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Good Pharmacovigilance Good Pharmacovigilance Practices Practices Min Chen, RPh Min Chen, RPh Associate Director, Associate Director, Division of Drug Risk Evaluation Division of Drug Risk Evaluation Office of Drug Safety, CDER Office of Drug Safety, CDER

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Page 1: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

Good Pharmacovigilance PracticesGood Pharmacovigilance Practices

Min Chen, RPhMin Chen, RPh

Associate Director,Associate Director,

Division of Drug Risk EvaluationDivision of Drug Risk Evaluation

Office of Drug Safety, CDEROffice of Drug Safety, CDER

Page 2: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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What is Pharmacovigilance?What is Pharmacovigilance?

• Is generally regarded as all postapproval Is generally regarded as all postapproval scientific and data gathering activities scientific and data gathering activities relating to the detection, assessment, relating to the detection, assessment, understanding, and prevention of adverse understanding, and prevention of adverse events or any other product-related events or any other product-related problemsproblems

• This includes the use of This includes the use of pharmacoepidemiologic studiespharmacoepidemiologic studies

Page 3: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Good Pharmacovigilance Practice Good Pharmacovigilance Practice starts by acquiring complete data from starts by acquiring complete data from

spontaneous adverse event reportsspontaneous adverse event reports

Page 4: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Characteristics of a Characteristics of a Good Case ReportGood Case Report

• Adverse event(s) detailsAdverse event(s) details• Baseline patient characteristicsBaseline patient characteristics• Therapy detailsTherapy details• Time to onset of signs or symptomsTime to onset of signs or symptoms• Diagnosis of the event(s)Diagnosis of the event(s)• Clinical course of the event and outcomesClinical course of the event and outcomes• Laboratory dataLaboratory data

• Any other relevant informationAny other relevant information

Page 5: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Good Medication Error ReportGood Medication Error Report

• Product(s) involvedProduct(s) involved• Sequence of events leading to the errorSequence of events leading to the error• Work environment in which the error Work environment in which the error

occurredoccurred• Types of personnel involved with the errorTypes of personnel involved with the error• Narratives- follow NCC MERP taxonomy Narratives- follow NCC MERP taxonomy

(National Coordinating Council for Medication (National Coordinating Council for Medication Error Reporting and Prevention)Error Reporting and Prevention)

Page 6: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Case Series DevelopmentCase Series Development

• Includes spontaneous case reports and Includes spontaneous case reports and scientific literature case reports scientific literature case reports

• Good database search strategies using Good database search strategies using MedDRA terminologyMedDRA terminology

• Case definitions may be developed to Case definitions may be developed to provide consistent characterizations of provide consistent characterizations of the adverse events, and to facilitate the adverse events, and to facilitate retrieval of all clinically relevant casesretrieval of all clinically relevant cases

Page 7: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Assessing CausalityAssessing Causality• It is rarely certain whether an event is product It is rarely certain whether an event is product

inducedinduced• Features supportive of an associationFeatures supportive of an association– event occurred in the expected timeframe event occurred in the expected timeframe – absence of symptoms prior to exposureabsence of symptoms prior to exposure– absence of co-morbid conditions or use of absence of co-morbid conditions or use of

concomitant medications concomitant medications – (+) dechallenge, (+) rechallenge(+) dechallenge, (+) rechallenge– event consistent with the established event consistent with the established

mechanism of action of product mechanism of action of product • Grouping case reports into “probable,” “possible,” Grouping case reports into “probable,” “possible,”

and “unlikely” when appropriateand “unlikely” when appropriate

Page 8: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Safety SignalsSafety Signals • An apparent excess of adverse events An apparent excess of adverse events

associated with a product’s useassociated with a product’s use– a single well-documented case report may be a single well-documented case report may be

viewed as a signalviewed as a signal

– preclinical findingspreclinical findings

– experience with other similar products in the experience with other similar products in the classclass

• May be further assessed in terms of May be further assessed in terms of magnitude, population at risk, changes in magnitude, population at risk, changes in risk over time, biological plausibility and risk over time, biological plausibility and other factorsother factors

Page 9: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Data Mining As a Signaling ToolData Mining As a Signaling Tool

• Uses raw case report data and arrays of all drug-Uses raw case report data and arrays of all drug-adverse events combinationsadverse events combinations

• Calculates “expected” (E) number of events for Calculates “expected” (E) number of events for all drugs, then compares each drug’s “observed” all drugs, then compares each drug’s “observed” (O) to “expected” (O) to “expected”

• Various methods may be used to generate Various methods may be used to generate relative signal scores (intensity) of O:Erelative signal scores (intensity) of O:E

• May be useful adjunct to routine safety signaling May be useful adjunct to routine safety signaling methods methods

• Further exploration and validation is neededFurther exploration and validation is needed

Page 10: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Safety Signals May Be...Safety Signals May Be...

• New unlabeled adverse eventsNew unlabeled adverse events• An observed increase in the severity or An observed increase in the severity or

specificity of a labeled eventspecificity of a labeled event• An observed increase in the frequency of a An observed increase in the frequency of a

labeled eventlabeled event• New interactionsNew interactions• Confusion with a product’s name, Confusion with a product’s name,

packaging or use, either actual or potentialpackaging or use, either actual or potential

Page 11: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Understanding Safety SignalsUnderstanding Safety Signals

• Demographics - age, gender, raceDemographics - age, gender, race• Effect of exposure duration and doseEffect of exposure duration and dose• Relationship between concomitant Relationship between concomitant

medications and potential interactions and medications and potential interactions and the risk of eventthe risk of event

• Relationship between co-morbid Relationship between co-morbid conditions and the risk of eventconditions and the risk of event

Page 12: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Understanding Safety Signals (cont’d)Understanding Safety Signals (cont’d)

• Effects of lot-to-lot variation and Effects of lot-to-lot variation and differences in product formulation and the differences in product formulation and the risk of the eventrisk of the event

• Potential for an excess of adverse events Potential for an excess of adverse events given the disease being treatedgiven the disease being treated

• Estimates of the magnitude of risk or Estimates of the magnitude of risk or differences from known background ratesdifferences from known background rates

Page 13: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Questions for Public CommentQuestions for Public Comment

How can the quality of spontaneously reported How can the quality of spontaneously reported case reports be improved?case reports be improved?

Page 14: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Questions for Public CommentQuestions for Public Comment

What are possible advantages or What are possible advantages or disadvantages of applying data mining disadvantages of applying data mining

techniques (e.g., empirical Bayesian techniques (e.g., empirical Bayesian techniques, proportional reporting ratios) to techniques, proportional reporting ratios) to

spontaneous reports databases for the spontaneous reports databases for the purpose of identifying safety signals?purpose of identifying safety signals?

Page 15: Good Pharmacovigilance Practices Min Chen, RPh Associate Director, Division of Drug Risk Evaluation Office of Drug Safety, CDER

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Questions for Public CommentQuestions for Public Comment

What are possible advantages or What are possible advantages or disadvantages of performing causality disadvantages of performing causality

assessments at the individual case level?assessments at the individual case level?