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Using Oracle's Empirica Topics to Document Your
Signal Management Process
March 7, 2012
Rodney Lemery, MPH, PhD
Vice President, Safety and
Pharmacovigilance
BioPharm Systems, Inc.

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Agenda
• Summary of Signal Management
— CIOMS VIII Suggestions
— Definitions
• Signal Management using Oracle Empirica Products
— Detection
• Use of e-Signal for data mining
— Prioritization
• Accel-Tracker (Prioritization Workflow)
— Evaluation
• Accel-Tracker (Evaluation Workflow)

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Detailed Signal Management Process
Signal
Detection
Signal
Prioritization
Signal
Evaluation

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Signal Management
• The process of identifying, prioritizing and evaluating
determined signals in a data population

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Signal Detection
• The act of looking for and/or identifying signals using event
data from any source. (CIOMS, 2010 p.116)
Signal Prioritization
• The controversial act of applying plausibility criteria to identified
signals in order to place the signals in context and apply
appropriate resources. (Waller, 2010 p.50)
Signal Evaluation
• The act of formally gathering additional data to evaluate the
identified signal for the purpose of risk management. (Waller,
2010 p. 50,51)

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What the Industry Seeks
• A systematic approach to signal
management
 Ability to identify potential issues in clinical and post-
marketing data
 Standard prioritization questions
 Standard evaluation methods to feed risk management
 Pre-defined workflow for these processes
• A system to collect and track this
approach
 Standard system to document the identification,
prioritization and evaluation of signals
 Capability to report this process for audit answering and
justification or risk methods (document due diligence)

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Accel-Tracker
— Using the Empirica Suite (e-Signal and e-Topics) tool as the basic software,
BioPharm has created an accelerator that allows a company to document
the formal signal prioritization and evaluation methods suggested by the
CIOMS VIII working group and a series of decision support articles from the
literature
— The following slides will walk us through a practical example of signal
management, starting with signal identification and followed by signal
prioritization and signal evaluation, resulting in risk identification/mitigation

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Signal Detection
• The Empirica Suite contains the same signal detection tool (used by
the FDA) to identify potential signals based on disproportionality
reporting ratios
• As we’ve seen above, the CIOMS VIII group recommends that signal
management begins with signal detection
— This can be either data mining large repositories or identification of cases or case
series in traditional individual case safety review
• While the process begins with signal detection of individual case
safety reports, eventually the collected ICSRs become large enough for
data mining techniques; the prioritization of the signals becomes an
important aspect of signal management (Waller, 2010, p.50)
1. Ensures focus on appropriate signals – “Hay in a hay stack”
2. Focuses appropriate resource allocation time/energy/money

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Signal Detection Example
• Assuming we are the marketing authorization holder for the
US-marketed product Risedronate (Risedronic Acid)
▫ This is a bisphosphonate used in the treatment of degenerative bone
disease. Its mode of action is the strengthening of bone as well as
the inhibition of bone reabsorbtion.
▫ It was approved on March 27th, 1998 under the trade name
“Actonel”
• We can establish FDA/AERS queries in the e-Signal tool to
identify “hot-spots” of the MedDRA dictionary levels

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Signal Detection Example
• In this example,
we see an EBGM
of ~9.7 in an
interesting SOC

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• The rapid review of SOC data from FDA/AERS seems to
indicate that we may have a signal for some kind of
degradation of the oral cavity warranting tooth extraction to
correct. This signal may warrant further investigation, but we
do not want to waste resources on the following:
• Known issues with the product already well documented
(expected events or well-established safety profiles)
• Co-morbidities or complications due to natural disease progression -
Disease states epidemiologically related to the treatment population
without regard to product exposure
(confounding by indication)
Signal Prioritization

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Signal Prioritization
• Prioritization of signals is a critical aspect of signal
management when mining large repositories of data
(Waller, 2010, p.50)
1. Simplifies the often daunting task of signal management
2. Focuses appropriate resource allocation time/energy/money

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Signal Management Challenge: Where do we begin?
• No real standard in the prioritization process (Waller, 2010, p. 50)
— The WHO uses a method similar to Emergency Room triage processes in hospital
settings to quickly evaluate the aspects of a 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

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Accel-Tracker
— Using the e-Topics tool as the basic software, BioPharm has created an
accelerator that allows a company to document the formal signal
prioritization and evaluation methods suggested by the CIOMS VIII working
group and a series of decision support articles from the literature
— Once a signal is identified, a topic is created in e-Topics and assigned to the
appropriate work-group in a standard workflow within the system

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Accel-Tracker

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Accel-Tracker
— Once the signal is placed into the initial Signal Prioritization step, the Accel-
Tracker system allows the formal prioritization, according to the CIOMS VIII
methodology and a series of decision support articles in the literature
— This is a series of questions that allow the categorization of the signal
according to signal strength (S), novelty (N), clinical importance (I), potential
for prevention techniques (P) (CIOMS, 2010; Heeley, Waller & Moseley,
2005; Waller, 2010; Waller, Heeley & Moseley, 2005; Waller & Lee, 1999)

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Accel-Tracker

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Accel-Tracker
— Additional
external
documentation
can also be
attached to the
topic to support
the prioritization
of the signal

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Accel-Tracker
— Signals prioritized as
High or Medium are
moved into the Signal
Evaluation workflow
step for further
investigation and signal
workup

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Accel-Tracker
— Actions can be created and assigned to other users in the company
—In this example, an action to review the case series is assigned

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Accel-Tracker
— Using e-Signal, we can drill
down into the case series
that makes up the signal of
interest
—The case series can
be attached to the
topic of interest for
historical
identification

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Accel-Tracker
— Additional
external
documentatio
n can also be
attached to
the topic to
support the
evaluation of
the signal

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Accel-Tracker
— After research on the signal is collected, Accel-Tracker can document
the results of evaluation through the exposure of several custom
questions designed to assist in the formal evaluation of signals
— The signal can be classified and optionally elevated to a Potential or
Identified Risk to begin the Risk Analysis and Mitigation process

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Accel-Tracker
— Using the default abilities of e-Topics, we can run reports documenting
our signal management process at the request of a regulatory authority
or equivalent

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Accel-Tracker
— Complete auditing of the topic case

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Summary
— Using existing literature and Empirica Suite, configured with the Accel-
Tracker settings, we can provide a systematic method for signal
management in a single solution that accomplishes the following:
• Ability to identify potential issues in clinical and post-marketing data
• Standard prioritization questions
• Standard evaluation methods to feed risk management
• Pre-defined workflow for these processes
• Capability to report this process for audit answering and justification
or risk methods (document due diligence)

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Ways to Engage…
• For those not quite ready…
— Collaborate on requirements
• For those in the midst of an e-Topics implementation
— Refine your approach with Accel-Tracker
• In-depth system demonstration of Accel-Tracker
• On-site proof of concept
• Looking to harmonize relevant business processes?

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References
• 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 .
• 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
• 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

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Questions & Answers
Rodney Lemery, MPH, PhD
Vice President, Safety and Pharmacovigilance
BioPharm Systems
(650) 292-5310
rlemery@biopharm.com
info@biopharm.com