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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 documentation 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