As clinical development portfolios grow in scale and complexity, Pharma organizations continue to face a familiar challenge: EDC design remains one of the most time consuming and variable components of study start up. Despite advances in digital execution, EDC design is still largely manual, repetitive, and dependent on individual interpretation of protocols, standards, and historical designs.

EDC Recommender was developed to address this challenge directly—by accelerating and standardizing EDC design at the point where variability has the greatest downstream impact. Understanding when to deploy EDC Recommender, and which trials benefit most, is key to realizing its full value.

This guide outlines best practice scenarios for deploying EDC Recommender across the clinical trial lifecycle.

Why Timing Matters in EDC Design

EDC design decisions made immediately after protocol finalization influence far more than database build timelines. Inconsistent or manual design choices early on often cascade into:

• Extended UAT cycles
• Rework during data cleaning
• Inconsistencies across studies within a program
• Delays in downstream activities such as SDTM mapping and analysis

EDC Recommender is most effective when deployed as soon as the protocol is finalized, before manual build activities begin. By automating the generation of a protocol specific EDC design at this stage, sponsors can significantly reduce variability and rework later in the study lifecycle.

Deploy EDC Recommender Immediately Post Protocol Finalization

EDC Recommender is designed to operate directly from the digital protocol, using an AI model to read protocol content, apply defined business rules, and pull reusable design components from a centralized EDC design library.

Best practice:

Deploy EDC Recommender as the first step following protocol finalization to generate the initial EDC design, including visits, forms, fields, code lists, and edit checks.

This approach delivers:

• Up to 62% time savings in generating the initial EDC design
• Faster transition from protocol approval to initial EDC design
• A consistent, standards aligned starting point for review

By addressing design variability before build execution begins, teams avoid carrying inefficiencies forward into later phases.

Use EDC Recommender for Studies Where Start Up Speed Is Critical

EDC Recommender is particularly well suited for trials where compressed start up timelines are a priority.

Ideal scenarios include:

• Programs with aggressive first patient in targets
• Studies where delayed start up has downstream commercial or portfolio impact
• Organizations seeking more predictable EDC build timelines

Using EDC Recommender, sponsors can achieve:

• Four week EDC build timelines for highly standardized studies
• Eight week EDC build timelines for studies requiring sponsor approved or IQVIA standards and limited customization

Because the initial design is automated and standards driven, faster timelines do not come at the expense of quality or compliance.

Deploy EDC Recommender Across Repeat or Programmatic Studies

One of the most effective uses of EDC Recommender is across programmatic or repeat studies, where consistency across trials is essential.

EDC Recommender leverages:

• IQVIA standards
• Approved sponsor standards
• Historical study designs stored in a centralized design library

This enables design reuse and standardization across studies, ensuring that EDC designs remain consistent from trial to trial.

Best suited for:

• Development programs with multiple studies in the same indication
• Sponsors seeking greater consistency across their EDC portfolios
• Organizations looking to reduce variation in downstream data handling and analysis

By applying centrally defined business rules, EDC Recommender ensures repeatable design decisions that support program level efficiency.

Select the Right EDC Design Model Based on Trial Complexity

EDC Recommender underpins three EDC design models, allowing sponsors to align deployment with trial complexity and governance requirements.

Accelerated Model

Best for:

• Highly standardized studies
• Sponsors prioritizing speed and cost efficiency
• Minimal sponsor involvement and no sponsor UAT

Supports a four-week build timeline using IQVIA standards only.

Standard Model

Best for:

• Studies requiring sponsor approved or IQVIA standards
• One round of sponsor UAT
• Balanced speed and control

Supports an eight-week build timeline.

Custom Model

Best for:

• Complex programs requiring sponsor specific standards
• Broader integrations and multiple UAT cycles
• Higher levels of customization

Build timelines reflect the added complexity, while still benefiting from a consistent, automated starting point.

Across all models, EDC Recommender ensures traceability, consistency, and predictability at the design stage.

Focus Expert Review Where It Adds the Most Value

A common concern with accelerated design is reduced review time. In practice, the opposite is true.

Because EDC Recommender generates consistent, standards driven designs, review teams can:

• Focus on protocol specific elements
• Avoid re reviewing established, approved content
• Spend less time on repetitive validation

EDC Recommender does not remove the human from the loop. It removes inefficiency—allowing expert oversight to be applied where it delivers the greatest value.

Realizing the Full Value of EDC Recommender

EDC Recommender is most effective when deployed deliberately—early in the study lifecycle, aligned to trial complexity, and scaled across programs where consistency and speed matter most. By delivering up to 62% time savings, enabling four- to eight-week EDC build timelines, and reducing downstream rework, EDC Recommender helps Pharma organizations move from manual, variable EDC design toward a more automated, predictable, and scalable approach.

To explore how EDC Recommender can be deployed across your clinical portfolio and aligned to your standards, platforms, and governance model, contact IQVIA to discuss a custom EDC design strategy tailored to your organization’s clinical development goals.