Clinical trial complexity is outpacing traditional data management— here’s how to catch up

Clinical trials are at a breaking point. Over the past decade, the volume and complexity of clinical data have surged dramatically. The average number of data points collected per study has tripled, endpoints have nearly doubled¹ and design elements in Phase II and III protocols have become significantly more intricate. While these advances reflect scientific progress, this results in rising costs, longer timelines and increasing operational strain across drug development programs. These advances also introduce a new reality: that clinical data management (CDM) practices need to evolve and keep pace.

Organizations that lack internal CDM resources, or specialized expertise to effectively support their trials, or are looking to expand CDM efficiency, may benefit significantly from functional service provider (FSP) partnerships. FSP partnerships enable sponsors to address operational gaps, and gain access to advanced data science capabilities, experienced personnel, and scalable infrastructure without the burden of building and maintaining a full in-house team.

Contract research organizations (CROs), such as the PPD™ clinical research business of Thermo Fisher Scientific, offer tailored FSP arrangements, allowing sponsors to tap into cutting-edge CDM technologies and expertise, gain deeper insights, improve data quality and achieve more efficient trial execution.

Risk-based data management is surpassing traditional CDM models

Legacy CDM models were built for an era defined by structured datasets, limited sources and largely manual processes. Modern trials integrate data from an increasingly diverse ecosystem of sources including electronic health records (EHRs), wearable devices, imaging systems, eCOA platforms, cardiac safety technologies and digital biomarkers. As decentralized and hybrid trial models continue to expand, the volume, velocity and variability of endpoint data are increasing dramatically. Yet many CDM workflows are limited in operational efficiency, as they still rely on manual review, point-by-point query resolution and siloed datasets.

Further, siloed approaches prevent teams from seeing the bigger picture. This prohibits opportunities to improve data collection, ensure data quality and integrity and gain valuable clinical and operational insights.

As sponsors and CROs become more aware of limitations with traditional approaches, they are shifting from managing data to leveraging it as a strategic asset. Clinical data management is evolving into a broader data science function, where the focus extends beyond data handling to generating actionable insights. Powered by artificial intelligence (AI), new bleeding edge tools in development can help reduce cycle times by automating repetitive tasks and assisting in data cleaning and query generation. This transformation allows teams to focus on higher-value activities like trend analysis and decision support.

New roles are emerging as well. PPD™ Functional Service Partnership (FSP) Clinical Data Management solutions experts note that data strategists who guide data-driven decisions across the trial lifecycle are becoming more central to study success. These experts bridge clinical, operational and statistical teams, ensuring that data is accurate and meaningful.

One of the key contributors enabling this shift is risk-based data management (RBDM). Rather than applying the same level of scrutiny to every data point, RBDM prioritizes resources based on what matters most: patient safety and study outcomes. Data are categorized by risk level, and review efforts are scaled accordingly. This targeted approach improves efficiency, enhances data quality and aligns with evolving regulatory expectations. It also introduces more adaptive oversight. By using key risk indicators (KRIs) and performance metrics, teams dynamically adjust their focus as trials progress, ensuring that attention is always directed where it’s needed most.

Traditional CDM models were about managing isolated datasets. Modern CDM is about orchestrating a connected, intelligent data ecosystem. A key component of this evolution is centralized monitoring, where teams analyze data across sites, regions and patient populations to identify trends and anomalies. This approach enables a big picture view, offering earlier issue detection (including data inconsistencies to potential compliance risks), and supports more proactive decision-making. Equally important is the integration of data across functions. When clinical, operational and statistical data are unified in a single environment, teams collaborate more effectively and act with greater speed and confidence.

A solution that delivers a valuable, holistic CDM approach

For many organizations, transitioning from traditional to modern CDM practices requires capabilities that may not exist in-house, whether it’s advanced technology, specialized expertise or scalable resources. Through flexible FSP partnership models, sponsors fill specific gaps or fully outsource data science capabilities without the need to build and maintain large internal teams.

PPD FSP Clinical Data Management solutions play a critical role in combining experienced data science professionals with advanced digital infrastructure. PPD FSP Clinical Data Management solutions help sponsors transition from siloed CDM to holistic, data science-driven models, implement risk-based data management strategies, leverage AI and automation to streamline workflows and access cross-functional expertise spanning CDM, biostatistics and medical review.

Clinical trial data continues to grow, and the corresponding complexity likely will continue to accelerate as new data sources, technologies and therapeutic approaches emerge. Organizations that cling to outdated CDM models risk falling behind, facing longer timelines, higher costs and missed opportunities. Those that embrace a data science-driven approach, supported by the right expertise and technology, are better positioned to move faster, make smarter decisions and ultimately bring therapies to patients sooner.

FSP partnerships are prime for helping sponsors adapt their data management approaches to handle this wealth of data while maintaining time and resource efficiency. With more than 30 years of experience, PPD FSP Clinical Data Management solutions are a leader in driving data science innovation, creating digitized solutions that meet changing needs and unlock new efficiencies and deeper clinical insights for sponsors.

We enable clients of every size to fill specific resource gaps or outsource data science entirely, avoiding redundancy while supporting studies with top-tier staff and systems. Our CDM solutions empower study teams to make faster and smarter decisions and meet their timelines. We continue to evolve to best serve partners, implementing AI and machine learning tools to streamline processes, gaining predictive insights that lead to better trials and make the most of human expertise.

1. Moe Alsumidaie, Tufts CSDD: New Insights on The Clinical Trial Industry (2024), Clinical Trial Vanguard https://www.clinicaltrialvanguard.com/conference-coverage/tufts-csdd-new-insights-on-the-clinical-trial-industry/ ↩︎