1. Practical Signal Management
Rodney L. Lemery
Vice President of Safety and Pharmacovigilance
BioPharm Systems, Inc.
Sixth Annual Pacific Drug Safety Summit
September 20-21, 2012
San Francisco, CA USA

2. Disclaimer
• The views and opinions expressed in the following PowerPoint slides are those
of the individual presenter and should not be attributed to BioSoteria, Inc. or
Pacific Drug Safety Summit (“PDSS”).
• These PowerPoint slides are the intellectual property of the individual presenter
and are protected under the copyright laws of the United States of America and
other countries. Used by permission. All rights reserved. BioSoteria, Pacific
Drug Safety Summit and PDSS logo are registered trademarks or trademarks of
BioSoteria, Inc. All other trademarks are the property of their respective
owners.
Practical Signal Management 2

3. Contents
• Part I: Overview of Signal Management
– Common Language
– Current Regulatory Environment
– Proposed Signal Management Methodology
• Prioritization
• Evaluation
– Overview of Decision Support Systems
• Part II: Small Group Break-out
– Description of activity
– Overview of Prozac
– Prioritize signals, evaluate signals, evaluate
risks
Practical Signal Management 3

4. Part I: Overview of Signal
Management
Signal Prioritization
and Evaluation Process
Practical Signal Management

5. Detailed Signal Management Process
Signal
Detection
Signal
Prioritization
Signal
5
Evaluation

6. Simplified Safety Signal Lifecycle
Signal Signal
Detection Prioritization
Signal
Evaluation
CIOMS (2010, p. 9)
Practical Signal Management 6

7. Common Language
• Prevalence – The total number of cases of a disease in
a given population at a specific time
• Incidence – The number of newly diagnosed cases
during a specific time period
• EMA – European Medicines Agency
• ADR – Adverse Drug Reaction
• APR – Adverse Product Reaction
• ICH – International Conference on Harmonization
• CIOMS – Council for International Organizations of
Medical Sciences
Practical Signal Management 7

8. Common Language…
• Two pervasive definitions (Abenhaim, Moore, &
Begaud, 1999)
1. The collection and scientific evaluation of
adverse drug reactions (ADR), under normal
conditions of use for regulatory purpose.
−Restricts the concept to regulatory
Pharmacovigilance compliance only and only medicinal
products.
2. Watchfulness in guarding against danger from
products or providing for safety of the product
−Expansive beyond just regulations and
frames the construct for use in academia
and the sciences
Practical Signal Management 8

9. Common Language…
•The application of
epidemiologic techniques
used to study the effects of
Pharmacoepidemiology
drugs in populations
−First mentioned in the
early 1980’s (Abenhaim,
Moore, & Begaud,
1999)
Practical Signal Management 9

10. Exercise 1
Define the following 1. Please segregate into your
terms: small group as assigned by the
index card in your chair
2. Using collaborative discussion,
please reach consensus for the
Signal definition of the following terms:
Signal Detection  “Signal”
 “Signal Detection”
Signal Prioritization  “Signal Prioritization”
 “Signal Evaluation”
Signal Evaluation 3. Nominate a single
spokesperson from the group to
share the definition with the
larger audience.
Practical Signal Management 10

11. Common Language…
•Much debate on the definition (we will use
the following):
•Information that arises from one or
multiple sources, which suggests a new
potentially causal association, or a new
Signal aspect of a known association, between
an intervention and an event or set of
related events, either adverse or
beneficial, that is judged to be of sufficient
likelihood to justify verificatory actions.
(CIOMS, 2010 p.14)
Practical Signal Management 11

12. Common Language…
•Much debate on the definition (we will use
Signal the following):
•The act of looking for and/or identifying
Detection signals using event data from any source
. (CIOMS, 2010 p.116)
Practical Signal Management 12

