Information on adverse drug effects is collected to monitor patterns of use, detect new safety signals that were not discovered in clinical trials, and update benefit:risk profile of marketed drugs. Accurate information on the safety profile and the limitations of use is in the best interest of patients and physicians as well as manufacturers and insurers. Denial of a useful drug to a patient who may benefit from it is as harmful as prescribing it to a patient who is likely to develop an adverse event. The main limitations are the lack of epidemiological indicators, variable quality of data, and lacking causality assessments. The system needs to improve to achieve higher accuracy and speed of detection of safety data to provide valid, reliable, and accurate information for benefit:risk assessment.

1. Pharmacovigilance as integral part of
hospital Quality Management Systems
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3. Data Collection
Implicit Guidance and Control
• Title 21 CFR Section 314.80
• E2E Pharmacovigilance Planning
• Article 24 of Regulation (EC) No 726/2004
• Article 107 and 107a of Directive 2001/83/EC
• Electronic submission under ICH-E2B(R3)
• Good PV Guideline (GVP)
• Off-label Use in PV (EMA/293194/2016)
• ICSRs from literature (EMA/161530/2014)
• Good practice guide medication errors
Compliance-driven discipline
Over-specialization
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4. Data Collection
Unfolding circumstances
• Treatment guidelines and standards of care
• Standard and new treatment protocols
• Off-label use
• Creative use by patients, abuse and misuse
Outside information
• Unreported Adverse Drug Events
• Patient experience
Interaction with environment
• Social media hot topics, true or not
• Reimbursement, pharmaco-economics
• Availability and real-life use
• Counterfeit, falsified and substandard drugs
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5. Data Gaps
• Exposure data not available
 Incidence and prevalence unknown
• Indication typically not collected
 Risk:benefit profile of off-label uses
 Standard and new treatment protocols
• Voluntary reporting by physicians in the U.S.
 Incomplete picture
 Medication errors inconsistently reported
 ADR vs. ADE vs. Quality concerns
• Overdose and abuse
 Not subject to expedited reporting, PSUR only
• Efficacy and comparative efficacy data
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6. Orientation
• Compliance as the key driver
• Dominant IT providers define form
Signal detection: case review &
disproportionality analysis
 Human factors affect detection
threshold
 Organizational culture defines
response to safety concerns
 Significant uncertainty
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7. Hospital QMS v. PV systems
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Adverse Drug
Reactions
Medication Errors Adverse Drug Events
Adverse drug reaction: “Harm
directly caused by a drug at normal
doses”
Medication error: “Inappropriate
use of a drug that may or may not
result in harm”
Adverse Drug Events: All harms
that occur during medical care that
are directly caused by the drug
including medication errors, ADRs,
allergic reactions and overdoses
HRET, 2017 and DHHS, 2014
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8. Adverse Drug Events
Inpatient settings
• ADEs account for 1 in 3 of all hospital AEs
• 30% of inpatients experience an ADE
• Affect 2 million hospital stays each year
• 40-50 ADEs / 1,000 hospital discharges
• Prolong hospital stays by 1.7 to 4.6 days
Outpatient settings
• Over 3.5 million physician office visits
• 1 million emergency department visits
• 125,000 hospital admissions
Highest risk
• Elderly
• Pediatric patients
• Multiple medications
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HRET, 2017 and DHHS, 2014
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Measure Numerator Denominator
Target
Reduction
Departmental
Measure Alignment
Rate of visits to U.S.
hospital EDs for
injury from oral
anticoagulants
Number of visits to
U.S. hospital EDs
for injury from oral
anticoagulants
Number of patients
receiving dispensed
oral anticoagulants
in U.S. retail
outpatient settings
10% HHS Healthy People
2020Medical Product
Safety Objective 5.1
Rate of visits to U.S.
hospital EDs for
injury from insulin
Number of visits to
U.S. hospital EDs
for injury from
insulin
Number of patients
receiving dispensed
insulin in U.S. retail
outpatient settings
10% HHS Healthy People
2020Medical Product
Safety Objective 5.2
Rate of visits to U.S.
hospital EDs for
injury associated
with therapeutic use
of opioid analgesics
Number of visits to
U.S. hospital EDs
for injury associated
with therapeutic use
of opioid analgesics
Number of patients
receiving dispensed
opioid analgesics in
U.S. retail outpatient
settings
10% HHS Healthy People
2020Medical Product
Safety Objective 2.3
ODPHP (2017). National Targets and Measures - Adverse Drug Events - health.gov. [online]
Health.gov. Available at: https://health.gov/hcq/ade-measures.asp [Accessed 26 Nov. 2017].
