CTMS platforms centralize and streamline every aspect of a clinical trial – planning, site coordination, patient tracking, budget oversight, document management, and regulatory compliance – into one unified, cloud-based system. The increasing trial complexity, the growing data volume, and the need for real-time collaboration have driven the shift toward cloud-based, integrated CTMS platforms that provide real-time operational insights into trial performance. Modern CTMS platforms integrate with EHRs, EDCs and other clinical systems and leverage AI, automated workflows, and real-time analytics to help teams forecast enrolment issues, manage risks, and speed up trial execution. In this report, we assess 13 CTMS product providers. The report enables buyers to choose the best-fit provider based on their sourcing considerations and empowers providers to benchmark themselves against their peers.

Clinical trials are becoming more complex due to the adoption of decentralized models, increasing data volumes, and greater regulatory scrutiny. Conventional approaches centered on 100% Source Data Verification (SDV) and uniform on-site monitoring are inefficient, costly, and slow at detecting emerging risks. RBQM addresses these limitations through a comprehensive, risk-focused framework. Anchored in principles such as Quality by Design (QbD), centralized monitoring, and continuous risk assessment, RBQM empowers sponsors to identify, prioritize, and mitigate critical risks across all trial phases. The approach enhances trial quality, accelerates timelines, and ensures compliance with global regulatory standards, including FDA, EMA, and ICH E6 (R3). This report outlines the evolution from Risk-based Monitoring (RBM) to RBQM, presents the core principles and key components of RBQM, and offers guidance on how enterprises can derive success from their RBQM initiatives. It is intended for sponsors and Contract Research Organizations (CROs) seeking to modernize trial oversight and improve operational performance through data-driven quality management.

Clinical trials are becoming increasingly digital yet remain decisively manual. Sponsors and CROs have invested heavily in digital platforms, but without orchestration across these systems, operational blind spots persist. Data is collected, monitored, and reported – but rarely acted upon in real time. Trial execution still relies on manual coordination, disconnected processes, and delayed responses. What is missing is not visibility, but adaptability. The question is no longer whether we have enough data or tools, but whether clinical systems can sense what is happening, decide what to do next, and act accordingly. Systems that wait for human input are increasingly misaligned with modern clinical development’s speed, scale, and complexity. What is needed is a shift from fragmented enablement to connected intelligence. This is where Systems of Execution (SoE) come in. By embedding agentic AI across the clinical value chain, SoE enable real-time orchestration of trial activities – detecting risks, triggering actions, and optimizing execution. These systems do not just support clinical operations, they transform them. In this Viewpoint, we share our insights and perspective on the SoE approach to applying agentic AI in clinical trials.

The clinical trial landscape is fundamentally transforming with generative AI adoption. Historically, trials have relied on manual processes for protocol design, database lock, and regulatory documentation, often leading to inefficiencies, rising costs, and prolonged development timelines. Growing clinical data volume and increasingly stringent regulatory requirements pressure pharma companies to optimize costs and accelerate drug development. Generative AI is uniquely positioned to address these challenges by synthesizing fragmented datasets, automating routine tasks, and enabling real-time data analysis and predictive modeling. By streamlining trial workflows, supporting adaptive trial designs, and enhancing decision-making, it is helping sponsors improve operational efficiency while maintaining data integrity and compliance. Integrating generative AI into clinical trials requires redefining core processes, reimagining stakeholder roles, and implementing new workflows that allow AI-driven insights to be seamlessly embedded into trial operations. This Viewpoint explores how sponsors can effectively adopt generative AI, key implementation considerations, and the best practices to ensure successful clinical development integration. Scope Industry: life sciences Geography: global Contents In this report, we examine: How generative AI addresses inefficiencies and drives innovation in trial processes Strategic changes required to integrate generative AI, including redefining roles and optimizing workflows Key considerations and best practices for successful adoption and organizational goal alignment Membership(s) Clinical Development Technology Sourcing and Vendor Management

Clinical Trial Management Systems (CTMS) are vital to modern clinical research, offering essential tools to manage and track all operational aspects of the trial process. Clinical trials’ increasing complexity, the growing data volume, and the need for enhanced collaboration have transformed CTMS platforms from basic on-premise, siloed data management systems to cloud-based, integrated systems. Initially focused on addressing manual, paper-based limitations, early CTMS lacked integration capabilities. Over time, technology advances, regulatory demands, and growing trial complexity led to the emergence of modern CTMS platforms that offer enhanced features such as integration with electronic health records, remote monitoring, and real-time actionable insights. CTMS platform providers continue to invest in AI/ML, automation, and advanced analytics to enable more efficient clinical trials. By providing real-time insights, automating routine processes, and allowing better data management, modern CTMS platforms ensure trial operations are streamlined and more effective, leading to more informed decision-making and faster trial execution. In this report, we assess 13 CTMS providers’ capabilities. The providers are mapped on the Everest Group PEAK Matrix®, a composite index of a range of distinct metrics related to a provider’s capability and market impact. Scope Industry: life sciences Geography: global Contents In this report, we assess: The CTMS product provider landscape CTMS product providers on several capabilities and market success-related dimensions Membership(s) Clinical Development Technology Sourcing and Vendor Management

