, not controlled • Many consumer reports with no medical follow up • Lack of integrity of data relationships (e.g., time to onset) • FDA and World only report “serious and unexpected” – bad things Company Proprietary9

  10. Data Considerations with QscanTM Sources • QscanTM FDA (through FOIA or other 3rd party) • FDA data released under FOI in “raw” form (verbatim terms) • Released quarterly - approximately 6 month latency • Nov 1997 to present - Adverse Event Reporting (AERs); MedDRA reaction dictionary (very old release) • 1969 – October 1997 - Spontaneous Reporting System (SRS); COSTART mapped to MedDRA • Regulations to control volume of data – severe and unexpected • QscanTM World • World Data – 67 countries – CIOMs except US • Includes FDA data, but only “non-consumer” reports • WHO-ART reaction dictionary; WHO-DD • Some noticeable latency in data collection (years in some countries) • QscanTM PRO • Internal data – Post Market and Clinical Trial • World Health Organization – Uppsala Monitoring Centre • Clinical Trials Company Proprietary10

  11. Sample Data Dictionary mappingsand aggregations Suspect vsnon-suspect Company Proprietary11

  12. Verbatims (Show Source) Company Proprietary12

  13. Data Examples – Case Listing Follow-on processing Reactions – MedDRA terminology Duplicates? Twins? Company Proprietary13

  14. Sample – Case Detail • All the data is made available to review every known detail. • Additional elements can be easily added. Company Proprietary14

  15. Other Possible Data Sources • Commonly used for analysis • Consumer reports to the company • GPRD (General Practice Research Database) • Claims data • Registries • Uncommonly used, commonly used as data extenders • Prescription data - denominator • Medical records (closed systems like Kaiser Permanente) • Medical records with claims data (hard to find) • Genomic databases, Toxicology data • Internet sites • Requirements for use • Structured • Coded (dictionary, reactions, outcomes, demographics) Company Proprietary15

  16. Analyzing the Data

  17. If it’s so bad, why use this data? • Availability ….Many AE’s include herbals, vitamins and OTCs as a by-product of the process • Severely under reported, but can assume that the under reporting is uniform • Many herbals, vitamins and OTCs have been around for a long time – our data goes back to 1969 • Patterns may emerge using more sophisticated techniques: • Proportional Analysis • Correlation • Reactions are coded (MedDRA and WHO-ART) • Drug names are mapped and can be remapped easily • Available today, immediately Company Proprietary17

  18. Analytics • Common output with these data • Rates and counts • Proportional reporting rates – “out of norm” • Odds Ratio (where appropriate) • Correlations • Comparisons – standard backgrounds, other data sets • Trends • Ability to export data from the system • Continued analysis and imaging • Documentation • Information sharing • Requires structured information • Dictionaries and terminologies • Setup for both analysis and research (drill-down) Company Proprietary18

  19. Research Social Circumstances – PRR 2.98 • Details • Case 3570383Drug abuser • Case 3618733Refusal of treatment Primary suspect on both! Positive Dechallenge Company Proprietary19

  20. Research Capabilities

  21. Case Series and Search Criteria • Ability to group cases based on criteria, for example • Reactions • Concomitants • Demographics • Report dates • Outcomes • Medically significant • Methods to find “difficult” groupings, for example • Cases where these two drugs occur together • Cases with this drug or that drug • Cases where this drug occurs, but not that drug • Cases with only these reactions • Ability to review out put and refine criteria based on results • Facility to share results with interesting information or comments Company Proprietary21

  22. What’s it take to make data “analyzable?” • Structured data for elements coded to terminologies, where possible • Drug/compounds (primary, concomitants, suspect drugs and why) • Reaction Terms • Outcomes • Demographics • Additional information is a plus to increases capabilities and understanding • Condition data • Time to onset • Report dates • Good intake procedures improve the data quality • Handling of consumer reports • Medical review of reports • Data collection tools and automation procedures • Application and data access for review, follow-up and analysis • Methodologies – passive and active Company Proprietary22

  23. Summary

  24. Summary • Not much available today, so make the most of what’s there • You can use what is available to your advantage with the “right” approaches • Tools and software frameworks make the task less arduous, data readily available • Better data sources for herbals and vitamins are sorely needed • Qscan-like tools can be used against any spontaneous data source with some minimal effort • Dictionaries, standard terminologies and proper mapping techniques make the data systematically available Company Proprietary24

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