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Collection and Analysis of Drug
Safety Data in Pregnancy
Myla Moretti
Motherisk Program
The Hospital for Sick Children
• to discover possible adverse pregnancy
events related to maternal exposure
during pregnancy
• to identify signals and establish risks early
• to disseminate this information back to
patients and health care providers so that
rationale choices about disease
management in pregnancy can be made
But why?
• drugs are RARELY evaluated in human
pregnancy prior to market release
– pregnant women are actively excluded
• 50% of women will take at least 1 drug in
• patients may require continued
pharmacotherapy in pregnancy
Where are we now?
• currently in Canada there are no
regulated, standardized methods of
collecting or reporting drug safety data in
pregnancy (mostly voluntary)
• worldwide methods vary, but can include:
– manufacturer registries
– observational studies from research facilities
– database linkage (often governmental)
• events can occur long after exposure (at
least the duration of a pregnancy)
• even for teratogens, adverse outcomes
are rare
• physiologic changes in pregnancy and
concomitant exposures make evaluating
the data complex
Strategies: The Registry
• usually initiated by manufacturers (can be
done in house or outsourced)
• spontaneous reporting
• often retrospective (reporting bias)
• variable data quality
• possible duplication of results
• no consistent methodology
US FDA/CDER Document
very comprehensive
when, where, how
active recruitment
sources of follow-up data
how to select comparison groups
data collection and minimum data sets
sample size
Manufacturer’s Registries
• since the guidance documents few NEW
registries were voluntarily initiated
• most still do not generate/collect/report
comparator groups
• very little data analysis or interpretation
– limited to summary reports and case counts
• linkage to experts in the field?
• rarely published in peer review literature
– not readily accessible by clinicians
Strategies: Database Linkage
• populations where health care and
medications are paid for (government/
• duplication
– can occur if there are errors in linkage
cases can be unlinked if patients move
exposure data not verified (ie.Rx records)
huge data sets
good data interpretation
accessible, peer reviewed
Strategies: Observational Study
• research groups or industry
– cohorts or case control studies
• good data quality within a single centre
• some standardization across different
research centres
• can be arduous and cumbersome without
electronic collection
• smaller sample sizes
• good interpretation of data
• accessible, peer reviewed
What is really needed?
Work with existing infrastructure
• a number of centres (research, pharma
and government) have the capability to
provide the expertise to achieve this goal
• Teratogen Information Services and large
obstetric units are ideally situated to
collect the patient data as they encounter
the patients as part of day-to-day
Tool: Electronic Data Collection
• Move towards electronic health records
• Computer usage increasing – storage,
capture, analysis
• Reliance on automation is increasing
• do it right
• make sure its working
• ensure system is secure, validated, tested
• funding for creation and maintenance needed
Uniform Data Standards
• the existing FDA document and currently
published studies suggest good clear
guidelines for a minimum data set
• patients can be good reporters of their
own health information
• uniform data collected electronically can
more easily be linked to existing
databases (prescription, medicare)
The Bottom Line
• the situation is complex
– data that is convincing to one person is
unconvincing to another
• standardization and a defined data set will
promote good data collection
• electronic capture software can be
implemented across various sites, thus
increasing sample size
• link human expertise to interpret data
– statisticians, clinicians, epidemiologists,