Rewriting the Rules of Informed Consent Development with AI

How AI and Structured Content Management Are Transforming the ICF Process

Informed consent forms (ICFs) are essential to clinical trials, serving as the primary vehicle for communicating study information to participants in a clear, ethical, and compliant manner. Given their importance to an effective and compliant clinical trial, the process of developing, managing, and localizing ICFs remains one of the most time-consuming and resource-intensive parts of clinical trial startup.

Fortunately, new applications of AI tools in ICF development are changing the way organizations approach this critical process, and can dramatically reduce the time and resources spent on this activity.

Here’s what you need to know:

The ICF Challenge: Complex, Costly, and High-Stakes

Developing, maintaining, and managing updates following protocol amendments to ICFs is one of the most critical—and often underestimated—components of conducting a clinical trial. These documents must satisfy regulatory requirements, ethical obligations, and patient comprehension standards in every country where the trial is conducted. 

For many organizations, the process remains resource-intensive and operationally fragmented due to the high stakes and low margin for error in these heavily reviewed and evaluated documents. Key challenges include:

• Compliance Pressure: Regulatory bodies require ICFs to meet specific content, formatting, and readability standards. These expectations vary by region and are often updated, adding an extra layer of complexity to ensure ongoing compliance, with zero room for error.
• High Volume of Customizations: Each study design, patient population, country, and trial site may require different versions of the ICF. Principal investigators and ethics committees may also have their own preferences. This creates a complex web of documents that are difficult to develop and manage consistently.
• Manual Workflows: In many organizations, the process of authoring, translating, reviewing, and approving ICFs—followed by managing feedback from ethics committees and regulatory authorities—is still largely manual. This increases the risk of version control issues, delays, and human error.
• Budget and Timeline Impact: ICF development can consume up to 12% of a clinical trial’s budget during study conduct—representing hundreds or even thousands in costs, depending on study size and geographic scope. Multiplied across trials and regions, this upfront investment can significantly impact overall clinical operations.

In short, ICFs must be clear, localized, and fully compliant. But the path to achieving this is often inefficient, redundant, and costly. Until recently, technology lacked the sophistication to be trusted with such a critical step in the clinical trial process. However, recent advancements in AI and structured content have caused many forward-thinking teams to explore how these tools can reimagine the ICF process from the ground up.

Rethinking ICF Workflows with AI and Structured Content Management

Traditional approaches to informed consent development rely heavily on manual processes, static template documents, and repeated rework. Teams often start from scratch with each trial or site, adjusting language and formatting for every region, patient population, and regulatory requirement. This not only strains internal resources but increases the risk of inconsistencies, delays, and compliance gaps.

By implementing specialized AI tools and a structured content management system, life sciences organizations can introduce a more modular, scalable, and intelligent approach to creating and localizing ICFs.

Here’s how it works:

Content Modularization with Structured Systems

Component Content Management Systems (CCMS) allow content teams to break ICFs into manageable components, such as standard risk statements, procedure descriptions, or eligibility criteria. Each component can be stored, tagged, and reused across studies, reducing duplication and enabling greater consistency across trial documentation. Instead of drafting new ICFs from the ground up, teams can assemble them from pre-approved building blocks. Those functionalities also enable efficient updates to the master and local ICFs when new protocol amendments are released.

Additionally, managing the regulatory and ethics committee (EC) reviews has typically been a challenge. The solution allows you to capture EC and regulatory feedback directly within the tool—either by improving future AI outputs through continuous model training, or by reflecting more significant comments within the component content directly. 

AI-Driven Efficiency and Quality

AI enhances this modular foundation by automating content population, translation, and validation processes. Natural language processing (NLP) can help identify similar or duplicate content across ICF libraries, while AI populates many parts of a master ICF with information drawn from protocol/investigator brochures, documents, and any other relevant sponsor sources, generating a review-ready ICF in about 30 seconds. Generation of local ICFs from this approved master may then be managed effectively. AI-powered translation tools accelerate localization with terminology that aligns with regulatory expectations and patient literacy guidelines. Built-in QA features can flag inconsistencies or potential compliance issues, reducing review cycles and manual oversight.

Streamlined Collaboration and Oversight

Structured content platforms also make it easier for cross-functional teams—medical writing, clinical operations, regulatory, and legal—to collaborate within a single environment. With role-based permissions and audit trails, stakeholders can confidently manage content updates while maintaining compliance, version control across all markets and studies, and proper documentation of the ICF generation process for the trial master file (TMF).

Flexible Localization and Faster Approvals

Because structured content allows for rapid adaptation and reuse, localized versions of ICFs can be generated more quickly and with fewer errors. This speeds up the submission process to ethics committees and health authorities, ultimately helping studies start on time and stay on track by reducing time spent on the authoring, review, finalization, and translation steps in the submission process.
 

Modernizing ICF Development

Transforming how ICFs are developed doesn’t mean taking shortcuts on compliance or patient understanding. With AI and structured content, you can scale smarter, localize faster, and maintain high standards across global markets.

Ready to modernize your ICF strategy?
Watch our recent webinar, where TransPerfect’s regulatory, medical writing, and content technology experts explore how AI is transforming ICF development—making it simpler, faster, and more cost-effective.