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Clinical development activities generate lots of data – data that might be rich with promising information, but in reality, it’s difficult to access and analyze. This is especially true for emerging biopharmaceutical companies in the clinical development phase. These early-stage companies don’t have the data management resources or infrastructure that larger, well established companies take for granted. That said, clinical data may be even more important for first-time launchers who need to capitalize on every advantage to prove their science and deliver a new therapy to patients.

Deriving value from CRO data requires the ability to readily perform exploratory analysis. Exploratory analysis informs clinical trial designs and regulatory filings, informs commercial strategy and messaging, and creates negotiating advantages for fundraising, partnering opportunities and even suitors. Unfortunately, clinical data is challenging because it’s not normalized by default – it isn’t always in a standardized format, it’s received through different mediums or channels, and the raw data itself is unclean and unprofiled. So how can an emerging biopharma company with limited resources gain practical, useful control of its clinical data assets?

A centralized, accessible clinical data infrastructure enables organizations to:

  • Standardize data formats across trials
  • Improve information traceability
  • Drive leverage of work from one study to the next
  • Have control, ready access and mastery of its clinical data

Learn how a centralized clinical data repository we established benefited this biotech company!


Below, we have outlined some of the typical outcomes we see from use of a centralized clinical data infrastructure versus data that is otherwise disparate. We want to know about your experiences dealing with clinical data. What worked, what didn’t, and why?

Centralized Clinical Data

Disparate Clinical Data

Less risk

Lack of traceability of information (adverse events)

Greater efficiency, consistent communications and reporting, common assessment methods

Difficult cross-study analysis, unexplained conclusions due to numerous handlings of data

Improved response to regulatory obligations

Slow resolution of regulatory queries

Increased value of Intellectual Property

Gaps and unfamiliarity with sponsor requirements

Reduction in costs

Dispersed clinical data across numerous costly programs

Shorter learning curves between CRO and Sponsor, one set of SOPs

Delays due to lack of familiarity of processes between CRO and Sponsor

Centralized reports available in real-time

Inability to make timely crucial decisions due to lack of comprehensive information

Contact us to learn more.

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Authored by: Ben Stickney

Ben is the Director of IT Services for SVA Consulting, LLC. Ben understands data, integration and the interconnectivity of business functions. Phone: 608-826-2002 Email: stickneyb@svaconsulting.com