![Page 1: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/1.jpg)
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, PhDThe Uppsala Monitoring Centre
www.who-umc.org
![Page 2: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/2.jpg)
16% of hospital admissions are drug-related (medical ward). Nelson KM, Talbert RL. Pharmacotherapy 1996;16:701-7.
Adverse drug reactions are the 5th leading cause of death in a hospital. Lazarou J. Pomeranz BH, Corey PN. JAMA 1998;279:1200-5.
Avoidable in ca. 50 %
![Page 3: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/3.jpg)
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
![Page 4: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/4.jpg)
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
![Page 5: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/5.jpg)
How pharmacovigilance?
• Spontaneous Reporting
• Intensive monitoring (hospital)
• Prescription Event Monitoring
• Case Control Surveillance
• Comprehensive population databases, data-mining
• Patient series
• Observational studies
![Page 6: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/6.jpg)
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
![Page 7: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/7.jpg)
![Page 8: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/8.jpg)
![Page 9: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/9.jpg)
Emphasis on
• Early warning
• Generation of knowledge
• Dissemination of information
• Rational and safe use of medicines
– Benefit and harm together
![Page 10: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/10.jpg)
Three categories of adverse drug reactionsNeed 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
![Page 11: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/11.jpg)
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
![Page 12: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/12.jpg)
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
![Page 13: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/13.jpg)
Advantages of Spontaneous Reporting
• Effective
• ‘All’ patients; ‘all’ drugs; many ADRs
• Continuous
• Rapid
• Cheap
• Not much health care infrastructure needed
![Page 14: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/14.jpg)
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
![Page 15: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/15.jpg)
Data assessment in pharmacovigilance
1. Individual case report assessment• Interest, relevance (new, serious?)• Medical, pharmacological; coding• Follow-up• Causality assessment
2. Aggregated study and interpretation• Signal detection• Risk factors, interactions• Serial (clinicopathological) study• Frequency estimation
![Page 16: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/16.jpg)
General design of systems for causality assessment Drug Safety 1997;17:374-389
• Basic questions
– Sub-questions• Scores
• Overall score
• Causality category,
e.g. possible, probable, etc
![Page 17: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/17.jpg)
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
![Page 18: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/18.jpg)
• What causality assessment can 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
![Page 19: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/19.jpg)
Underreporting
• Vast (> 90%)
• Unknown
• Variable
• Biased
• Difficult to adjust for
• No frequency calculation
• Delays signal detection
![Page 20: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/20.jpg)
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;17:355-65.
![Page 21: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/21.jpg)
0
10
20
30
40
50
60
70
80
90
100
Time
Kno
wle
dge
of a
dver
se e
ffect
(%)
signalstrengthening
signalfollow-up
signalgeneration
signal assessment
//
//
![Page 22: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/22.jpg)
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
![Page 23: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/23.jpg)
• 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
![Page 24: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/24.jpg)
WHO Collaborating Centre for International Drug Monitoring
The Uppsala Monitoring CentreStora Torget 3, 75320 Uppsala, Sweden
www.who-umc.org
![Page 25: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/25.jpg)
The Uppsala Monitoring Centre
• 1968 - WHO Collaborating Centre for International Drug Monitoring, Geneva
• 1978 - 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
![Page 26: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/26.jpg)
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
![Page 27: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/27.jpg)
Members of WHO Drug Monitoring Programme
0
20
40
60
80
100
1969 1979 1989 1999
Year
No
of
co
un
trie
s
![Page 28: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/28.jpg)
WHO International Pharmacovigilance Programme, March 2006
![Page 29: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/29.jpg)
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
![Page 30: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/30.jpg)
Cumulative number of reports in ’Vigibase’
![Page 31: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/31.jpg)
TOP 10 COUNTRIES
THA 2%
USA 46%
NLD 2%
GBR 13%
DEU 6%
ESP 3%
CAN 5%
AUS 5%
FRA 4%
SWE 3%
OTHERS 11%
![Page 32: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/32.jpg)
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
![Page 33: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/33.jpg)
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
![Page 34: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/34.jpg)
Signal detection at the Uppsala Monitoring Centre
Eur J Clin Pharmacol 1998;54:315-321
A combination of 1. Automated quantitative data mining,
using Bayesian statistics and a neural network architecture (Information Component – ‘IC value’)
2. ‘Triage’3. Human assessment
– National Centres– Review Panel– UMC staff
![Page 35: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/35.jpg)
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
![Page 36: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/36.jpg)
-2
-1
0
1
2
3
4
5
6
79:1 81:1 83:1 85:1 87:1 89:1 91:1 93:1 95:1
Time(year)
Captopril - Coughing
IC
![Page 37: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/37.jpg)
SSRI Neonatal convulsions or neonatal withdrawal syndrome
All SSRI
"2
00
3:1
"
"2
00
2:1
"
"2
00
1:1
"
"2
00
0:1
"
"1
99
9:1
"
"1
99
8:1
"
"1
99
7:1
"
"1
99
6:1
"
"1
99
5:1
"
"1
99
4:1
"
"1
99
3:1
"
"1
99
2:1
"
"1
99
1:1
"
"1
99
0:1
"
"1
98
9:1
"
"1
98
8:1
"
Info
rmati
on
Co
mp
on
en
t
6
4
2
0
-2
-4
-6
![Page 38: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/38.jpg)
Example of results in one Quarter (2004)
Total number of combinations: 60000
No. of associations IC025 > 0: 2300
Triage selection: 560
No. of signals for SIGNAL: 28
![Page 39: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/39.jpg)
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)
![Page 40: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/40.jpg)
The SIGNAL document
• Sent to all National Centres (national distribution)
• Individualized section available to industry
• All recipients encouraged to comment on topics presented
![Page 41: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/41.jpg)
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
![Page 42: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/42.jpg)
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: 482-7.
• Coulter D, et al. Antipsychotic drugs and heart muscle disorders in international pharmacovigilance: data mining study. BMJ 2001;322:1207-9.
![Page 43: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/43.jpg)
Support to National Centres
• Methodology • Terminologies, guidelines• Software (VIGIFLOW)• Harmonisation, standardisation• VIGIMED email discussion group• Annual meetings• Training• Books and brochures
![Page 44: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/44.jpg)
Terminologies, guidelinesLinks with WHO Geneva, CIOMS, ICH
• WHOART• Drug Dictionary• Guidelines for setting up and running of
a Pharmacovigilance Centre www.who-umc.org/DynPage.aspx?id=13136&mn=1512#8
• Herbal ATC• Accepted scientific names of therapeutic
plants. 2005, ISBN 91 974750 3 3.• WHO guidelines on safety monitoring of
herbal medicines
![Page 45: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/45.jpg)
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 92 9036 071 2.)
![Page 46: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/46.jpg)
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
![Page 47: Ronald Meyboom, MD, PhD The Uppsala Monitoring Centre who-umc](https://reader035.vdocument.in/reader035/viewer/2022062314/56812a46550346895d8d831d/html5/thumbnails/47.jpg)
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