Introduction to

Pharmacovigilance

Mondira Bhattacharya, MD

Senior Medical Director, Global Pharmacovigilance

Abbott Laboratories

Disclaimer

• The views and opinions expressed in this

presentation are solely those of the presenter and do not necessarily reflect

those of Abbott Laboratories or any of its affiliated organizations.

Course Overview: Focus on Postmarketing Safety

• History of U.S. Pharmacovigilance (the regulations!)

• Definitions: Pharmacovigilance, ICSR, MedDRA, Signal, Risk

• General PV Processes: Less data driven; greater emphasis on regulatory submissions

– Spontaneous reporting: ICSRs and Aggregate Reports

• Signal Detection and Evaluation: Systematic; Data Driven

– Qualitative – cases/cases series

– Quantitative – disproportionality algorithms

• Risk Management

• Benefit Risk Assessment and its Implications: ongoing evaluation of a drug’s profile

Discipline that employs scientific methodologies to detect, assess and understand adverse events associated with use of drugs/biologicals/vaccines

• Postmarketing activities• Utilizes data gathering from multiple sources: clinical

trials, spontaneous reports, literature, pharmacoepidemiologic studies, registries

• Major task is to identify new safety signals and to better understand the patterns of recognized signals (risk factors, severity, outcome)

PV activities contribute to the understanding of the risk/benefit profile of the drug and to the communication of changes identified to the existing profile

Definition of Pharmacovigilance

History of Drug Safety Regulations1906 Pure Food and Drug Act: Tetanus: contaminated diptheria antitoxin leading to deaths in children

• Required licensing of manufacturers and distributers

• Prevented mislabeling of drugs and adulteration of drugs

• NO requirement for proof of safety/efficacy.

Next major disaster: Elixir of sulfanilamide used to treat gonorrhea and pneumococcal infections was newly introduced in a more flavorful dosage

using a solvent which was the antifreeze diethylene glycol.

> 100 deaths

Only charge against the company was that the “elixir” contained no alcohol.

1938 Food, Drug and Cosmetic Act: requirement for collection of clinical

safety data on and submission of such data to the FDA prior to approval. No postmarketing safety reporting requirements.

Thalidomide Storm

• Thalidomide (sedative/antiemetic) disaster: malformed limbs along with other birth defects reported in Lancet in 1961

• Drug was never approved in the US for morning sickness because reports of fetal malformations were quickly picked up by the press and communicated worldwide

Thalidomide Storm: Outcome

Kefauver-Harris Amendment (1962):

A result of the thalidomide disaster (phocomelia in newborns). Extensive pre-clinical testing, submission of such data to FDA (IND) before clinical testing could begin. Three explicit phases of clinical testing were defined. Proof of efficacy was required.

Also mandated that pharmaceutical manufacturers having an NDA must report AEs to the FDA.

History of U.S. Regulations

• Historical Perspective

- 1967: computerization of AE reports

– 1985 NDA Rewrite : requirement for submission of spontaneous reports; prior to that these reports got filed away as part of IND submissions.

– 1993 MedWatch – devices, vaccines

– 1997 FDA Modernization Act: AERS database

– 2003 Concept Papers on Risk Management

– 2007 FDAAA

Adverse Event

• Any untoward medical occurrence in a

patient…administered a pharmaceutical

product and which does not necessarily

have a causal relationship with this

treatment.

• Can be any sign, symptom, or abnormal

lab result temporally associated with a

treatment.

• Unsolicited reports from health care professionals or consumers

• Includes adverse experiences, medication errors and product quality complaints sent directly to FDA

through the MedWatch program or via a manufacturer.

• Postmarketing surveillance: compilation of these spontaneous reports + data from formal clinical trials + literature reports + pharmacoepidemiological

studies = postmarketing surveillance data

Spontaneous Reporting: Sources of Data

• Identify new (previously unrecognized) ADRs

• Identify risk factors/at-risk populations for known ADRs

• Identify change in reporting of an AE/ADR over time

• Identify manufacturing problems

• Identify medication errors (wrong dose, wrong

patient, drug interactions, use in the face of clear contraindications) are common: estimated to contribute to 44,000-98,000 annual deaths in the

U.S. and are associated with 17-29 billion dollars of excess expenditure.

Uses of Spontaneous

Data

Why do we need spontaneous reporting after drug

approval? Why is Clinical Safety Data Inadequate

for Identifying all Risks?

