The SCOPE US conference in early February brought together industry leaders to explore the evolving landscape of clinical research, with technology taking center stage. From AI-driven trial design to advanced data analytics and decentralized trial solutions, innovation is reshaping how studies are conducted, monitored, and optimized. This year’s discussions highlighted the critical role of digital transformation in improving efficiency, patient engagement, and regulatory compliance.
In this debrief, we’ll explore key takeaways from SCOPE, showcasing how emerging technologies are driving the future of clinical trials.
The rise of site consolidation
A notable and recurrent theme from SCOPE surrounded the consolidation of sites into larger site networks. This movement is generally driven by private equity and venture capital investments, which aim to streamline administrative burdens and enhance operational efficiency. By forming site networks, independent research sites join forces under a centralized structure, allowing for streamlined operations, standardized procedures, and enhanced access to resources like advanced technology and dedicated staff.
- Centralized administrative processes: Shared resources improve site performance and reduce administrative burden.
- Enhanced technology and tools for site operations: Many site networks invest in advanced clinical trial management systems (CTMS), electronic health records (EHR) integration, and AI-driven patient matching to optimize trial execution.
- Focused patient care and protocol adherence: Standardized training, centralized oversight, advanced technology integration, and dedicated patient support ensure higher quality trials for patients while increasing compliance.
- Cost efficiency through resource sharing: Consolidation can enhance financial viability by ensuring consistent trial opportunities, reducing overhead costs, and attracting investment from sponsors and CROs.
“Private equity can really provide that level of support to sites, there is an opportunity for sites to have even more improved tools and technology.”
Site network consolidation not only promises operational efficiency but also shifts the focus back to patient care, allowing site staff to dedicate more time to medical and protocol procedures.
AI’s role in patient recruitment
AI’s impact on patient recruitment is undeniable. With a significant percentage of solutions presented at SCOPE focused on patient recruitment support, it’s clear that AI is revolutionizing how clinical trials attract participants.
- Improved targeting of potential participants: AI analyzes EHR, genetic data, and real-world evidence to quickly find eligible patients, and machine learning models ensure precise selection based on trial criteria.
- Enhanced patient engagement: AI-driven chatbots and digital tools provide personalized communication and support.
- Faster recruitment timelines: Streamlined processes accelerate recruitment and study startup.
As AI technologies advance, they provide more sophisticated tools for patient recruitment, ensuring that trials are populated with suitable participants more efficiently than ever before.
Modernizing biospecimen collection
A very well-attended session at SCOPE focused on the critical need for improving sample management, particularly in how informed consent is handled when a participant withdraws from a study. As trials increasingly rely on biobanking, genetic analysis, and AI-driven insights, ensuring proper handling of biospecimens—especially in cases of patient withdrawal—is critical.
This trend underscores the need for modernization in biospecimen management. AI insights are being leveraged to address these challenges, offering a more comprehensive approach to consent management and specimen tracking. Some considerations for improving this process include:
- Clear and granular consent: Modern consent forms should outline specific uses of biospecimens, including future research, secondary analyses, and data sharing, allowing patients to make informed decisions.
- Withdrawal protocols: When a patient withdraws, sponsors must define whether samples are destroyed, de-identified for continued use, or retained for specific purposes based on consent parameters.
- Enhancing transparency and patient trust: Clearly communicating how biospecimens will be used—even post-withdrawal—enhances trust, supporting long-term engagement in clinical research.
Challenges of AI and tech adaptation
While AI offers numerous benefits, its adoption in clinical trials is not without challenges. The integration of AI technologies into existing processes is often hindered by regulatory complexities and data access issues.
- Navigating data privacy regulations: Evolving global regulations on AI, data privacy (e.g., HIPAA, GDPR), and GCP compliance create challenges for widespread adoption.
- Data quality and integration: AI relies on vast datasets, but inconsistencies, incomplete records, and siloed systems can hinder accurate analysis and patient matching.
- Ensuring compliance with AI-generated data: Protecting patient data from breaches and safeguarding secure AI-driven decision-making is critical for maintaining trust.
- Adapting existing processes to leverage AI: Sites, sponsors, and CROs must invest in training and change management to ensure seamless integration and effective use of AI tools. High upfront costs, infrastructure needs, and ongoing maintenance can also make AI adoption challenging for smaller research organizations.
“We aren’t adapting our process and expectations to live in an electronic world as fast as the electronic world is creating capabilities for us.”
Addressing these challenges requires a concerted effort to align technological advancements with regulatory frameworks, ensuring that AI can be seamlessly integrated into the clinical trial landscape.
Looking ahead: A preview of SCOPE 2030
The future of clinical trials is poised for transformation by 2030. The integration of AI into all facets of clinical processes is expected to be a game-changer, driving efficiency and innovation. Some expectations for trends we’ll be discussing at SCOPE 2030 include:
- AI embedded in all clinical processes
- Increased use of synthetic control arms
- Consolidation of tech vendors for streamlined operations
“AI should be layered on top of every process, even if in the smallest way, as a starting place for the human to then begin interacting with it.”
As clinical trials continue to evolve, AI integration and site network consolidation mark significant advancements toward greater efficiency and patient-centric operations. Adapting to these shifts will be essential for companies aiming to stay competitive in a rapidly changing landscape. By 2030, AI will be a driving force behind industry transformation, unveiling new levels of innovation and operational excellence.
To hear more about Premier’s perspectives for embracing AI and other emerging trends, contact us.
ABOUT PREMIER RESEARCH:
Premier Research, a global clinical research, product development, and consulting company, is dedicated to helping innovators transform life-changing ideas and breakthrough science into new medical treatments. We offer strategic solutions across the entire development lifecycle, from pre-clinical through commercialization, specializing in smart study design and full-service clinical trial management.
Leveraging technology and therapeutic expertise, we deliver clean, conclusive data with a focus on reducing development timelines, securing access to the right patients, and effectively navigating global regulations to ensure submission-ready results.
As an organization that puts patients first, we pride ourselves on helping customers answer the unmet needs of patients across a broad range of medical conditions. Visit premier-research.com.
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