1. The Uppsala Monitoring Centre
Pharmacovigilance and the WHO Collaborating Centre for International Drug Monitoring in Uppsala Technical Briefing Seminar in Essential Medicines Policies, Geneva, October 2007
Ronald Meyboom, MD, PhD
The Uppsala Monitoring Centre

2. 16% of hospital admissions are drug-related (medical ward)
16% of hospital admissions are drug-related (medical ward). Nelson KM, Talbert RL. Pharmacotherapy 1996;16: Adverse drug reactions are the 5th leading cause of death in a hospital. Lazarou J. Pomeranz BH, Corey PN. JAMA 1998;279: Avoidable in ca. 50 %

3. Definition of Pharmacovigilance: (WHO, 2002, ISBN 9241590157)
The science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problems
Treatment evaluation science

4. Why pharmacovigilance?
Clinical trials focus on demonstrating efficacy and tolerability (selected ‘healthy’ patients, limited in number and duration)
Incomplete knowledge, e.g. effectiveness, rare but serious adverse reactions, interactions, ‘real-live’ patients, sub-populations
Do not produce all the information needed for the balance of benefit and harm

5. How pharmacovigilance?
Spontaneous Reporting
Intensive monitoring (hospital)
Prescription Event Monitoring
Case Control Surveillance
Comprehensive population databases, data-mining
Patient series
Observational studies

6. Formal studies Vigilance
Defined aim (identified problem)
Hypothesis testing (problem solving)
Established methods (clinical trial, case control, cohort)
Comparison
Limited in time, drugs, population, place
Open question: looking for the unexpected
Hypothesis generation (‘problem raising’)
Exploratory, controversial (SR, PEM, CCS)
No comparison
Continuous, all drugs, total population

9. Emphasis on
Early warning
Generation of knowledge
Dissemination of information
Rational and safe use of medicines
Benefit and harm together

10. Three categories of adverse drug reactions Need different methods for detection An ABC of drug-related problems. Drug Saf 2000;22:415-23
Type A
(pharmacological)
Type B
(hypersensitivity)
Type C
(more frequent in exposed than in unexposed)
Clinical trial
Spontaneous reporting
Pharmacoepidemiologychallenge

11. Spontaneous Reporting
A country-wide system for the reporting of suspected adverse reactions to drugs
A case report is a notification from a health care professional, describing the history of a patient with a disorder that is suspected to be drug-induced
Limitations because of privacy protection and medical secrecy

12. Spontaneous Reporting
When different doctors independently report the same unknown and unexpected adverse experience with a drug, this may be a valid early signal
Quantitative: more frequently reported than expected from the background

13. Advantages of Spontaneous Reporting
Effective
‘All’ patients; ‘all’ drugs; many ADRs
Continuous
Rapid
Cheap
Not much health care infrastructure needed

14. Limitations of Spontaneous Reporting
Suspicions, incomplete, uncertain
Underreporting is vast but unknown and variable
Exposure data available?
No frequency measurement
Comparison of drugs difficult
Insensitive to type C adverse effects
Further study for signal testing and explanation

15. Data assessment in pharmacovigilance
Individual case report assessment
Interest, relevance (new, serious?)
Medical, pharmacological; coding
Follow-up
Causality assessment
Aggregated study and interpretation
Signal detection
Risk factors, interactions
Serial (clinicopathological) study
Frequency estimation

16. e.g. possible, probable, etc
General design of systems for causality assessment Drug Safety 1997;17:
Basic questions
Sub-questions
Scores
Overall score
Causality category,
e.g. possible, probable, etc

17. None of the available systems has been validated (i. e
None of the available systems has been validated (i.e. shown to consistently and reproducibly gives a reasonable approximation of the truth)
Validation = ‘proving that a procedure actually leads to the expected results’
No gold standard
Causality category definitions

18. What causality assessment can do What causality assessment cannot do
Decrease disagree-ment between assessors
Classify relationship likelihood (semi-quantitative)
Mark individual case reports
Education / improve-ment of scientific assessment
What causality assessment cannot do
Give accurate quantitative measurement of relationship likelihood
Distinguish valid from invalid cases
Prove the connection between drug and event
Quantify the contribution of a drug to the development of an adverse event
Change uncertainty into certainty

19. Underreporting
Vast (> 90%)
Unknown
Variable
Biased
Difficult to adjust for
No frequency calculation
Delays signal detection

20. Hypothesis, data, arguments
A signal is a set of data constituting a hypothesis that is relevant to the rational and safe use of a medicine
Hypothesis, data, arguments
Pharmacological
Clinical/pathological
Epidemiological
Quantitative / qualitative
Dynamic; develops over time
Drug Safety 1997;17:

22. The balance of evidence in a signal
Quantitative strength of the association
number of case reports
statistical disproportionality
drug exposure
Consistency of the data (pattern)
Exposure-response relationship
site, timing, dose, reversibility
Biological plausibility of hypothesis
pharmacological, pathological
Experimental findings
e.g. dechallenge, rechallenge, blood levels, metabolites, drugdependent antibodies
Analogies
Nature and quality of the data
objectivity, documentation, causality assessment

23. Signal detection is searching for the unknown
Signal detection is searching for the unknown. The same data can lead to different conclusions. Since the truth is unknown it is uncertain who is right, but nobody is wrong!
Dilemma: a signal should be early and credible at the same time
Signals may consist of only a few cases and may not be statistically prominent
A signal is a snapshot and changes over time
Signal testing and explanation require further study
Many signals remain unconfirmed
scientific limitations
no funding

