Since the first few citations of registered and structured clinical data in the 1940s, the methods of capturing clinical data, use and application of clinical data, global inclusions, and role of payers, users and regulators have evolved.

At present, the Clinical Data universe comprises the siloed internal and external data sources within clinical development processes. There’s a need to integrate all such data with source agnosticism, which is a conceivable evolution for actionable insights into the performance of a clinical trial portfolio. Currently, every organization in the industry is looking for this ability.

This resultant data universe is primarily necessary to support catch and mitigate errors in real-time to save time and get to market early as strategic decisions are made in the interest of business to manage cost & revenue pressures, to enable focus on core R&D and management, and to ensure continuous compliance with dynamically evolving regulatory guidance.

Staying focused on the core R&D business and continually improving operational & clinical performance have always been the topmost priorities among the business stakeholders; but, a collective and timely insight across the horizontally spread data and information hasn’t always been possible. In such cases, the business decisions have often been delayed, or had to rely on outdated information or lacked any cross-functional impact. 

Other reasons for this evolution could also be that for a long time, the conduct of clinical trials and healthcare initiatives have been carried out by separate functional silos within an organization using separate “legacy” applications & cookie-cutter solutions. Such approaches are typically focused on a specific process or function. This has resulted in multiple, disparate, and inefficient solutions that may not work well together. This has deprived organizations of the ability to make timely decisions, as well as increase efficiencies and overall productivity at the corporate portfolio level while controlling costs & mitigating risks involved at a specific study or at a functional level or portfolio level.

However, the adoption of digital means such as electronic patient reported outcome (ePRO) and electronic data capture (EDC) systems in lieu of paper-based case report form (PCRF) has changed the landscape of clinical data. It has reduced the time taken to collect data and to relay it into the next stage of the process from five days to fifteen minutes. Also, it has managed to expedite the process of developing drugs.

Another milestone is the evolution of data structures. Big Data has allowed the management of large volumes of data and its conversion into comprehensible and insightful visualizations. To realize such benefits, clinical data management processes are compelled to use standardized fields, formats, and forms. This requires the application of a metadata-driven process.

The uprise of Clinical Trial Globalization has eliminated gaps between global study expectations and national standard protocols that lead to many operational complexities. Regulatory bodies like FDA and EMA have come together to synchronize requirements on a protocol-by-protocol basis.

To control financial risks in managing patient populations and to provide continuous access to electronic data, private networks have started building centralized data repositories. This can be further used for a range of analytics, including predictive modeling, quality benchmarking, and risk stratification.

These breakthroughs have eased out many challenges in implementing clinical trials but have also made it the responsibility of CROs and Clinical data managers to upgrade and standardize their systems in response to these progressive developments.

About MaxisIT:

At MaxisIT, we believe that complex data analysis can produce simple yet powerful insights.

MaxisIT’s Clinical Trial Oversight System (CTOS) is a purpose-built command center designed to manage biopharma and life sciences clinical trials as mission-critical business processes. With its complete AI-enabled analytics platform, the CTOS enables “data-driven digital transformation” from data ingestion, processing, and analysis to in-time clinical intelligence. Its real-time data ingestion, analytics, and visualization empower researchers to identify and address errors as they occur.

The CTOS elevates the value of data, improves efficiency, and empowers clinical stakeholders to seize new opportunities. The platform brings clinical operations and patient data together in a single, central data hub as a single-source-of-truth to help clinical operations, clinical data management, biostatistics, and clinical R&D portfolio management.

A complete self-service, AI-enabled analytics platform, the CTOS unifies trial data from disparate eClinical systems to support study planning, clinical data quality, clinical review, patient safety, clinical operations, CRO performance, risk-assessment, portfolio management, compliance, and submission.

From study setup to data ingestion, clinical trial stakeholders can manage clinical development processes with insight into the study conduct and take proactive actions to reduce costs, mitigate risks, and ensure compliance.

MaxisIT’s CTOS helps you maintain an ongoing health-check on your portfolio of clinical trials, using real-time data, analytics, and visualization to drive rigorous analysis of the entire dataset, allowing for proactive trial risk management.