How the Trial Master File is Expected to Evolve in the Next Three Years

The immense transformation in technology over the past decade has accelerated the need to be faster, more prolific, and competent. With the assistance of eTMF technology sponsors and CROs can speed up timelines, reduce the risk of minor and major findings, and better align with regulatory compliance that has been updated for a digital world. Those who have already adopted eTMF applications in particular report upgraded audit and inspection readiness, improved central and remote monitoring, and gained a better understanding of performance metrics.

Here is our take on how eTMF platforms can evolve in the next few years.

1. Increased Adoption of Artificial Intelligence to Automate eTMF Workflows

In the next two to three years, the emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML) can further advance the eTMF by eliminating resource intensive cumbersome tasks to increasing stakeholder collaboration. It can transform the eTMF from being a traditional document repository to an intelligent platform for improved ICH-GCP compliance. With rising workload and complexity in clinical research eTMF system can propel document storage, security and access controls, audit trails, and system validation, and drive compliance throughout the study.

The increasing variability in the documents required by regulatory authorities has steered the need for automation and ML for processing clinical and regulatory documentation. As a move towards greater data standardization, modern-day cloud computing services offer a scalable means to store and process large libraries of documents. The industry’s steady adoption of Standard Reference Model version 3.2 aids in providing more consistent and reliable terminology that ML can identify as metadata. Coalescing the eTMF system with ML can improve TMF operations through more automated document transfer, classification and indexing. For example, with integrated ML it is possible to convert a physical document into structured data that can be automatically processed, and subsequently useful knowledge can be extracted.

1.1. How Machine Learning can enhance the eTMF

A Machine Learning (ML) application uses a neural network, a structure analogous to the network of neurons in the human brain to train a machine to learn from experience by processing examples to analyse without relying on traditional computer programs. With ML, there are a wide range of TMF related manual activities that can be automated based on pattern recognition. For example, the auto-identification and auto-classification of different types of source data, auto-translation of multi-lingual source documents, and auto-redaction of personally identifiable information (PII) are some of the significant benefits that can be realized with ML capability.

1.2 Reducing redundant tasks with predefined integrated workflows

eTMF systems can be configured with pre-defined workflows to trigger event-driven external document exchange as well as internal document management with automated eSignatures that facilitate contract execution, training sign-offs, and internal SOP management within the platform.

1.3 Extraction of Metadata embedded in unstructured text

Manual entry is the most common way firms get metadata into eTMF systems. Metadata consists of attributes that describe a document, such as the research data to which the document relates. System operators depend on metadata to trace documents in eTMF databases. By using optical character recognition (OCR), the neural network can be trained to recognize an extracted attribute such as the name of a study to an index that links the document containing it to the correct study. Thus, ML can minimise manual entry of filing TMF documents by automating classification and indexing. It could also stimulate metadata standardization by decreasing errors and maintaining uniformity. As a result, ML has the potential to fast-track TMF filing processes with fewer corrections and rework.

1.4 Minimizing interoperability challenges with ML

As clinical trials can be large and complex linking many sponsor departments, investigator sites and contract research organisation (CRO), the management of the TMF can become challenging. Automating the process of sharing data across multiple systems leads to minimal development timelines. Thus companies can progress their TMF operations with improved data integration and easy access to auditors. Sponsors have also reported a reasonable decline in labour, acceleration in uploading documents, quality enhancement and standardization.

2. The Rise of Automated Document Quality Control in the eTMF

In recent times, the frequency of compliance updates from regulatory authorities and International Standards Organizations (ISO) has increased. The European Medicines Agency (EMA) published new guidelines on content and essential documents management and archiving of the TMF. With the introduction of these composite guidelines, it is becoming increasingly difficult to remain compliant. Additionally, even the slightest changes in terminology, procedures and processes are bound to increase the compliance efforts.

Considering these impediments, we can predict that modern eTMF systems will have the capability of automated Quality Checks (QC). Automated QC eliminate if not reduce the manual QC findings and provide regular signals for low performing study sites. They will also be capable of organising content within a shorter time frame, and forecasting inspection outcomes to comply with various regulatory requirements.

3. Orchestrating eTMF Real-Time Collaboration between Clinical Research Sites, Sponsors and Regulators

Clearly, the modern eTMF (Electronic Trial Master File) system is no longer a mere manuscript repository. It serves as an active platform for accelerating clinical trials, reducing compliance risks and ensuring real-time collaboration between research sites, sponsors and regulators.

More than ever before, today research is significantly outsourced as the demand for integrated systems has increased to enable better collaboration between sponsors, investigator site and CRO. The systems that hold research content outside of the eTMF (e.g. within external email servers) are usually siloed leading to inconsistent and inaccurate descriptions amongst internal and external teams. As illustrated here, lack of common lexicon and communication between organizations often creates data management challenges when it comes to portraying the entire TMF.

The integration of the eTMF system with the research site and Electronic Investigator Site File (eISF) can ensure TMF completeness. This combination allows for real-time, quality controlled remote monitoring, and document exchange with sites considerably reducing document cycle time. It also moderates the amount of time CRAs spend on site. Compliance risks can be effectively managed by swiftly identifying missing and incomplete documents across the Sponsor, CRO and participating research sites eTMF systems.

Most recently, sponsors and clinical research sites have voiced the need for tools that envision the evolution of Key Performance Indicators (KPIs) throughout the clinical trial. KPIs represent Individual and Vendor Performance, TMF Timeliness, and QC Findings. Although many organizations have KPIs in place, users need TMF completeness metrics for better awareness of their level of inspection readiness.

Keeping up with the growing requirements, eTMF solution providers are introducing more advanced data visualization and reporting capabilities that can describe the entire TMF content. With integrated reporting, researchers will be able to draw connections between data to enable strategic decision-making. In the next three to five years, biopharma companies can expect spontaneous navigation and process mapping between systems that contribute to the TMF. This practice of integrated document management will ease the process of inspection with the complete single source of truth to auditors.

How We Can Help

Techsol’s eSource System Integration and Validation practice focuses on introducing latest technology innovation and best practices that can be scaled to requirements of your organization. With our clinical development and technology expertise, our team can lay down the technology roadmap to implement, validation and optimize your current trial master file management process. To know more, please reach out to us at info@techsollifesciences.com.