The clinical research industry has come a long way. Traditionally, a clinical research organization (CRO) relied on internal networks and investigator database to support a clinical study for drug/medical device development and clinical trials.

As the clinical space continues to grow at a rapid pace, there is a surge in demand for clinical trial sites. CROs are struggling for new sites to perform their clinical study. The number of trials, in the US, has quintupled (from 48,295 to 288,728) over the last decade, and almost half the sites fail to achieve their objectives, causing expensive trial delays and increased cycle times. How can you keep up with this exponential growth in demand?

Clinical research holds the key here, as it allows the pharmaceutical organizations to validate the safety and efficacy of drug/medical device for regulatory approval, and prepares them for an effective drug launch. The global clinical research market is expected to cross $65 billion USD by 2025.

North America has more than 50% of the clinical research market share, followed by the EU and the APAC region. Selection of an appropriate site becomes extremely important for a successful clinical trial, for drug/medical device development, and is essential for an organization to identify sites with the desired set of patients who meets specific medical conditions to have an effective clinical trial.

Companies are looking for alternative site discovery strategies to cope with the demand in trial sites globally. A data-driven approach across the clinical trial process offers an opportunity to harness the information for an improved clinical trial, patient recruitment, site selection, monitoring insights, and better decision making. Applying analytics with the right set and volume of data received from claims, prescription, electronic health records (EHRs), drug and medical device sales/distribution channels will enable a patient-centric approach for an effective clinical trial.

However, the volume of data is humongous, and these data assets are not centralized/standardized and are distributed across channels in multiple formats. Big data technologies (Hadoop, Spark, Pex, Teiid, etc.) will enable organizations to consolidate and standardize these assets into a single unified platform to allow smooth processing of data and provide valuable insights from the collected data.

Here's how the industry will benefit by adopting a data-centric approach:

Effective patient recruitment: Through data analytics on EHRs, pre-screening of patient is performed for a given population. This reduces the overall time for a clinical trial
Better decision making: Pharmaceutical companies prioritize accurate data. Analyzing that data can help companies drive better data-driven decisions and clinical trial outcomes
Data monitoring: Make data-driven decisions around site monitoring and enable faster decision in site selection
Anticipating a data-centric future

The paradigm shift that we see in the way clinical research is evolving is expected to evolve further. Analytics along with machine learning (ML) and artificial intelligence (AI) will drive the future of clinical research. However, what has been tapped so far is just the tip of the iceberg considering the volume of data available for clinical analytics and emerging technologies to play a major role to drive efficiency in clinical research and accelerate clinical trials.

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