• Very restricted patient population(inclusion/exclusion criteria; concomitant medications restricted)

• Too small (few thousand)

• Duration of exposure is usually less than 1 year

• Often not designed to identify specific change in incidence of outcomes of the underlying disease

• Errors associated with medical prescribing not captured

• Public failures of our system:

– 20% of new drugs get Black-box warnings

– 4% of new drugs removed from market due to safety reasons (industry inefficiency)

Greatest Challenge for Spontaneous

Reports: Under reporting

HIPPA Regulations have not helped!

Report Quality: Inclusion of details to establish causality: diagnostic test results?, progression of disease?, effect of concomitant medications?, etc.

Biases Affecting Spontaneous Reporting

• Nature of the event

– Severity

– Uniqueness

– Co-morbidity/outcome of disease being treated

• Length of time drug is on the market: first in class vs. later

– Weber effect: peak is 1-2 years after approval; not shown to be true for all classes of drugs

• Publicity/media attention

• Litigation

• Reporting regulations

Triggers for Increased Reporting

0

50

100

150

200

250

300

Jul-1

999

Sep

-199

9N

ov-

199

9Ja

n-2

000

Mar

-200

0M

ay-2

000

Jul-2

000

Sep

-200

0N

ov-

200

0Ja

n-2

001

Mar

-200

1M

ay-2

001

Jul-2

001

Sep

-200

1N

ov-

200

1Ja

n-2

002

Mar

-200

2M

ay-2

002

Jul-2

002

Sep

-200

2N

ov-

200

2Ja

n-2

003

Mar

-200

3M

ay-2

003

# o

f C

ase

s (In

itia

l o

r F

ollo

w-u

p)

0

100

200

300

400

500

600

700

800

900

Pre

scri

pti

on

s

(Th

ou

sa

nd

s)

Initial Versions Follow-up Versions Prescriptions

Another drug

in class

removed

from market

for safety

reasons

←

No denominator available!

Next step - Coding of Events: Medical Dictionary for Regulatory Activities (MedDRA)

• Each event within a report (ICSR – individual case safety report)

• To aggregate reported terms in medically meaningful groupings for the purpose of reviewing and/or analyzing safety data

• To facilitate consistent retrieval of specific cases or medical conditions from a database

• To identify frequency of medically similar ADR/AEs

• To improve consistency in comparing safety data from multiple sources (clinical trials and spontaneous reports)

Features that may Suggest a Causal Relationship:

• Absence of symptoms/condition prior to exposure to drug

• Timing of event in relationship to drug administration suggestive

• Evidence of a positive dechallenge and/or positive rechallenge

• No mitigating factors identified

• Consistency with the drug’s known pharmacological and/or toxicological effects

• Supporting evidence from other sources (clinical studies, nonclinical studies, reports for drugs of the same class)

• Event typically associated with a drug effect (i.e. Steven Johnson Syndrome)

Evaluation of Causality of a Single Case Report: Medical

Assessment and Query = Adverse Drug Reaction (ADR)

MEDICALLY SIGNIFICANT LIST – Examples of

events that require immediate follow-up

Acute respiratory failure/acute

Acute respiratory distress syndrome

Ventricular fibrillation

Torsade de pointes

Malignant hypertension

Convulsive seizures

Agranulocytosis

Aplastic anemia

Toxic epidermal necrolysis

Stevens-Johnson syndrome

Hepatic necrosis

Acute liver failure

Anaphylactic shock

Acute renal failure

Pulmonary hypertension Pulmonary fibrosis

Confirmed or suspected endotoxin shock

Confirmed or suspected transmission of infectious agent

by products

Aggregate Reports: Periodic vs. PSUR

Periodic Report (PADER) PSUR (a)

Covers FDA USA ICH International

Events No required events; analysis of expedited events; non-expedited and fatal reports

Required events (Overdose, Drug Interaction); selected events; analysis of Serious unlisted events

Foreign Reports Non-included / Optional Included

Period Quarterly for 3 yrs. Annual after 3 yrs. Every 6 mos (2yrs), annually (2yrs),

every 3yrs

Total Exposure Not included Included

Studies Targeted safety studies or studies yielding important safety data that were initiated during reporting period

Targeted safety studies or studies yielding significant safety data; tracked until final report