13. Common Language…
Waller (2010, p.50) defines this as an
important and controversial method of
ensuring only those signals worthy of
internal resources are passed into the
formal evaluation process
—The WHO uses a method similar to
Emergency Room triage processes in hospital
Signal settings to quickly evaluate the aspects of a
Prioritization case that make it critical for research while
placing other cases on hold until a later
investigation period
—The MHRA uses an analytic methodology
comprised of two mathematical scores
contributing to a final score that will prioritize
the case
—Other articles exist in the literature
suggesting valid decision support methods
Practical Signal Management 13

14. Common Language
•The formal process of reviewing
scientific data sources to refute or
confirm the existence of a signal in a
company product safety profile; this
confirmation will elevate the signal to a
potential or identified risk
Signal •CIOMS VIII (2010, p. 90) indicates that
Evaluation this process should be multi-faceted:
1. Collect evidence to evaluate causal link
between the product and the event
2. Determine if the signal represents an
identified or potential risk
3. Communicate the identified risk and to
propose its further evaluation and
mitigation
Practical Signal Management 14

15. Current Regulatory Environment…
• As of July 2, 2012, the EMA has required among other
things…
– “All validation, prioritisation, assessment, timelines, decisions,
actions, plans, reporting as well as all other key steps should be
recorded and tracked systematically. Tracking systems should be
used for documentation and should also include signals, for which
the validation process conducted was not suggestive of a new
potentially causal association, or a new aspect of a known
association. All records need to be archived” (EMA, 2012).
Practical Signal Management 15

16. Current Regulatory Environment
• In June of 2002, the US Congress reauthorized (for
a second time) the Prescription Drug User Fee Act
(PDUFA III)
– “Specifically, FDA issued three concept papers. Each
paper focused on one aspect of risk management,
including
• (1) conducting premarketing risk assessment
• (2) developing and implementing risk minimization tools
• (3) performing post marketing pharmacovigilance and
pharmacoepidemiologic assessments.” (FDA, 2005)
Practical Signal Management 16

17. Exercise 2
1. Please segregate into your
What does your small group as assigned by the
index card in your chair
company do to 2. Using collaborative discussion,
adhere to these please discuss your response to
requirements? the question to the left of this
slide
3. Nominate a single
spokesperson from the group to
share your team’s perspective
with the larger audience.
Practical Signal Management 17

18. Proposed Signal Management Methodology
• A workflow
to document
the stage of
the signal is
important
especially
when
dealing in
large
volumes of
potential
signals
Practical Signal Management 18

19. Signal Prioritization Methodology
• For our purposes we use the following method to prioritize our signals
for further investigation:
– Is the signal and expected event
(without a change in intensity)?
– Is confounding by indication likely?
– Final prioritization
• High – Signal should be placed into formal
evaluation
• Medium – Signal should be placed into
formal evaluation though evaluation work can
be minimized compared to High signals
• Low – Signal is currently
confounded by indication, expected (known)
• Monitor - Requires additional
information to fully appraise
Practical Signal Management 19

20. Proposed Signal Evaluation Methodology…
• Once prioritized, formal signal evaluation must occur
– CIOMS VII focuses their discussion of this effort on the importance
of confirming the signal strength and using a comprehensive safety
management team approach (CIOMS, 2010 p. 91)
– Final evaluation categories
• Verified – Signal has been confirmed
using scientific sources and
thus should move into a risk
assessment category.
• Refuted – Signal has been refuted
using current epidemiologic,
biologic or other scientific
criteria
• Monitor - Requires additional
information to fully evaluate
Practical Signal Management
the signal 20

21. Proposed Signal Evaluation Methodology…
• Signal strength (S)
– Degree to which we believe the ADR represents a causal relationship
between the drug and the event
– How common is the term?
• Very Common 1:10 affected persons
• Common 1:10 to 1:100 affected persons
• Uncommon 1:100 to 1:1000 affected persons
• Rare 1:1000 to 1:10,000 affected persons
• Very Rare less than 1:10,000 affected persons
– Rechallange proof?
– Positive dose response?
– Supporting Quality Data?
– Is there a consistent trend in epidemiologic
studies/literature?
– Is there evidence of a class effect?
Practical Signal Management 21