Adverse Drug Events
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ICSRs: Clinical trials, PMS, PASS, Literature
Company databases, monitoring systems
Signaldetection
No action
Triage of Outputs & Interpretation
Impact Assessment
ICSR review
Aggregate reports, PSURs
NI studies, class analysis
Data mining algorithms
Disproportionality
reporting ratios
Signal evaluation
Signalprioritization
• ICSR review
• Aggregate analysis
• Periodic reports
• NI studies
• Class analysis
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Large-sample confidence intervals (CI) for reliability and validity:
(a) both estimates from random samples;
(b) reliability from a random sample but validity from a selected sample;
(c) validity from a random sample but reliability from a selected sample;
(d) both estimates from selected samples.
Good reliability
Poor validity
Poor reliability
Good average validity
Good reliability
Good validity
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12. Decide & Act
• FAERS data
• EudraVigilance data
• PRAC reviews
• Product label updates
• Box warnings
• RMP/REMS
• Product withdrawal
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Level of evidence Number (%) of withdrawals
All marketed drugs
(n = 462)
Marketed drugs
launched since
1950 (n = 286)
Level 1: Systematic reviews 6 (1.3) 6 (2.1)
Level 2: Randomized studies 27 (5.8) 25 (8.7)
Level 3: Non-randomized studies 43 (9.3) 30 (10.5)
Level 4: Case reports 330 (71.4) 189 (66.1)
Level 5: Mechanism-based reasoning 56 (12.1) 36 (12.6)
Levels of evidence used to justify post-
marketing withdrawal of medicinal products
Onakpoya, I., Heneghan, C. and Aronson, J. (2016). Post-marketing withdrawal of 462 medicinal products
because of adverse drug reactions: a systematic review of the world literature. BMC Medicine, 14(1).
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Marketing budget/
marketing efforts
Doctor's Likelihood
to prescribe drugevent reports
serious adverse
Number of reliable
collected
data
Quality of
Pharmaceutica
company earnings
Number of prescriptions
given to patients
Rapidly detected
negative side effects
Drug
Toxicity
Number of
therapeutic
alternatives
Doctor's Reporting
Rate
Strength and clarity of
causal link between
adverse events and the drug
Earnin
expectations
Medical
Journal
Advertisements
Number of patient
drug requests
Education programs
for doctors
published
negative studies
Number of
Number of
favorable studies
published
safety research
sponsor post-approval
Funds available to
Percentage of
by big payers
full price paid
Time left on
drugs's patent
and promotion
on drug
FDA control
serious adverse events
Total number of
Sales Force
Detailing
DTC
advertising
coverage of drug
Other information
including patient
feedback, past
experience,
word of mouth
Market size
Market ShareDrug price
Third party
Leveson, N: Applying System Engineering to Pharmaceutical Safety
The direct effects of an improved information system
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15. Threats to
enterprise
Compliance Failure
Diverse requirements
Fluid and changing
Accidents
Drug shortages
Forced improvisation
PHI breaches
Business sector competition
Dominant IT providers
Stove-piping & groupthink
Failure to innovate
Mergers and acquisitions
Incompetence & Corruption
Local and national interests
Off-shoring operations
Access to global talent
Cultural differences
Training
Organized crime
Civil disruption
Natural disaster
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16. Summary
• Gaps in observation: Exposure data, patterns of use
• Compliance-driven discipline, other threats disregarded
• Customers other than regulators and sponsors often ignored
• Dominant IT providers define form, limit innovation
• PV signal detection relies on disproportionality analysis
• PV reporting poorly captures patterns of use and trends
• Level 4 evidence (case reports) used for most withdrawals
• ADEs routinely monitored as part of QMS
• Most ADEs attributed to anticoagulants, insulins and opioids
• Improvement in information environment crucial
• Future: utilization of real-world data in standard PMS
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