Regulatory Actions taken for safety reasons globally

Actions taken for safety reasons globally

Label Changes USPI Changes during the reporting period

CCDS changes during the reporting period

(a) Only medically confirmed cases are used

CLASSIC CLASSIC

PHARMACOVIGILANCEPHARMACOVIGILANCE

Adverse Drug ReactionAdverse Drug Reaction

No

No

Review Of Data From All SourceReview Of Data From All Source

Aggregate and Present In Aggregate and Present In

Periodic ReportsPeriodic Reports

ChangeChange

RegulatorsRegulators

YesYes

EXPED

ITED

Bulk of effort was to better characterize

what was known and heavily reliant on

company’s own database. Not a very

effective means for identifying signals!

What is a Signal?

Reported information on a possible causal

relationship between an adverse event

and a drug, of which the relationship is

unknown or incompletely documented

previously and which is of enough

interest to justify verification action.

Source: Trinks, Uwe. DIA Conference, Chicago, IL, 2011

How do you find Signals: many routine activities within PV

• Single case of concern (ie:SJS)

• Trial results revealing an imbalance in ADRs

between treatment arms

• Data mining:

– Methodology to identify hidden patterns of association

between use of a drug and an unexpected adverse reaction

– Computer algorithms to analyze records contained in huge drug safety databases.

– Estimated 1000 reports per day are added to FDA AERS database

Data Mining

• It is a prospective, timely methodology for analyzing these reports to ascertain whether there is an excess

of events of concern with use of a drug

• Is now considered an essential adjunct to other PV

activities and needs to be integrated into existing PV processes.

• Databases:

– US FDA-AERS:available through FOI Act (5 month lag)

– WHO Vigibase: licensing agreement

– EMEA Eudra Vigilance:products on EU market; only access to data on their own products

– In house corporate database

Data Mining

• Examination of reported AEs using statistical or mathematical tools to assess for an excess of specific AEsfor a product

• Output is generally a score that quantifies the disproportionality between the observed and expected values for a given product-event combination

• Comparison: assumption for these scores is that the proportion of specific events is the same across all drugs

– This comparison can be modified as appropriate (for example, for an anti-diabetic drug, the comparison may be made only to other anti-diabetic drugs rather than all drugs)

• A threshold is arbitrarily set, with scores above this thresholddeemed in excess of expected and meriting further investigation

Datamining Method

Disproportionality Analysis

Drug of Interest All Other Drugs Total

AE of interest A C A + C

All other AEs B D B + D

Total A + B C + D A + B + C + D

Comparison of relative reporting frequencies

Example:

Proportional Reporting Ratio (PRR) =

AA + B

CC + D

> 9,000 event codes (MedDRA Preferred Terms)> 7,000 drug/biological products by trade names > 60,000,000 drug-event combinations possible!

Data Mining

• Scores are determined using statistical

models

– Multi-item Gamma Poisson Shrinker (MGPS) algorithm

– Proportional Reporting Ratio (PRR) method

– Neural Network Approach

Results of Data Mining

• EBGM: Empirical Bayes Geometric Mean that can be understood as an average ratio of expected to observed events

• EB05: The lower limit of the 95% CI on the EBGM

– Example: if EB05=20, then the drug-event occurred AT LEAST 20 times more frequently in AERS than expected

• Data Mining Signal (“Threshold Interval”) EB05 >=2:

– The drug-event occurred AT LEAST twice as often as expected. This threshold gives assurance that potential signals are unlikely to be noise

Interpretation of Data Mining Results

• Advantages: large, reproducible, comparable – however only hypothesis generating

• Areas of uncertainty:

False associations:

- Drug constantly used with other drugs that do cause the event

- Outcome/event more related to natural history of disease than drug

Missed associations:

- Later in drug class → under reporting

- Event linked to the disease → under reporting

- Event occurs years after initiation of treatment (cancers, heart disease) → under reporting

• No confirmation of a causal relationship between a drug and an AE can be

established through this exercise.

