Streamlining Mid-Study Changes with Technology

Streamlining Mid-Study Changes with Technology

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How many studies have you seen

that do not have a mid-study change?

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zero

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Completed protocols across all clinical trials incurred an

average of 2.3 amendments

Each required an average of 6.9 changes to the protocol

Phase III studies required 8.5 changes per amendment

http://csdd.tufts.edu/news/complete_story/pr_ir_sep-oct_2011

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Protocols are more complex

CRFs are larger

Clinical trials are lasting longer

Clinical trials are global

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and those numbers are growing…

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What’s the impact?

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Time delays

Cost overruns

Regulatory risk

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What’s the impact?

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Why do these impacts occur?

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Why do these impacts occur?

Change Management

Design

Test

Approve

Deploy

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Deployment Challenges

Staggered deployments due to IRB approvals

Manual deployments are subject to human error

Why do these impacts occur?

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Data Migrations

Moving data from Version 1 to Version 2

Site downtime

Lost data

Why do these impacts occur?

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Multi-system Impact

EDC

Coding

Randomization

CTMS

Why do these impacts occur?

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Factors that affect time, cost and risk

Mid-study Change Challenges

Change Management

Deployment Challenges

Data Migrations

Multi-system Impact

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What role should technology play?

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What role should technology play?

Support Real-World Changes

Inclusion / Exclusion

Range checks

Extension visits

…to name a few

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What role should technology play?

Improve Operations

Reduce cost

Accelerate timelines

Lower risk

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How can technology support real-world changes and improve operations?

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Overcoming challenges. Change Management

Does the tool support a process-oriented approach to change management?

Design

Test

Approve

Release

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Overcoming challenges. Change Management

Does the tool produce supporting documents like blank CRFs and annotated CRFs?

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Overcoming challenges. Change Management

Does the tool identify what changed between study revisions so that you can support risk-based verification?

Change Version 1 Version 2

1 – Age Question Text

Are you 18 or older? Are you 17 or older?

2 – Temperature Edit Check

35.0 < temp < 37.0 35.0 < temp < 37.3

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Overcoming challenges. Change Management

Can you easily and consistently move study revisions through separate design, test and approve environments?

Design Test Approve Release

Study Revision 2

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Overcoming challenges. Deployment Challenges

What utilities are in place to support the mid-study deployment process?

Change Type Element Utility

Add Edit Check Reconcile data

Remove Edit Check Reconcile data

Add Question (All Patients)

Update Questions

Add Question (Specific Patients)

Update Question Type Change answer options

Remove Question

Add Form

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Overcoming challenges. Deployment Challenges

Does the update cause downtime or data entry inaccessibility for the sites?

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Overcoming challenges. Data Migrations

Use a tool that does not have to move data for mid-study change updates.

If you have to move data in the tool, create a “checksum” script to ensure the data are safely transferred from one version to the next.

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Overcoming challenges. Multi-system Impact

Don’t lose sight of today’s connected environments!

If your EDC is connected with Coding, CTMS, Randomization, lower risk with a Change Assessment Checklist

Is anything changing that might affect connections with other systems?

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How can the process flow?

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How can the process flow? Design

Identify the change (e.g. a simple edit-check update)

Designer makes the change in the online development environment, reviews her work and flags the version for testing.

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How can the process flow? Test

The tester loads the version, reviews the configuration difference report and is ensured only the temperate edit was modified (release classified as low risk).

The tester runs tests, everything passes and they flag the version for UAT.

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How can the process flow? Approve

Clinical reviews the modification and approves the version.

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How can the process flow? Deploy

The project manager coordinates the deployment with the study team.

A mid-study change utility is run to identify data that falls outside the updated normal range.

The sites are never down.

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In summary…

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Mid-study changes happen

Factors that create delays, add cost and risk include: Change management Deployment challenges Data migrations Multi-system impact

Technology should Support real-world changes Improve operations

Process-oriented technology appropriately applied can help Reduce cost Accelerate timelines Lower risk

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