In this interview, Jeffrey Sorenson, CEO of Yunu, outlines how his company is enhancing the precision and efficiency of clinical trials through advanced imaging technologies. Sorenson highlights how enhanced imaging and data integrity are crucial to driving faster and more effective medical advancements, paving the way for new patient care and treatment breakthroughs. He also explains that Yunu is addressing significant challenges in clinical trials by integrating real-time monitoring and cloud analytics for imaging data, which streamlines trial management and improves decision-making processes.

Moe: What are the current challenges of imaging in clinical trials, and how is Yunu addressing them?

Jeffrey Sorenson: There is a significant accuracy and efficiency crisis in clinical trials, particularly evident in site to central imaging service discordance and enrollment challenges in early-phase and rare disease drug trials. As the number of trials increases and the enrollment pool shrinks, the importance of each participant grows. Historically, imaging data has been isolated from other data sets, hindering comprehensive analysis essential for effective outcomes. To address this, we’ve ensured that imaging data, annotations, and results are seamlessly integrated and accessible, reducing data fragmentation and enhancing clinical signal visibility.

Moreover, the clinical trial landscape faces pervasive challenges such as inconsistent data integrity across sites and delays in data availability, which can impede timely decision-making and regulatory submissions. By integrating advanced imaging workflow technologies and improving data management, we enhance the reliability of the data submitted for regulatory review and ensure robust, consistent data across all trial sites, supporting a smoother and faster regulatory submission process.

Moe: Can you explain how your technology enhances operational efficiency and maintains data integrity in clinical trials?

Jeffrey Sorenson: Our technology significantly enhances operational efficiency in clinical trials by integrating and automating the workflows associated with radiology reading. By streamlining these processes, our system reduces the time spent on radiology assessments and impacts the broader aspects of trial management. For instance, the automation of image processing and data entry eliminates repetitive tasks, reduces the potential for human error, and speeds up the cycle times for trial phases. This results in substantial time savings—up to 80% of study staff time and 50% of radiology reading time—and cost reductions,

Jeffrey Sorenson CEO Yunu

allowing clinical trial teams to allocate their resources more effectively and focus on critical aspects of patient care and data analysis.

Furthermore, our platform enhances the transparency and management of imaging data across multiple trial sites and among stakeholders, when managed by sponsors and CROs. The real-time updates and centralized data management system ensure that all parties have immediate access to the latest imaging results and trial data. New and configurable dashboards give real-time visibility and facilitate more informed decision-making with quicker adjustments to study protocols. This level of transparency is vital in dynamic trial environments where conditions and requirements can change rapidly. By automating the collection, processing, and distribution of imaging data, we mitigate the risks associated with manual data handling and improve the reliability of the trial outcomes.

Moe: Can you discuss the importance of data integrity and standardization in clinical trials and how your system ensures this?

Jeffrey Sorenson: Ensuring data integrity and standardization in clinical trials is essential, as it bolsters the accuracy and reliability of the results that guide medical advancements and regulatory approvals. Our system is designed to maintain strict control over the entire data workflow, from initial image capture to final analysis. This end-to-end control ensures that every piece of data adheres to the highest quality standards and compliance requirements, regardless of the geographical location of the trial sites. By managing the workflow meticulously, we ensure that the data collected is consistent, accurate, and perfectly aligned with the trial’s scientific and regulatory needs.

Moreover, our platform enhances the traceability of all data modifications, an essential feature for auditability and regulatory review. Each change in the data set is logged and justified, creating a comprehensive audit trail that supports transparency and accountability. This traceability is crucial for identifying and addressing any discrepancies that might arise during the trial, thereby safeguarding the integrity of the data.

Moe: How does your platform promote more inclusive and diverse participation in clinical trials?

Jeffrey Sorenson: Our platform is designed to enhance the inclusion of diverse populations in clinical trials by decentralizing the management of sophisticated imaging data. This enables community sites without access to advanced imaging technologies and capabilities to participate in complex trials, which traditionally were limited to large, well-funded urban medical centers. This approach broadens trials’ geographic and demographic reach, ensuring a more representative sample that reflects diverse genetic backgrounds and environmental conditions influencing health. Integrating detailed imaging data into the clinical trial process, our platform advances precision medicine by making trials more inclusive and enabling treatments tailored to individual patient needs, thus enhancing the development of effective therapies across diverse groups.

Moe: What future advancements in clinical trial imaging can we anticipate from Yunu?

Jeffrey Sorenson: Looking ahead, Yunu is committed to significantly advancing the capabilities of clinical trial imaging by enhancing our cloud analytics and dashboard features. This development is geared towards enabling real-time monitoring of trials, a step that will revolutionize how data is accessed and analyzed during the course of clinical research. By providing sponsors and CROs with real-time visibility into various aspects of the trial, such as patient recruitment, adherence to the protocol, interim results, and more, our platform will facilitate a more dynamic and responsive approach to trial management. Furthermore, integrating advanced cloud analytics into our imaging solutions will enable more profound insights into patient responses at an individual level, enhancing the ability to tailor treatments within trials. This technology will also support predictive analytics, helping researchers anticipate potential issues before they become problematic, such as identifying patients who may not respond well to a treatment based on early imaging data.

Yunu has broadened the scope of our imaging technologies beyond oncology to include virtually all specialties and modalities, extending anywhere that the demands for precise and efficient imaging are pressing. Examples of this would be neurology, cardiology, and inflammatory diseases, where imaging plays a pivotal role in diagnosing conditions, monitoring treatment effects, and ensuring patient safety. Additionally, our efforts to unify the imaging and data management processes are designed to create a more integrated and user-friendly platform for researchers and healthcare professionals. By providing a consistent framework for imaging across various types of clinical trials, we can reduce the learning curve and operational complexities associated with managing clinical data, allowing research teams to focus more on patient care and less on administrative tasks.

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Moe Alsumidaie Chief Editor
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.