Healthcare & Life Sciences

Minimize clinical trial delays to bring life-saving therapies to market faster

Intelligently analyze, classify and extract clinical trial documents to reduce risk of costly stops and starts

Life Sciences companies want to get new, affordable and cutting-edge products to market as quickly as possible. The faster products and therapies are introduced, the faster individuals can benefit — and lives can be saved.

Clinical trials are a critical part of the process for taking new treatment therapies from R&D to market availability. While we saw COVID-19 vaccine development move at an exceptional pace, the industry overall still defaults to traditional, high human touch methodology when it comes to collecting, analyzing and cleansing clinical data and documents, with 50 percent of clinical trials relying on paper-based case report forms (CRFs).

This manual approach lacks analytical power and flexibility, leading to errors related to misplaced, mislabeled and hard-to-find documentation. Therefore, it’s no surprise that 85 percent of trials experience delays, with 94 percent delayed by more than a month.

These delays are further exacerbated with nearly half of pharmaceutical pipelines comprising newer and more complex biologics, adding nearly two years to the development cycle.

This leaves Life Sciences companies asking, how do we:  

  • Reduce inevitable delays to get to market faster?
  • Decrease risk tied to misplaced and mislabeled content?  
  • Better support launch readiness teams with fast access to accurate content?
  • Improve data quality to reduce deviations and failure?

Decreasing delays gets organizations to revenue faster

Bringing efficiency, automation and high-quality clinical trial results to the regulatory filing process expedites approvals, lowering clinical operating costs and resulting in faster time to revenue — with significant upside potential. Introducing a new therapy to market even 24 hours earlier can result in additional revenue of $600,000 to $8M per day.

But that’s not all. A faster product launch, combined with ongoing studies to extend product indication and the life of the product, also increases lifetime revenue — a compelling business case for introducing intelligence and automation to trial processes.

The road to “database lock”

Clinical trials produce massive volumes of documentation with a single clinical trial for 100 patients generating as many as 3.6 million data points, three times the data collected by late-stage trials a decade ago. Add to that, 80 percent of content is unstructured, with data changing from one study to the next, leading to an increase of queries related to misfiled, mislabeled or missing documents. This triggers manual processes, often requiring a person to track down incomplete information and delaying database lock.

The complexity of clinical data documentation creates a negative trickle effect — the quality of metadata goes down due to content complexity, and poor metadata quality, in turn, results in trial data delays.

Have clinical trial data within reach  

Bringing efficiency and automation to records management processes, puts information at individuals’ fingertips, making it easy to search and locate data for regulatory and audit requests and requirements. Knowing where information resides, driven by accurate document and metadata classification, drives compliance and reduces delays as trials move through various phases, driving success for key stakeholders, from launch readiness teams to commercial teams, including product planning.

Improve data quality and inspection readiness

Clinical Data Intelligence for Life Sciences from OpenText™ helps organizations eliminate trial stops and starts to more quickly achieve inspection readiness for filing and validation.

By leveraging automated intelligent technology to capture, enrich and enhance metadata collected from clinical research studies, organizations bring efficiency to the preparation, classification and extraction of clinical data, improving data quality and expediting time to “database lock” with minimal data wrangling and queries.

How it works:

  • Intelligently capture documents and data from any source
  • Automatically analyze and classify documentation   
  • Extract important metadata and required text
  • Enhance metadata— AI and natural language processing decreases deviation exception through self-training
  • Accurately load documents and file into any eTMF system

Quality metadata with accurate classification, categorization and filing of clinical trial documents is within reach.

Discover how Clinical Data Intelligence for Life Sciences from OpenText helps Life Sciences customers bring efficiency to the clinical trial lifecycle, reducing complexity and delays to more quickly introducing life-saving therapies. To learn more about why intelligent classification of clinical trial data is important, download the whitepaper Solving the challenges of data in clinical trial supply chains for rare diseases.

Ferdi Steinmann

Nearly 25 years of experience in driving strategy & commercialization efforts in Biotech & Pharma with an exclusive focus in Life Sciences (LS) strategic planning and industry marketing efforts for enterprise software solutions. Today I am responsible for the LS global industry strategy development at OpenText. I am energized by strategies that deliver on their promises

Related Posts

Back to top button