22. Proposed Signal Evaluation Methodology…
• Novelty (N)
– Degree to which a signal has not been observed before or the
degree to which the reporting frequency of a known ADR has
changed
– Is this a newly identified signal?
– Is this an existing signal/term that is now increasing in
frequency or intensity over time?
Practical Signal Management 22

23. Proposed Signal Evaluation Methodology…
• Importance [clinically speaking] (I)
– Degree to which such a causal relationship impacts patients’
lives or how the potential relationship is viewed by regulatory
bodies/scientific/legal community
– Is this signal being monitored at the behest of a regulatory
agency?
– Is this signal part of internal targeted surveillance efforts?
– Is this signal part of an ongoing legal issue?
– Is there a significant public interest or concern about the
signal?
Practical Signal Management 23

24. Proposed Signal Evaluation Methodology…
• Prevention potential (P)
– Degree to which an clinical/epidemiological prevention
program could be established to prevent the signal
– Are there existing treatments or preventions in place for this
signal?
– If such a prevention is required, is it practical/likely or not?
Practical Signal Management 24

25. Part II: Small Group Project
Signal Prioritization
and Evaluation of Prozac
Practical Signal Management

26. Overview
• Purpose: To gain experience and exposure in the
practical signal prioritization and evaluation process
and to practice the use of a decision support system
in this analysis
• Product of interest: Fluoxetine (Prozac)
• Population: For any signals, assume all
reporters/patients are >21 and that this is a
category of ADULT sufferers of depression
• Source: Routine signal detection
methods of querying the FDA AERS
database using a data mining query
Practical Signal Management 26

27. Prozac Overview
• Fluoxetine (Prozac) – This selective serotonin ( 5-
hydroxytryptamine [5-HT]) reuptake inhibitor (SSRI) is
used in the treatment of depression, anxiety and
personality disorders (Stahl, 1998)
– Inhibits the reuptake of the neurotransmitter
serotonin into the presynaptic cell resulting in an
increase of serotonin in the synaptic gap
– It often takes several weeks for the body to adapt
the brain to deal with the increased serotonin and its
effect on the downstream synaptic processes
• This can result in anxiety being reported
in patients within the first several weeks
of treatment
Practical Signal Management 27

28. Mechanism of SSRI Action
Practical Signal Management 28

29. Detected Signals (MedDRA PT)
• Retrieved from Adversevents.com on August 28, 2012
Practical Signal Management 29

30. Prozac Package Insert
Practical Signal Management 30

31. Exercise 3
1. Please segregate into your
small group as assigned by the
index card in your chair
2. Please use the information on
the previous several slides to
Prioritize your formally prioritize the signals
according to our methods
signals described above and complete
the following slide
3. Nominate a single
spokesperson from the group to
share your team’s perspective
with the larger audience.
Practical Signal Management 31

32. Confirmed Signals
• Regardless of your small group, we will assume for
the next part of the exercise, that the only
confirmed signal from the data above was
– Completed Suicide
– Suicide Ideation
• Remember too that we are focusing on MDD use
of Prozac so it will be important to understand the
etiology and epidemiology of depression.
Practical Signal Management 32

33. Exercise 4
1. Please segregate into your
small group as assigned by the
index card in your chair
2. Please use the information on
the next several slides to
Evaluate your formally evaluate the signals
according to our methods
signals described above and complete
the following slide
3. Nominate a single
spokesperson from the group to
share your team’s perspective
with the larger audience.
Practical Signal Management 33

34. Small Group Project
• Retrieved using Oracle Empirica Signal on August 28, 2012
Practical Signal Management 34

35. Small Group Project
Reports of Prozac Use
45, 3% and Suicidal Issues
59, 4% • NOTE: These suspect reports
178, 10% of Fluoxetine, Fluoxetine And
Olanzapine use and reports
one of the following PT:
• Completed suicide,
Suicidal behavior,
Elderly Suicidal ideation, Suicide
Adult attempt
Adolescent
Child
1419, 83%
• Retrieved using Oracle Empirica Signal on August 28, 2012
Practical Signal Management 35

