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The increasing complexities in clinical trials, including expanded patient populations, decentralized trials and new technologies, are directly impacting the amount of data and information available to clinical trial sponsors. Though this provides significant value to the industry, it presents a new challenge of consolidating disparate and siloed systems, improving standardization and unifying the explosion of data across clinical trials.

Organizations are now faced with the need to centralize data and are increasingly adopting advanced data and analytics capabilities to bring efficiency to data centralization and democratization processes. 

Regulatory challenges, incongruous data and increasing stakeholders

As accountability shifts with regulatory guidelines, sponsors increasingly carry the burden of clinical trial oversight, taking responsibility for any unforeseen problems, regardless of who conducted what task. Even if certain operations are conducted by outsourced contract research organizations and third-party vendors, the sponsor remains liable. Additionally, the myriad of new global data privacy and security regulations increases the complexity of managing multiple sources of clinical research data. These responsibilities exacerbate sponsors’ pre-existing challenge of unifying data across disparate and disconnected systems. 

Another obvious obstacle across the ever-expanding clinical trial landscape is the increasing number of stakeholders working to analyze data across information repositories, communication channels and locations. This presents the inevitable struggle of integration, aggregation and standardization of information. 

Incongruous data, for example variations in frequency and format, creates the arduous task of unifying misaligned information and results in a resource intensive, time-consuming process. It is a critical process that cannot be overlooked, as a lack of synchronized data can affect data quality and lead to errors and inconsistencies. The culmination of these types of challenges with data unification is unacceptable and creates delays in critical decision making. 

In the context of clinical trials, these challenges lead to deteriorated coordination between stakeholders, regulatory and compliance risks, and challenges in interpreting and communicating results. Using modern data technologies to consolidate data for analysis and review solves not only the disparate data challenge, but also enables cross-functional review of the same data source by multiple stakeholders.

Solution to managing disparate data

A centralized, comprehensive cloud-based solution that consolidates and harmonizes data can drastically reduce time spent manually aggregating and standardizing information and calculating metrics across the clinical trial portfolio. 

Implementing a software solution that can act as a central repository of information increases efficiency while providing analytic capabilities to analyze, monitor and measure data across a clinical trial portfolio.

Managing multiples sources of information across various locations requires a system capable of handling overhead, workflow and transactional complexity. The ability to consolidate data across a wide range of sources accelerates timelines and establishes interoperability among disjointed systems. Not only does a central repository of information improve data quality and consistency, but it also reduces costs by eliminating redundancy.

The advantages of cloud-based data lake technologies include real-time and proactive data management, improved data harmonization, which accommodates sponsor specific systems for data exchange, and integration of clinical, operational and real-world analytics. Sponsors specifically benefit from a faster deployment of standard key performance indicators (KPIs) and key risk indicators (KRIs).

Additionally, the current implementations of artificial intelligence and machine learning algorithms are showing great promise in automating data acquisition and harmonization, facilitating data analysis and increasing data quality.

Standardized solutions improve enterprise performance

Transforming data from third-party sources to a harmonized data model allows your enterprise access to accurate data streams, improving communication and syndication across departments that previously struggled with collaborative data insights. Once data is aligned and prepared for analysis, organizations can better assess and improve clinical trial operations on demand. 

The flexibility of these solutions also allows organizations to customize platforms to meet their specific needs. Instead of focusing on reactive approaches to clinical trial management, organizations can now take proactive measures based on data and analytics. This not only fosters improved outcomes but helps professionals to step away from administrative oversight and focus on more critical aspects of clinical trial management.

Especially with the increase in decentralized trials, data has become more scattered than ever before, leading organizations to spend more resources, funds and time on tedious consolidation and standardization processes. Cloud-based solutions that unify data in clinical trials allow organizations to better manage data to ensure quality and regulatory compliance, streamline information analysis and improve communication between stakeholders. 

Wendy Morahan, Senior Director, Clinical Data Analytics Suite (CDAS) at IQVIA. Wendy has more than 25 years’ experience in the life sciences industry, with a career spanning academic research, preclinical drug discovery, and clinical trials culminating in a focus and passion for delivering technology solutions that help bring treatments to patients faster. She is currently part of the product strategy leadership team for IQVIA Clinical Data Analytics Suite (CDAS), providing both SaaS solutions for the market as well as IQVIA’s internal CRO needs. As part of the CDAS team, Wendy is responsible for strategy, product management leadership, and go-to market activities.