In the rapidly evolving pharmaceutical and biotech industries, efficient and effective clinical data management (CDM) is paramount. As companies strive to bring new therapies to market faster, the demand for high-quality, accurate, and complete data from clinical trials has never been greater. CDM not only ensures compliance with stringent regulatory standards but also significantly reduces the time from drug development to marketing by streamlining data collection, cleaning, and management processes. EDETEK, with its innovative CONFORM™ Informatics platform, stands at the forefront of this transformation, providing cutting-edge solutions that meet the diverse and complex needs of modern clinical trials.
Peter Smilansky, the Senior Vice President, Product Strategy has over 25 years of information technology experience in the life sciences industry and leads the product teams to ensure the EDETEK conform platform vision and philosophy is applied throughout.
Let us dive into this insightful and enriching interview to know more about EDETEK and Peter’s vision for the future of EDETEK:
Can you provide our readers with an overview of the current data management needs of pharmaceutical and biotech companies?
Clinical Data Management (CDM) is a vital element to ensure the delivery of high-quality, accurate, complete, and statistically sound data from clinical trials and studies. CDM reduces the time from drug development to marketing by efficiently collecting, cleaning, and managing subject data in accordance to stringent regulatory standards. This process combines meticulous data collection and electronic data capture with the involvement of team members across all stages of clinical trial design and execution.
In the evolving landscape of clinical development, clinical data management continues to play a critical role, leveraging analytical tools and software technologies to streamline management of study data according to established standards and government regulations while ensuring integrity, confidentiality and regular quality assessment of the data.
How has this changed in recent years?
The pandemic served as a critical inflection point, driving the industry towards adopting data management technologies that enable faster study configuration and real-time data access and analytics. This shift has not only improved our responsiveness to emergencies but has also underscored the importance of robust, adaptable software platforms capable of continuous study quality monitoring and data management. The pandemic catapulted the industry towards adopting new and more nimble processes. This change in thinking led to the implementation of real-time data processing frameworks capable of managing studies of greater volume and complexity.
Cloud-based solutions driven by scalability, security, flexibility, and cost-effectiveness have become an increasingly popular choice in the life sciences industry. EDETEK’s CONFORM™ Informatics platform helps clinical trial sponsors and their data management and biometrics teams to ingest, monitor, clean, transform, analyze and submit the data swiftly.
Our CONFORM platform’s capabilities of reusable and pluggable data ingestion adapters, zero-code business rule designer, real-time data aggregation, validation, scientific alerting and visualization of operational and patient data has set new standards for effective data management. EDETEK pioneered these before the COVID pandemic — but we observed more adoption by pharma clients in the last 3 years.
Modern algorithms as well as AI/ML technologies are revolutionizing the landscape of clinical research by enabling the analysis of vast datasets that include patient demographics, medical histories, laboratory results, safety reports and treatment outcomes. These emerging technologies allow researchers to envision patterns that traditional methods could miss. For instance, predictive modeling and tools provide early quality assessment of studies and sites enabling data managers to identify and resolve issues earlier and less expensively than was historically possible.
The Analytics and Data Review component of EDETEK’s CONFORM IQ features numerous configurable interfaces for data managers, medical monitors, data scientists, biostatisticians, and third parties to collaborate effectively in a unified environment for comprehensive data reviews. One of many analytical features includes proactive subject level safety reviews and early signal detection leading to improved medical and quality assessments from start to finish. CONFORM IQ delivers risk assessment and improved quality throughout the clinical trial conduct.
Artificial Intelligence (AI) and Machine Learning (ML) are radically transforming clinical data management from a traditionally passive to a dynamically interactive process. AI algorithms can monitor clinical and operational data in real-time, efficiently showing inconsistencies that could compromise data integrity or violate regulatory standards. Our CONFORM IQ platform is being enhanced with an AI-supported ecosystem with tools like Chat.IQ, which fosters a more natural, seamless interaction with data. This tool allows scientists and analysts to post complex questions and receive immediate results.
With generative AI, CONFORM IQ will respond to queries with instant data listings and visualizations, allowing data managers to review 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. We are also working on AI-based algorithms to evaluate the audit trail enabling the system to suggest better CDM study designs and effectiveness of rule-based data validation. One of the upcoming AI deliverables in CONFORM is going to be machine automated metadata and business rule configuration of a clinical trial to reduce CDM study design work.