The clinical development landscape is rapidly evolving, with hybrid trial approaches and the growing use of RWD/RWE. Clinical trial sponsors are increasingly challenged to manage the vast volume of data generated during multiple, simultaneously running trials. This data explosion, combined with heightened regulatory scrutiny from bodies like the US FDA, is pushing sponsors to take greater ownership in trial oversight, risk management, and patient safety. The challenge is exacerbated when clinical trials are outsourced, as sponsors lose real-time access to trial data, delaying critical decision-making and risk management. The solution lies in an end-to-end unified clinical Data and Analytics (D&A) platform, which provides a single source of truth by consolidating trial data across multiple solutions, ensuring quality and standardization and delivering real-time trial performance analytics. This report addresses the key challenges sponsors face in managing clinical data, the benefits of deploying an end-to-end unified clinical D&A platform, and implementation considerations. It is tailored to assist biopharma and MedTech enterprises, as well as contract research organizations, in streamlining their clinical data management, enhancing trial oversight, and improving decision-making. Scope Industry: life sciences Geography: global Contents In this report, we outline: The business challenges that sponsors face in managing clinical data An end-to-end unified clinical D&A platform’s benefits Key implementation considerations for clinical D&A platforms Membership(s) Clinical Development Technology Life Sciences Information Technology Sourcing and Vendor Management

In the dynamic life sciences clinical development field, patient engagement has emerged a vital innovation and success driver. As clinical research evolves, integrating patient perspectives and active participation has become a transformative force, significantly enhancing clinical trials’ quality and relevance. Effective patient engagement throughout the clinical trial process, from study design and recruitment to data collection and result dissemination, ensures that trials are more patient-centric, efficient, and likely to yield meaningful insights. Patient engagement in clinical development is not merely a regulatory requirement but a strategic imperative. Patients who are engaged are more likely to participate in clinical trials and remain committed throughout the study, thereby reducing dropout rates and accelerating the research timeline. In this report, we assess start-ups that provide clinical trial patient engagement solutions, offering insights into capabilities, market impact, and the evolving landscape. Furthermore, from creating patient advisory boards to using patient-reported outcomes, we will explore practical strategies to incorporate patient engagement into clinical development. We will also examine case studies and best practices that illustrate patient-centric approaches’ tangible benefits. Scope Industry: life sciences Geography: global Contents In this report, we Examine the drivers and barriers to patient engagement solution adoption in clinical trials Introduce a framework to evaluate high-potential start-ups in the patient engagement market Highlight the trailblazers in patient engagement, including their assessment, leaderboard, and profiles Membership(s) Clinical Development Technology Sourcing and Vendor Management

Patient recruitment is a complex and dynamic part of clinical trial management, requiring proactive strategies, collaborations, and innovation to overcome challenges and achieve enrollment targets. Patient recruitment is vital for clinical trials, yet it presents challenges that impact study timelines, costs, and overall success. By adopting patient-centric approaches, using technology, and fostering collaborations across stakeholders, organizations can enhance recruitment efficiencies and accelerate study timelines, ultimately introducing new treatments to market faster for patients’ benefit worldwide. Patient recruitment in clinical trials will evolve due to technology advances, changing regulatory landscapes, and dynamic patient expectations. Outsourcing patient recruitment to specialized firms offers enterprises and Contract Research Organizations (CROs) opportunities to use expertise, scalability, and flexibility in navigating enrollment complexities. In this report, we examine the patient recruitment landscape, including the challenges that sponsors face. The report also assesses the current state of the supplier ecosystem and explores technology’s role in solving major challenges in patient recruitment. Scope Industry: life sciences Geography: global Services: life sciences BPS, life sciences ITS, and clinical development technology Contents In this report, we: Examine the patient recruitment landscape, including the challenges that sponsors face The report also assesses the current state of the supplier ecosystem and explores technology’s role in solving major challenges in patient recruitment Membership(s) Life Sciences Business Process Sourcing and Vendor Management

Decentralized Clinical Trials (DCTs) are transforming the landscape of clinical research by leveraging digital technologies to facilitate remote patient participation. This patient-centric approach not only benefits participants but also ensures more inclusive and robust study results while reducing the workload for investigators. In the aftermath of the pandemic, a hybrid model is emerging that seamlessly integrates technology with traditional site workflows, ushering in a new era of clinical trials that harnesses the strengths of both approaches. In a financially constrained environment, DCT platform providers are looking to strike a balance between client satisfaction and cost reduction. They prioritize delivering comprehensive solutions that include real-world evidence, integration with sensors and wearables, and tools dedicated to enhancing patient engagement and retention throughout the trial process. This compendium provides detailed and fact-based snapshots of 22 DCT providers. Each profile offers a comprehensive picture of the provider’s offerings, technology solutions, key clients, recent developments, and investments. Scope Industry: Life sciences Geography: global Contents This report features 22 DCT platform provider profiles and includes: Company overview: the company’s mission, client base, and revenue split across buyer segment and geographies Case studies demonstrating DCT capabilities Solutions/Products enabling DCT capabilities Recent product developments, partnerships, and investment areas Membership(s) Clinical Development Technology Outsourcing Excellence

Decentralized Clinical Trials (DCTs) are transforming the landscape of clinical research by harnessing digital technologies to facilitate remote patient participation. This patient-centric approach not only benefits participants but also ensures more inclusive and robust study results while reducing the workload for investigators. In the post-pandemic climate, a hybrid model is emerging that seamlessly integrates technology advances with traditional site workflows, creating a new era of clinical trials that harnesses the strengths of both. In a funding-constrained environment, DCT platform providers are looking to strike a balance between client satisfaction and cost reduction. They are focusing on delivering comprehensive solutions that include real-world evidence, integration with sensors and wearables, and tools dedicated to enhancing patient engagement and retention throughout the trial process. In this report, we assess the capabilities of 22 platform providers specific to the decentralized clinical trial landscape. These platform providers are mapped on the Everest Group PEAK Matrix® , a composite index of a range of distinct metrics related to a provider’s capability and market impact. Scope Industry: Life sciences clinical development technology Geography: global Contents In this report, we: Examine the provider landscape for DCTs Assess DCT platform providers on several capabilities and market success-related dimensions Membership(s) Clinical Development Technology Sourcing and Vendor Management