June 7, 2024 | Ophthalmic clinical trials are expanding in global reach, incorporating a wide range of geographical areas, sites, personnel, and imaging technologies. Maintaining data integrity, imaging reliability, process efficiency, and regulatory compliance across these multi-faceted environments can be quite challenging—and is why continuity across image collection, processing, and management is now a fundamental “must-have” for ophthalmic clinical trial success. 

Continuity Ensures Cohesion and Consistency Throughout the Ophthalmic Clinical Trial Imaging Lifecycle 

In the context of ophthalmic clinical trials, continuity refers to the integrated and uninterrupted flow of imaging data across all of the trial’s different stages, from the planning and design phase to image collection, data analysis, and reporting. It encompasses the connection and interaction between various scientific and software elements to create a secure, compliant, and contiguous data processing environment, enabling the trial to run as seamlessly as possible, without disruptions and with minimal regulatory compliance risk.  

The most effective way to achieve continuity in ophthalmic clinical trials is by using a consolidated closed-loop imaging management system that works end-to-end from site upload, image QC, and read straight through to data cleaning, reconciliation, and final delivery. Optimally, a system like this incorporates artificial intelligence (AI) throughout as a way to expedite image processing, streamline and guide reader workflows, and facilitate remote patient monitoring and real-time data collection. For this continuity to work well, the critical scientific elements of the study protocol and trial’s desired medical outcomes must be key considerations in the development, delivery, and support of the clinical trial imaging management solution. 

To understand the concept of continuity in ophthalmic clinical trials more thoroughly, let’s explore each of its different dimensions.  

Software Continuity Comprises Multiple Interrelated Components 

In terms of software continuity and the value it brings to an ophthalmic clinical trial, the whole is greater than the sum of its parts. Even so, it is beneficial to consider each of the interrelated elements, which can be sorted into five broad categories: 

• Data Continuity: Ophthalmic clinical trials are rich with data that is collected from a multitude of diverse scanners. Systems integration enables data continuity which ensures that all of this digital information is accurately captured, processed, and transferred between different modules or components without loss or corruption and in a standardized, repeatable manner. For example, using a single image viewing, processing and viewing platform that is agnostic to ophthalmic image format (and scanner type) is critical for generating reliable, unbiased, safety and efficacy data. 

• Process Continuity: Now that ophthalmic clinical trials usually span multiple sites and countries, there’s a growing need for consistency with workflows, such as data entry, validation, analysis, and reporting. Using a standardized platform for data collection, analysis, sharing, and reporting reduces the chances of miscommunication or misinterpretation of results. Further, leveraging AI with human oversight for data entry edit checks and workflow logic checks helps ensure that image QC technicians and image readers perform their activities in a consistent, repeatable, protocol-compliant manner across thousands of study time points. 

• Operational Continuity: The expanded global reach of ophthalmic clinical trials can create hurdles related to variations in image acquisition scanner makes, models, ages, and software from site to site. Site-based ophthalmology and imaging experience can vary as well. Operational continuity helps ensure that a large diversity of scanners, global sites, imaging staff, and levels of training come together and work in harmony to successfully support a clinical trial through the exchange of information and the optimization of processes within the closed-loop imaging management system. One important way operational continuity is achieved starts with a strong scientific collaboration among the clinical trial sponsor, the clinical research organization (CRO), and the ophthalmic imaging core lab. This collaboration will yield an imaging charter that sets the scientific and operational basis for standardized study site qualification and training that minimizes the impact of site-to-site, scanner-to-scanner, and technician-to-technician variability on the study’s data. 

• Maintenance Continuity: Imaging management systems must be able to be updated or modified without causing disruptions to overall functionality. This involves implementing strategies for upgrades, maintenance, and 24/7/365 global multi-lingual technical support. This can be accomplished with IT and product management organizations that have the capacity and expertise to effectively support an imaging management system that is responsible for thousands of studies spanning millions of timepoints collected across the globe.  

• Compliance Continuity: Using an integrated, closed-loop imaging management system creates a fully compliant, unbroken, contiguous quality audit trail. By contrast, utilizing a system that employs multiple third-party software vendors impedes continuity, leading to increased risk for data inconsistencies, quality concerns, and regulatory non-compliance. It is also virtually impossible to guarantee a complete and contiguous audit trail across a study workflow supported by software from disparate third-party vendors. Global ophthalmic clinical trials need the advantage of a cloud-based image and data management platform that is 21 CFR Part 11 and GDPR compliant, and going without this only increases the chances that a new drug or device will NOT achieve regulatory approval.  

The five components of continuity can all be enhanced through the use of AI. For instance, today’s most sophisticated AI technology can accurately identify and segment retinal tissues layers to improve image reader accuracy and consistency, as well as data quality. It can also be used to rapidly assess optical coherence tomography (OCT) and fluorescein angiography (FA) image quality and immediately notify sites if a rescan is required. This kind of “smart” application of AI in global ophthalmic clinical trials can save sites and patients time and headaches, which in turn can lead to increased patient enrollment/retention and improve site compliance.