36. Small Group Project
Reports of Prozac Use
and Suicidal Issues
181, 11% • NOTE: These suspect reports
of Fluoxetine, Fluoxetine And
Olanzapine use and reports
one of the following PT:
• Completed suicide,
Female Suicidal behavior,
585, Suicidal ideation, Suicide
34% Male attempt
935, Unknown
55%
• Retrieved using Oracle Empirica Signal on August 28, 2012
Practical Signal Management 36

37. Depression Co-Morbidities
• Retrieved from Epoctrates.com on August 28, 2012
Practical Signal Management 37

38. Risk Factors for Depression
• Retrieved from Epoctrates.com on August 28, 2012
Practical Signal Management 38

39. Epidemiology of Depression
• Retrieved from Epoctrates.com on August 28, 2012
Practical Signal Management 39

40. Epidemiology of Depression
• Retrieved from
http://www.nimh.nih.gov/health/publications/the-numbers-
count-mental-disorders-in-
america/index.shtml#MajorDepressive on September 5, 2012
Practical Signal Management 40

41. Epidemiology of Suicide
• Retrieved on September 5, 2012 from http://www.nimh.nih.gov/health/publications/suicide-in-the-
us-statistics-and-prevention/index.shtml 41
Practical Signal Management

42. Epidemiology of Suicide
• Retrieved on September 5, 2012 from http://www.nimh.nih.gov/health/publications/suicide-in-the-us-
statistics-and-prevention/index.shtml 42
Practical Signal Management

43. Epidemiology of Suicide
• Retrieved on September 5, 2012 from
http://www.afsp.org/index.cfm?fuseaction=home.vi
ewPage&page_id=04EA1254-BD31-1FA3-
C549D77E6CA6AA37
Practical Signal Management 43

44. “Completed Suicide” Reports in other SSRI
• Retrieved from Adversevents.com on August 28, 2012 44
Practical Signal Management

45. Class Effect of SSRI
• Retrieved using Oracle Empirica Signal on August 28, 2012
Practical Signal Management 45

46. Class Effect of SSRI (cont.)
• Retrieved using Oracle Empirica Signal on August 28, 2012
Practical Signal Management 46

47. Epidemiologic Study Data
• (Pariente, A., Daveluy, A., Laribie`re-Be´nard,
Practical Signal Management 47 A., Miremont-Salame,G., Begaud, B., and
Moore, N. 2009)

48. Epidemiologic Study Data
• (Barbui, Esposito, and Cipriani, 2009) 48
Practical Signal Management

49. Epidemiologic Study Data
• (Barbui, Esposito, and Cipriani, 2009) 49
Practical Signal Management

50. Decision Support Systems…
• Given the altered regulatory environment (specifically in the
EMA; for now), it is important that we focus our attention to
a related field and see what might be applied from like
experiences
– In the world of traditional health care, billing reimbursements, legal
disputes and other practice specific matters often require clinicians
to justify their particular advocation for patient treatment
• Tan (2010, p. 125) indicates that more and more clinicians
are turning to clinical decision support systems to document
the “…rationalization of the clinical decision-making process
and/or justifying final choices…” (Tan)
Practical Signal Management 50

51. Decision Support Systems
• Given the shifting regulatory environment, perhaps DSS
could assist us in compliance and protect our organizations
from litigation
• I propose the use of such systems (or their equivalent) are
mandatory given the specifics of the EMA regulations
• One such system is Oracle Empirica Topics; this system
empowers organizations to document and track all
decisions surrounding the signal management process
Practical Signal Management 51

52. Exercise 5
Does your company 1. Please segregate into your
use a DSS to small group as assigned by the
document signal index card in your chair
2. Nominate a single
management? spokesperson from the group to
Enter your decisions enter your team’s signal
prioritization and evaluation into
into the DSS the system provided by the
instructor.
Practical Signal Management 52

