Observational Studies: Strategic, Operational and Budgetary Considerations

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Observational Studies: Strategic, Operational and Budgetary Considerations 11 January 2011 Jeff Trotter – Executive Vice President – Phase IV Development

Transcript of Observational Studies: Strategic, Operational and Budgetary Considerations

Page 1: Observational Studies: Strategic, Operational and Budgetary Considerations

Observational Studies:Strategic, Operational and Budgetary Considerations

11 January 2011

Jeff Trotter – Executive Vice President – Phase IV Development

Page 2: Observational Studies: Strategic, Operational and Budgetary Considerations

Post-approval research today – Safety and value► Requirement

► In some countries, ‘real world’ post-approval experience data must be submitted to maintain market approval.

► Increasingly, some form of safety surveillance / risk management program will be mandated and enforced.

► Responsibility

► Corporate accountability for post-approval safety is increasingly expected by various constituencies.

► Documentation of clinical / economic / humanistic value is critical for commercial acceptance and accelerated product uptake.

► Opportunity

► If managed proactively, safety surveillance obligation can be controlled.

► An observational study can be a cost-effective, high ROI mechanism for fulfilling the post-approval obligation for both safety and effectiveness data.

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Real world perspectives

Real world research

“The conditions under which products are examined for regulatory approval are generally not the conditions under which they are actually used…”

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► …RCTs can be too artificial in intent and design, and therefore poorly reflective of actual medical practice

► Tight inclusion criteria

► Experimental protocol

► Tight procedural control

► Randomization, blinding, placebo, etc.

► Short in duration

► Homogeneous sites

► We need to know how a product is used and how it “performs” under real world conditions

► Safety

► Clinical outcomes (CER)

► Economic value

► Humanistic value

Real world (observational) studies are needed, because…

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Operational Issues and Challenges

►Site selection

►Site training and start-up

►Site “interaction” (monitoring) and management

► Site motivation

► Protocol “adherence”

> Inclusion

> Procedures

►Data management► Accommodating multiple

measures

► EDC issues

► Data quality> SDV

►Analysis► Biases, etc.

► Findings

► Reporting (communications

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Observational Studies are a “different animal”

So, who “owns” it…?

► HEOR

► Epidemiology

► Medical Affairs

► Marketing / Product Management

► Clinical Operations

► Development

► Safety / PV

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CRO

Proposal

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Product Management, HEOR

Clin OpsRFP/Bid Grid

Outsourcing

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Highlights from survey on Observational Research ► Motivation: “Schizophrenic” RFPs

► i.e., uncertainty, inconsistency, imprecision, over-engineering, etc.

► Many functional areas have some involvement in observational research studies

► Many different purposes underlie these studies

► “Observational research” goes by many names

► Sponsors have varying levels of “comfort” with observational research

► Most sponsors do not have defined processes for observational studies

► Design, Procurement, Operational, Analytical, etc.

► Sponsors have varying expectations for the “conclusiveness” of findings from observational studies

► Sponsors are concerned that regulatory/health authorities “don’t get it”

► Sponsors plan to become increasingly involved in observational research

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Observational Research: Budgetary Implications

► Observational Research is a different animal

► Strategic objectives

► Activities, resources, units

► Process

► Applying “traditional” processes to an Observational Study leads to…

► Over-engineered, overly expensive study

► Study not properly designed

► Project not undertaken

► Need for clarity and flexibility

► Observational Research may be outside traditional comfort zones

► Specialized skills are required

► Observational Studies can be very cost-efficient

► Balance objectives, analytical granularity, data management, etc.