•Case series

– Review of additional cases; if possible, use standardized case definitions (formal criteria for including or excluding a case in the series)

• Literature

• Epidemiologic studies: natural history; safety studies

• Clinical Trial Data

Signal Evaluation:

Confirm/Refute/Understand a Signal

CURRENT CURRENT

PHARMACOVIGILANCEPHARMACOVIGILANCE

SignalSignal

No

Assess SignalAssess Signal

Fully Characterize = Fully Characterize =

Risk ManagementRisk Management

Benefit/Benefit/

Risk AssessmentRisk Assessment

ClinicalClinical

DataData

RegulatoryRegulatory

ReportingReporting

Label & Other Label & Other

ChangesChanges

ADRsADRsDataData

MiningMining

Other Other

SourcesSources

Yes

PeriodicPeriodic

ReportsReports

Altered

Risk Management: The Patient’s

Perspective – Stop the Drug!

“Every substance is a poison; it is only a matter of dose” –

Paracelsus (1493 – 1541)

…and a matter of risk management!

Risk Benefit Decisions

Risk Management View

Maximum Maximum acceptableacceptable

risk for all risk for all

patientspatients

RiskRisk

AcceptableAcceptable

risk for risk for

some some

patients or patients or

physiciansphysicians

BenefitBenefit

Acceptable Acceptable benefit for benefit for

some patientssome patients

or physiciansor physicians

Minimum Minimum

acceptable acceptable

efficacy for efficacy for

all patientsall patients

Disapprove

Risk Management (RM) Zone

Approve

Source: Michael J. Klepper, MD (2006)

• Identify the significant risks and potential risks of the product

• Quantify the risks; identify populations for which risk is not known or quantified

• Identify the subpopulations who face the important risk

• Evaluate early detection and prevention potentials

• Strategic safety program designed to meet specific goals and objectives in minimizing known risks of a product while preserving its benefits.

• Proposed routine PV or active interventions (will include a PPI)but generally involves other activities (e.g.: change to the label, certification of prescribers, medication guide, restricted distribution, etc.)

Risk Management Plans: Quantify,

Characterize and Communicate Risks

FDA vs. EMEA• Convergence rather than divergence

• Both requiring estimation of risk (pharmacoepidemiology) with drug, with population, and lowering the thresholds for identifying risk in the label

• RMP in EU is a requirement, though a risk minimization

plan is not

• REMS is analogous to a risk minimization strategy and will

become more commonplace in the US. REMS must be

accompanied by a timetable for submission of assessments.

• Both utilizing these documents to shift the discussion to one of benefit/risk in a more formalized manner.

T.O.U.C.H. – Tysabri Risk Minimization

Plan• Monoclonal antibody launched in 2004 for treatment of MS

and Crohn’s disease

• Rare, fatal illness associated with use – PML – few cases in 2005

• Removed and reintroduced in 2007 (for relapsing MS only, neurologist only) with restrictive prescribing program that has allowed:- An efficacious drug to be available for a subgroup of patients with MS under

highly restrictive prescribing conditions

- Estimate the incidence rate and outcome of PML in patients using the drug

- Characterize early clinical presentations of PML

- Possibly reduce the number of fatal cases by working with clinicians to introduce new therapies

- Collect and characterize other opportunistic infections associated with use

Drug Safety Update March 2010, vol 3

Neurology Today May 2010, vol 10: 17-18

Summary: Changes in Emphasis within PV

Old Emphasis

• Collection, coding and timely

evaluation and reporting of individual cases

• Reliance on aggregate reports to identify signals (based primarily on

spontaneous reporting which lacks

quality, estimation of exposure)

• Concentration on analysis of

company’s own data

• Not analyzed in the context of reporting rates of similar events

with other drugs

• Less emphasis on the continued

evaluation of the benefit:risk profile of the drug

Current Practices• Collection, coding timely evaluation of ICSRs and

aggegate periodic reports continue.

• Implementation of signal detection methodologies to allow for identification of signals utilizing large

safety databases; standard processes for signal evaluation

• Comparison to epidemiologic data to understand incidence/prevalence in population

• Conduct more safety studies to answer

new/ongoing safety concerns

• Staffing to ensure that qualified persons are

reviewing these data outputs per company processes

• RMPs (including the specific risk minimization plans) provide opportunity to analyze the large volume of spontaneous reports in a more focused

manner and require utilization of data from other sources when risk/safety concerns exist and allows

the company to more formally place them in the context of benefit/risk

PV and Risk Management: Continuous

• Signal Detection: allows us identify what we

do NOT know (the needle in the haystack) –more data driven

• Risk Management/Benefit:Risk Assessments:

allows us to characterize better what we do know and attempt to mitigate the risk and

maintain a favorable profile

Benefit – Risk is a Familiar Concept

Questions?