53. Conclusions
• The current regulatory environment suggests the need for a
comprehensive decision support system surrounding signal
management
• Signal management should include at least prioritization and evaluation
of the signal
• Prioritization is designed to minimize the resource utilization in formal
signal evaluation and to quickly identify major threats to public health
• Evaluation is designed to formally gather scientific evidence to confirm
or refute the prioritized signal
– This may be in the form of existing data or new
pharmaco-epidemiologic investigations
• Decision support systems can be used to
Protect the organization from litigation or regulatory non-compliance
Practical Signal Management 53

54. References
• Barbui, C., Esposito, E., Cipriani, A. (2009). Selective serotonin reuptake
inhibitors and risk of suicide: a systematic review of observational studies.
Canadian Medical Association 180(3)
• Bennett Levitan, B., Yee, C. L., Russo,L., Bayney, R., Thomas, A. P. and
Klincewicz, S. L.. (2008). A Model for Decision Support in Signal Triage. Drug
Safety. 31 (9), pp. 727-735
• Council for International Organizations of Medical Sciences (CIOMS). (2010).
Practical Aspects of Signal Detection in Pharmacovigilance. Report of CIOMS
Working Group VIII, Geneva .
• EMA. (2012). Guideline on good pharmacovigilance practices. Retrieved from
http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2
012/06/WC500129138.pdf on September 10, 2012
• FDA. (2005). Good Pharmacovigilance Practices and Pharmacoepidemiologic
Assessment. Retrieved from
http://www.fda.gov/downloads/regulatoryinformation/guidances/ucm126834.pdf
on September 10, 2012
• Heeley E, Waller P, and Moseley J. (2005). Testing and implementing signal
impact analysis in a regulatory setting: results of a pilot study. Drug Safety 28
(10), pp. 901-6
Practical Signal Management 54

55. References
• Pariente,A., Daveluy, A., Laribie`re-Be´nard, A., Miremont-Salame,G., Begaud,
B., and Moore, N. (2009). Effect of Date of Drug Marketing on
Disproportionality Measures in Pharmacovigilance; The Example of Suicide with
SSRIs Using Data From theUKMHRA. Drug Safety 32 (5): 441-447
• Power, D. J and Sharda, R. (2009). Springer Handbook of Automation.
Springer Berlin Heidelberg. pp. 1539-1548
• Strengthening Pharmaceutical Systems [SPS], (2009). Supporting
Pharmacovigilance in Developing Countries: The Systems Perspective.
Submitted to the U.S. Agency for International Development by the SPS
Program. Arlington, VA: Management Sciences for Health. Retrieved from
http://www.msh.org/projects/sps/SPS-Documents/upload/SPS_PV_Paper.pdf
on August 20, 2012
• Tan, J. (2010). Adaptive Health Management Information Systems. Jones and
Bartlett Publishers, Sudbury MA, USA
• Waller P, Heeley E, and Moseley J. (2005). Impact analysis of signals
detected from spontaneous adverse drug reaction reporting. Drug Safety 28
(1), pp. 843-50
• Waller P, Lee E. (1999). Responding to drug safety issues.
Pharmacoepidemiology and Drug Safety 8 (7), pp. 535-52
• Waller, P. (2010). An Introduction to Pharmacovigilance. Wiley-Blackwell.
Oxford, UK
Practical Signal Management 55

56. Contact
Rodney has over 15 years experience in clinical research
including laboratory experimentation, clinical data
management, clinical trial design, dictionary coding and
safety management/pharmacovigilance.
Rodney has worked for BioPharm Systems for eleven
years now serving in a variety of roles all related to the
technical and/or clinical implementations of software
systems used in the clinical trial process.
Prior to coming to BioPharm Systems Rodney worked at
pharmaceutical and technology companies in the
Dictionary Coding, Statistical Programming and Data
Management areas.
In addition to his current work at BioPharm Systems,
Rodney holds an Associate faculty position at Walden
University teaching Public Health Informatics and disease
surveillance courses.
Rodney holds a Bachelor of Science in Genetic
Engineering, a Masters of Public Health in International
Epidemiology and a Ph.D. in Epidemiology focusing on
Social Epidemiology
Practical Signal Management 56