Call for change

Clinical trials for new medicines are increasingly generating a broader set of complex scientific and patient data from a range of new sources. Pharmaceutical companies can spend billions of dollars on drug development, and timely approval of new treatments is dependent on high quality data for regulatory review.

A global biopharmaceutical company knew that clinical data management was a critical area for improvement to usher an expanding pipeline of drugs through target trial milestones and regulatory approval. The growing pipeline is expected to increase workload threefold, putting unsustainable strain on the company’s legacy technology tools, which were constructed as a complex web of multiple systems.

Proof of concept that challenged efficiency. The positive results of improving clinical data management in an expanding pipeline of drugs.

We embarked on a program together to transform the company’s clinical data landscape.

In addition, the company’s processes required employees to manually gather and connect data collected from different systems of record. This created huge transactional workloads for a straining system and sapped employee bandwidth that could be focused on more strategic clinical trial activities.

To support the anticipated scale in its clinical trial volume, the company sought a simpler, faster way to aggregate, transform and access critical data for analysis and insight. We embarked on a program together to transform the company’s clinical data landscape by better connecting data collection systems and providing a user-centric experience for clinical data management.



When tech meets human ingenuity

To process crucial clinical trial data more efficiently, we developed a solution using the Accenture INTIENT Clinical product suite. The solution brings a cloud-native, insight-driven approach that enables companies to manage internal and external clinical trial data. It also automates the output of clinical trial databases and simplifies the processes to transform data into the formats required for regulatory submission. The scalable solution centralizes data ingestion, aggregation, cleaning and transformation to help teams analyze clinical, patient and scientific data. For instance, all contract research organizations and other third parties can upload data directly into the centralized system so everything is available in one place.

The study data tabulation model (SDTM) engine, powered by INTIENT Clinical, converted raw clinical trial data into a standardized format that regulatory authorities like the US Food and Drug Administration (FDA) can review consistently.

Consolidation of data

INTIENT Clinical consolidated internal and external clinical trial data sources into a single data management and warehousing platform.

FDA-required format

INTIENT Clinical automated the output of clinical trial databases and puts them into the US FDA-required format.

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A proof of concept (POC) showcased the time and labor saved through streamlined and automated processes when compared to current industry standard tools and processes, as well as the company’s previous metrics. The study data tabulation model (SDTM) engine, powered by INTIENT Clinical, converted raw clinical trial data into a standardized format that regulatory authorities like the US Food and Drug Administration (FDA) can review consistently.

The SDTM conversion pooled the company’s data from its clinical data collection tool, as well as sources from three external vendors. Up to 90% of the related SDTM processes were automated by implementing consistent data collection standards during the database design. The conversion process was completed in four weeks.

50%

Automated processes and a 50% decrease in trial data conversion efforts mean patients get access to life-saving medicines sooner than previously possible to help improve patient outcomes.

90%

The proof of concept successfully performed SDTM conversion, showing that up to 90% of the SDTM processes could be automated and the conversion process effort halved.

100%

The proof of concept showed excellent results. In both cases, it detected data anomalies early to make all SDTM conversions correct and compliant first-time, a 100% increase.

A valuable difference

The robust, integrated clinical data transformation solution is helping to manage higher trial data volumes without increased costs while speeding life-saving drugs through development. Employees are also freed up to concentrate on strategic projects like exploratory analytics, helping to improve productivity in focus areas to reach critical milestones faster.

INTIENT Clinical will also help automate other clinical processes, not just SDTM conversion. The cloud solution simplifies scaling to adapt to changing regulatory requirements.

The SDTM POC showed excellent results. When compared to current industry standard tools and processes, it reduced manual efforts to produce FDA-compliant data structure and content by approximately 22%. Quality control review activities fell by 50%. In both cases, it detected data anomalies early to make all SDTM conversions correct and compliant first-time, a 100% increase.

Overall, it reduced the time required to convert raw clinical trial data to FDA-required standards by 75% when compared to current industry standard tools and processes. The time is expected to drop even more as users become better acquainted with the solution’s tools and the new ways of working that it has enabled. All time saved means that patients can get access to life-saving medicine sooner than previously possible, helping to improve patient outcomes.

The SDTM conversion pooled the company’s data from its clinical data collection tool, as well as sources from three external vendors.

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