24. WHO Collaborating Centre for International Drug Monitoring
The Uppsala Monitoring Centre
Stora Torget 3, Uppsala, Sweden

25. The Uppsala Monitoring Centre
WHO Collaborating Centre for International Drug Monitoring, Geneva
Moved to Uppsala after agreement between Sweden and WHO
Non-profit foundation with international administrative board
WHO Headquarters responsible for policy
Self-financing
Global pharmacovigilance

26. The Uppsala Monitoring Centre
Director: Prof Ralph Edwards
Deputy director: Dr Marie Lindquist
International affairs: Sten Olsson
Pharmacists
(Bio)medics
IT specialists
Financing (‘Products and Services’)
Administrative
Together 45

28. WHO International Pharmacovigilance Programme, March 2006

29. Collaboration with National Centres
Aims and activities
Collaboration with National Centres
World-wide collection, analysis and distribution of data
Signal detection and analysis
Pooling of data, comparing experiences
Communication, exchange of information
Technical support
Development of methods and tools
Improvement of pharmacovigilance around the world

30. Cumulative number of reports in ’Vigibase’

32. World-wide accumulation and assessment of data
80 participating National Pharmaco-vigilance Centres around the world
3.5 million case reports
Early warning - acceleration of signal detection
Early signal strengthening by comparing countries

33. Automated quantitative signal detection
Extremely large numbers of drug - adverse reaction combinations
Selects automatically high-interest combinations, using quantitative disproportionality
Manageable subsets of data
No human time needed
No investigators bias
Objective, transparent, reproducible
Flexible / adjustable
Explorative

34. Signal detection at the Uppsala Monitoring Centre Eur J Clin Pharmacol 1998;54:315-321
A combination of
Automated quantitative data mining, using Bayesian statistics and a neural network architecture (Information Component – ‘IC value’)
‘Triage’
Human assessment
National Centres
Review Panel
UMC staff

35. Triage filter, combining quantitative and qualitative criteria; automatic selection of associations that
IC025 > 0; two or more countries
Quarterly IC increase of 2 or more
New and serious (WHOART Critical Terms)
Target reaction terms (e.g. SJS), two or more reports, irrespective of IC value
Literature check

37. SSRI Neonatal convulsions or neonatal withdrawal syndrome

38. Example of results in one Quarter (2004)
Total number of combinations:
No. of associations IC025 > 0:
Triage selection:
No. of signals for SIGNAL:

39. Signal Review Panel
40 Experts around the world
Evaluate signals, together with UMC staff and National Centres
Select associations for follow-up
Write signals in the SIGNAL document
Preference for System Organ Class or drug group (ATC)

40. The SIGNAL document
Sent to all National Centres (national distribution)
Individualized section available to industry
All recipients encouraged to comment on topics presented
A WHO signal is a hypothesis together with data and arguments. A signal is not only uncertain but also preliminary in nature: the situation may change substantially over time one way or another.

41. Presentations at ISOP annual meeting 2006
HMG-CoA inhibitors and pulmonary fibrosis
β-2-Adrenoceptor agonists and nocturnal enuresis
Systemic effects of intranasal cortico-steroids (neuropsychiatric reactions, spontaneous abortion)
Taxoids (paclitaxel and docetaxel) and myocardial infarction
Hypersensitivity reactions to Umckaloabo (Pelargonium sidoides and P. reniforme)
Potentiation of warfarin by glucosamine

42. Examples of articles
Clark DW, Strandell J. Myopathy including polymyositis: a likely class adverse effect of proton pump inhibitors? Eur J Clin Pharmacol 2006;62:473-9.
Sanz E, et al. Selective serotonin reuptake inhibitors in pregnant women and neonatal withdrawal syndrome. Lancet 2005;365:
Coulter D, et al. Antipsychotic drugs and heart muscle disorders in international pharmacovigilance: data mining study. BMJ 2001;322:

43. Support to National Centres
Methodology
Terminologies, guidelines
Software (VIGIFLOW)
Harmonisation, standardisation
VIGIMED discussion group
Annual meetings
Training
Books and brochures

44. Terminologies, guidelines Links with WHO Geneva, CIOMS, ICH
WHOART
Drug Dictionary
Guidelines for setting up and running of a Pharmacovigilance Centre
Herbal ATC
Accepted scientific names of therapeutic plants. 2005, ISBN
WHO guidelines on safety monitoring of herbal medicines

45. Harmonisation, standardisation
Definitions (Biriell C, Edwards IR. Drug Safety 1994;23:95-9)
WHO causality categories
Reporting adverse drug reactions. Definitions of terms and criteria for their use (CIOMS Council for International Organizations of Medical Sciences. WHO, 1999, Geneva. ISBN )

46. Herbal and traditional medicines
UMC Herbals database (Dr Mohamed Farah)
Herbal reviewers panel
Collaboration with
Uppsala University, Sweden
WHO Collaborating Centre, Cape Town, South Africa
Royal Botanical Garden, Kew, UK
University of Exeter, UK
Harvard, US

47. New development areas Integrate Chinese ADR database
Patient safety focus including medication errors
World Alliance for Patient Safety
Improved reporting and analysis of vaccine reactions (AEFI)
Flu pandemic planning
Safety surveillance for other Public Health Programmes
Involvement in active surveillance
Cohort Event Monitoring
Data mining analysis of longitudinal patient records

48. Thank you for your attention