What are the biggest data management challenges encountered by life science organizations?
One of the main challenges in clinical data management is ensuring data quality and integrity. Data discrepancies and errors can have a significant impact on the reliability and validity of the study results. Therefore, implementing robust quality control measures early in trial conduct is essential to address this challenge.
Integrating IoT and other data providers into clinical trials results in complexities, particularly around the volume of data, untraditional data formats, the diversity of data sources and ensuring their seamless synchronization. The CONFORM platform addresses these challenges by offering clients access to over 120 configurations from a validated global library of data adapters. These adapters support a wide range of medical systems and devices including IoTs.
With IoTs the technical challenges include the reliable ingestion and storing of massive amounts of data that are often coming in real time while performing data aggregation applicable to a particular provider and clinical trial. We have resolved these challenges with our scalable data processing and storage technologies, and it makes IoT data actionable rapidly. At the same time, EDETEK’s 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 and patient care benefits in cardiovascular and other therapeutic areas.
Another challenge in clinical data management is data integration and standardization. Clinical trials often involve multiple sites, each using different systems and formats for data collection. This can lead to difficulties in integrating and harmonizing the data from various sources. Standardizing data collection processes and implementing data management systems that support interoperability can help overcome this challenge. Additionally, establishing clear data standards and guidelines can ensure consistency and uniformity in data collection across studies.
Data security and privacy also pose significant challenges in clinical data management. Clinical trial data contains sensitive information about patients, and it is crucial to protect this information from unauthorized access or breaches. We are also working on automatic creation of study metadata based on corporate and therapeutic standards as well as previous history of study configurations assisting data managers in this complex and time-consuming task. Implementing robust security measures, including encryption, access controls, and automatic search and removal of PHI data, can help safeguard patient privacy and ensure compliance with legal and regulatory requirements.
How can software address these challenges?
Ensuring continuous quality of data is crucial to obtaining reliable and valid study results. This can be achieved through robust data validation processes, including checks for missing or inconsistent data, outliers, and adherence to predefined data standards. Additionally, implementing data cleaning and transformation techniques can help address issues such as data duplication, formatting errors, and incomplete records.
Modern data management is a combination of business processes and corresponding software tools. First, the traditional method of running simple edit checks in study-based data capture systems (i.e. EDC) is always there. Second, more complex validation rules apply to aggregated data that come from a multitude of clinical trial data sources. To achieve this data managers run sophisticated software for data transformation so disparate data sources can be brought into a normalized form called a quality review model.
Third, both raw and review enabled clinical datasets as well as operational study data are being analyzed by analytical software and AI to find “deep” issues and predict potential future issues. Fourth, new generation of WEB-based intuitive data review systems allow data managers and other business functions to slice and dice the data, visualize information graphically to find potential data and medical problems manually. Conversational AI is a great tool to make this process even more efficient.
What platform does EDETEK provide to overcome these challenges?
EDETEK’s CONFORM™ platform has emerged as a transformative business and technical solution for increasingly complex clinical trials. It creates an end-to-end digital interoperable ecosystem to rapidly orchestrate the movement, quality evaluation and remediation, and analysis and submission of clinical research data through a seamless and transparent experience for all business stakeholders.
CONFORM™ is a comprehensive, fully integrated end to end platform for the digital trials of the future. The CONFORM helps manage the myriad of clinical data management challenge with the four C’s:
- CONNECT – to an infinite number of external data sources seamlessly
- COLLECT – data faster with automated acquisition and management tasks
- CONFORM – your data to any protocol, industry and corporate standards and regulations
- CONSUME – your data using comprehensive clinical data review analysis and reporting systems
What other services does EDETEK offer to help life science companies bring products to patients faster?
In addition to clinical data management, EDETEK provides comprehensive metadata and business events-driven clinical software solutions to fulfill clinical trial data engineering and business analytics needs. We achieved this through excellence in technology and its biometrics applications, enabled by our deep knowledge in pharmaceutical clinical research and development. In addition to the Informatics Platform, EDETEK offers a complete eClinical Platform that includes EDC, CTMS, ePRO, eCOA, IWRS and other applications. EDETEK also provides business services for customers that use our eClinical and Informatics platforms. EDETEK’s SaaS platforms and solutions are based on industry standards and best practices. EDETEK delivers precisely targeted solutions designed to achieve critical data management and analysis objectives thereby helping assure quality, speed, and cost efficiencies.
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