Clinical trials are the backbone of evidence-based medicine—they rigorously test the safety and effectiveness of new treatments, protect patients by identifying potential risks early, and guide healthcare decisions that affect millions of lives. Behind every statistic is a person hoping for relief, a family searching for answers, or a community striving for better health. Clinical trials don’t just push science forward—they offer hope, healing, and the possibility of a better future. With 498,000 clinical trials currently underway worldwide, the amount of research activity and potential for positive human impact is unprecedented.
However, as clinical trials grow more complex and decentralized, they generate an unprecedented volume of data from various sources: electronic health records (EHRs), lab reports, imaging systems, and wearable devices. For example, genomic data, which is used to better understand patient subpopulations, predict drug response, and identify genetic biomarkers, also introduces significant complexity due to its privacy considerations and large size— which can be terabytes per patient in some cases. This data explosion spans structured and unstructured formats, collecting across multiple platforms and geographies, often in real-time. The result is a fragmented data ecosystem that challenges not only data harmonization and integration but also the ability to extract meaningful insights, detect trends, and maintain regulatory-grade traceability in an efficient and timely manner.
In order to keep up with the ever-increasing array of data points, healthcare organizations are adopting hybrid cloud data platforms so they can not only track important data but also collaborate with team members in different clinical trial locations. By merging on-premises systems with cloud infrastructure, hybrid cloud solutions provide the flexibility, scalability, and security necessary for more efficient management of clinical trial data, ultimately speeding up innovation and treatment advancement.
Breaking Down Data Silos Strategically for Better Compliance
One of the most pressing challenges in clinical research is data fragmentation. Clinical trials draw from a wide range of sources, each often operating in its own silo. For example, many clinical trials struggle to move past the recruitment and enrollment stage, with over 80% of in-person studies delayed due to insufficient patient recruitment, and 80% of research sites failing to meet enrollment goals.
This lack of integration not only limits visibility across the trial but also introduces inconsistencies that can hinder compliance efforts. Regulatory bodies like the FDA and EMA require complete, traceable data. When information is scattered across systems, tracking data lineage and ensuring data integrity becomes a lengthy manual task that increases the risk of non-compliance.
Hybrid cloud platforms address this issue by consolidating structured and unstructured data into a unified environment with built-in governance and compliance tools. Features like automated data management, audit trails, and access controls—centralized under a shared data platform—make it easier to uphold high data quality standards while ensuring compliance with regulatory requirements. Additionally, hybrid architectures support global trials by allowing organizations to localize sensitive data where needed and satisfy data sovereignty laws while leveraging scalable cloud analytics. By breaking down silos, healthcare organizations can transform compliance from a reactive burden into a proactive, streamlined process that accelerates trial execution and patient outcomes.
Enabling Collaboration at a Global Scale
Today’s clinical trials are rarely confined to a single location. They often span contract research organizations (CROs), academic institutions, hospitals, and even continents. This global footprint requires secure, scalable data-sharing capabilities. For example, in 2024, Gilead’s PURPOSE 1 trial, a landmark Phase III study of lenacapavir for HIV prevention, was conducted across multiple countries, illustrating the need for robust infrastructure to support international collaboration and data exchange on a real-time basis.
Hybrid cloud platforms enable seamless collaboration across geographies by supporting decentralized trial models and providing access to real-time data. They also ensure compliance with local data residency and privacy laws by allowing sensitive data to be stored on-premises or within specific jurisdictions while connecting to broader cloud resources.
Speeding Up Decision-Making with Real-Time Processing
In clinical trials, efficiency and speed matter. Behind every data point is a person—someone battling a life-threatening illness, a child with a rare disease, or a family holding out hope for a breakthrough. Patients and families are relying on innovative research to save loved ones, front-line researchers are looking for developments to help treat those patients on the ground floor. Delayed insights can stall recruitment, increase costs, and slow the development of life-saving therapies. Hybrid cloud platforms address this by enabling both real-time and batch data ingestion and analysis.
For example, clinical research coordinators can perform real-time patient eligibility screening, helping to accelerate enrollment. They can also detect and report adverse events and data integrity issues as they occur, enabling timely interventions and protocol adjustments that improve patient safety and trial efficiency. Streamlining the process of turning data into action helps shorten development timelines and enhances decision-making at every trial stage.
Predicting and Preventing Patient Dropout
Patient dropout is a major challenge in clinical research, with a 30% dropout rate according to Forte Research, often resulting in delays or inconclusive results. In some cases, especially in pharmaceutical trials, studies must overenroll to account for potential dropout, resulting in added time and expenditure. With a hybrid cloud setup, research teams can leverage advanced analytics and AI technologies to predict dropout risk before it becomes problematic.
By analyzing both historical and synthetic data, these platforms can identify patterns and risk factors associated with disengagement. With this information and context, trial sponsors can adapt protocols, offer additional patient support, and conduct more patient-centric trials.
Building a Future-Ready Research Ecosystem
The increasing complexity of clinical trials demands a new approach to data infrastructure. Hybrid cloud platforms provide a strategic foundation to meet this, delivering the speed and compliance capabilities required for next-generation research. By investing in hybrid cloud now, healthcare and life sciences organizations can get ahead of the curve and streamline their clinical trials and position themselves to lead the future of medical innovation.
Rameez Chatni
As Global Director AI Solutions—Pharmaceutical and Life Sciences at Cloudera, Rameez Chatni has more than a decade of experience and a robust skill set across biomedical, data, and platform engineering, machine learning, and more. Most recently, Rameez served as the Associate Director of Data Engineering at AbbVie, a biopharmaceutical company. He is passionate about creating end-to-end, innovative and robust technical solutions for pressing business and customer-centric problems. Rameez holds a bachelor’s degree and a master’s degree in Electrical Engineering and a PhD in Bioengineering, both from Purdue University.
