Technological advancements have become indispensable in clinical data management in the rapidly evolving clinical trials industry, especially in the post-pandemic era. This article explores how AI, IoT, and cloud computing fundamentally reshape clinical data management. We spoke with Munther Baara, Vice President of Product Strategy and Innovation at EDETEK, to uncover how these technologies meet the complex requirements of modern clinical trials and enhance the responsiveness and adaptability of research efforts.
Moe: How have technology platforms adapted to address the complex requirements of modern clinical data management?
Munther: The CONFORM™ platform epitomizes the evolution necessary in today’s technology platforms to effectively manage modern clinical data complexities. Adopted by four of the top five pharmaceutical companies in the US and facilitating over 2,500 clinical trials, the platform’s real-time data processing capabilities were crucial during the COVID-19 pandemic. It excelled in capturing data directly from patients, handling volumes up to 50,000 individuals, and seamlessly aggregating data from various sources, followed by comprehensive validation and transformation tasks. This capability provides significant advantages by enhancing data quality, increasing compliance, reducing clinical trial costs, and boosting efficiency across the clinical data lifecycle. The scalable architecture of CONFORM™, natively engineered to run on Amazon’s cloud services, offers almost limitless scalability in data processing and storage, dynamically adapting to the demands of many clients and trials of any complexity and size. Timely access to data allows our clients to analyze data rapidly, detect safety and efficacy signals early, and make proactive decisions. Modern metadata-driven platforms also allow for re-usability and optimization of study pipeline configurations, significantly reducing time and effort to achieve production readiness.
Moe: Given the scope of the pandemic’s changes, how do you perceive the industry’s response, particularly regarding data management?
Munther: The pandemic served as a critical inflection point, driving the industry towards adopting technologies that enable faster study start-up and real-time data access and analytics. This shift has improved our responsiveness to emergencies and underscored the importance of robust, adaptable platforms capable of continuous study quality monitoring and data management. Our platform’s capabilities of reusable and pluggable data ingestion adapters, zero-code business rule designer, real-time data validation, scientific alerting, and visualization of
operational and patient data had set new standards for effective data management even before the COVID pandemic, but we observed more adoption by pharma clients in the last two years.
Moe: AI and machine learning have been buzzwords for a while. However, their practical application in clinical data management intrigues many. How do you see AI reshaping this field?
Munther: AI radically transforms clinical data management from a traditionally passive to a dynamically interactive process. We are introducing an AI-supported ecosystem with tools like Chat.IQ, which fosters an engaging, conversational interaction with data. This tool allows scientists and analysts to post complex questions and receive immediate results. Chat.IQ changes the speed and manner of human-to-system interaction in clinical data review. With generative AI, the system responds to queries with instant data listings and visualizations, allowing data managers to delve into detailed inquiries, such as identifying incomplete visits, missing procedures, adverse events, and concomitant medications with non-matching dates and many other quality issues without re-running and waiting for a typical batch of validation rules. The interactive dialogue enhances data management, allowing for quality of data investigation. We are also working on AI-based algorithms to evaluate the audit trail to have the system suggest better CDM designs and the effectiveness of rule-based data validation. In the short term, one of the upcoming AI deliverables in CONFORM will be machine-automated metadata and business rule configuration of a clinical trial to reduce CDM study design work greatly.
Moe: How do platforms adapt to the integration of IoT, and what challenges does this pose?
Munther: Integrating IoT and other data providers into clinical trials introduces complexities, particularly around the sheer volume of data, untraditional data formats, and diversity of data sources, as well as ensuring seamless synchronization. Our platform addresses these challenges by offering clients access to over 120 configurations from a validated global library of data adapters. These adapters support various medical systems and devices, including IoTs. With IoTs, the technical challenges are reliably ingesting and storing a massive amount of data that often comes in real-time while performing data aggregation applicable to a particular provider and clinical trial. We have resolved these challenges with our scalable technologies, making IoT data actionable. At the same time, our medical alerting application evaluates these data streams in near real-time, and when necessary, our platform immediately informs medical reviewers and sites of the points or patterns of interest. This capability provides business benefits in cardiovascular and other therapeutic areas.
Moe: Can you discuss the recent partnership with Medidata and its impact on EDETEK’s strategic goals?
Munther: Our strategic partnership with Medidata significantly enhances our capabilities in managing clinical trial data more efficiently. This collaboration allows us to optimize the integration of the Rave EDC system with our platform highly, enabling a bi-directional data flow that enriches data quality and compliance. This partnership aligns with our vision to streamline clinical trial management, reduce costs, and improve data integrity across the industry.”
Moe: With your extensive background in pharma, how do you marry the drive for innovation with regulatory compliance within these data management systems?
Munther: “Balancing innovation with compliance is crucial. My extensive experience in pharma has ingrained the importance of embedding compliance into the fabric of innovation. At EDETEK, compliance with industry regulations and standards is not an afterthought but a foundational component of every tool and process we develop; hence, our name is CONFORM. Some components of our platform target the production of compliant data and documents. This approach ensures that as we push the boundaries of what our technologies can do, we remain firmly within regulatory guidelines, ensuring that our innovations are groundbreaking and compliant.”
Through these detailed insights from Munther Baara, we see the profound impact of technological advancements on clinical data management. These innovations meet current challenges and set the stage for future advancements in clinical trial efficiency and effectiveness.
Moe Alsumidaie is Chief Editor of The Clinical Trial Vanguard. Moe holds decades of experience in the clinical trials industry. Moe also serves as Head of Research at CliniBiz and Chief Data Scientist at Annex Clinical Corporation.
