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Drug regulatory process, the supporting information systems, and the Escher-project

Drug regulatory process, the supporting information systems, and the Escher-project

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Drug regulatory process, the supporting information systems, and the Escher-project

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  1. Drug regulatory process, the supporting information systems, and the Escher-project Tommi Tervonen Faculty of Economics and Business University of Groningen t.p.tervonen@rug.nl

  2. What is drug discovery and drug development? Ambit biosciences, commercial compound DBs (ambitbio.com) Example drug development costs of Trimeris Inc. (thebody.com)

  3. What are Drug Information Systems (DISs)? • What are they being used for? • Who uses them? • What could they be used for? Drug lifecycle

  4. DIS classes • Compound DBs • Pre/clinical trial DBs • Summary of Product Characteristics (SmPC) DBs • Adverse Drug Reaction (ADR) DBs • CPOEs

  5. The drug regulatory process • Aims to make sure, that the drugs entering market are both safe and efficient • Is laborious and slow • Has relatively poor dissemination of results • Doesn’t have transparent decision making • Has recently all participating parties (drug industry, academia, and regulatory authorities) concerned about reforming the process • The main reason forreforming the regulatoryprocess is to limitthe linear growthof costs,but…

  6. The current DISs don’t store regulatory information of sufficient precision; only aggregated information is available • Systematic, quantitative analysis is not possible without suitable quantitative information. Current Benefit-Risk analysis is qualitative!

  7. Dose-response curve-fitting with various A-II antagonists Similar compounds, partially different indications, totally different clinical data!

  8. Escher-projectWorkpackages 3.1 and 3.2

  9. ESCHER • Is a TI-Pharma project with an objective to “demonstrate, that another way is possible” • Incorporates 3 universities (+medical centers), 4 PostDocs, 17 PhD students, 4 drug development companies, and x external personnel • WP 3.1: develop a new framework for drug benefit-risk assessment • WP 3.2: build a drug information system that allows quantitative comparisons • Benefit-risk analysis of WP 3.1 requires data from the DIS of WP 3.2

  10. Escher 3.1 • How can we measure benefits and risks? • Rank drugs and placebo for the same indication • Multiple criteria • Inherent value judgements • But what about clashing / missing preference information? • Quantitative data available • But data is uncertain! • Should it be used “as is”? • Multi-Criteria Decision Analysis (MCDA)

  11. Stochastic Multicriteria Acceptability Analysis (SMAA) • Allows MCDA with imprecise criteria measurements and missing/incomplete preference information • Criteria measurements can be defined through joint probability distributions -> RCT data can be used +- directly

  12. SMAA central weights • Central weights are “typical” preferences that favour different alternatives • Although drug A might not have “better” benefit-risk ratio than drug B with all preferences, some preferences usually support A as well Elevator planning with SMAA

  13. Rank acceptability indices describe stability of ranking, and can be used in risk management Choosing a location for a new cargo airport in Morocco with SMAA

  14. Escher 3.2 • Supports various other workpackages by building an information system that allows quantitative analyses • Web-based drug repository (Java, Spring) • Agile development • Enables various newresearch topics

  15. Why Agile?

  16. How to model relevant data (SmPC)? 5.1 Pharmacodynamic properties Pharmacotherapeutic group: {group [lowest available level]}, ATC code: {code} [For products approved under “conditional approval”, include the following statement:] <This medicinal product has been authorised under a so-called “conditional approval” scheme. This means that further evidence on this medicinal product is awaited. The European Medicines Agency (EMEA) will review new information on the product every year and this SPC will be updated as necessary.> [For products approved under “exceptional circumstances”, include the following statement:] <This medicinal product has been authorised under “Exceptional Circumstances”. This means that due to <the rarity of the disease> <for scientific reasons> <for ethical reasons> it has not been possible to obtain complete information on this medicinal product. The European Medicines Agency (EMEA) will review any new information which may become available every year and this SPC will be updated as necessary.> 5.1 Pharmacodynamic properties Pharmacotherapeutic group: Drugs used in erectile dysfunction. ATC Code: G04B E03 … Studies in vitro have shown that sildenafil is selective for PDE5, which is involved in the erection process. Its effect is more potent on PDE5 than on other known phosphodiesterases. There is a 10-fold selectivity over PDE6 which is involved in the phototransduction pathway in the retina. At maximum recommended doses, there is an 80-fold selectivity over PDE1, and over 700-fold over PDE2, 3, 4, 7, 8, 9, 10 and 11. In particular, sildenafil has greater than 4,000-fold selectivity for PDE5 over PDE3, the cAMP-specific phosphodiesterase isoform involved in the control of cardiac contractility. … Template Viagra SmPC

  17. US Food and Drug Administration (FDA) is working to build a DIS (Janus) incorporating “raw” data • The European Medicines Agency (EMEA) doesn’t see aggregated data as a problem • Cause? FDA is multi-disciplinary, EMEA consists of medical doctors

  18. Conclusions • Drug regulatory process is in need of reform • Current drug information systems cannot support the future needs, because they don’t store the data in an appropriate format • Escher-project tries to show, that a different “way of doing things” is possible • Department of B&IS participates in the project through Bert, Tommi, Vahid, Douwe (starting 1d/w@Jan), and 1 more PhD-student (starting@Apr)

  19. Thank you! • Q? • Future publications: • T. Tervonen, V. Oskuee, E.O. de Brock, P.A. de Graef, H.L. Hillege (2008). Current status and future perspectives in Drug Information Systems (manuscript) • T. Tervonen, D. Postmus, H.L. Hillege (2009) Multi-criteria decision analysis in drug benefit-risk analysis. Invited presentation, 23rd European Conference on Operational Research, Bonn, Germany. July 5-8, 2009 • /dev/null