Operational Data for Managing Clinical Trials

The operational data to manage clinical trials is receiving renewed attention. Changes in how the trials are conducted have not kept pace with how this data is collected and managed. Pharmaceutical/biotechs rely on outside sources Contract Management Organizations (CROs) to run their clinical trials but are still relying on the technologies that supported old business models.  

Pharmaceutical/biotechs are responsible to monitor trials activities even if the activities are outsourced (ICH E6 R2: “The sponsor should ensure oversight of any trial-related duties and functions carried out on its behalf.”). Furthermore, CROs outsource activities to other companies and sponsors do functional outsourcing of some activities, further compounding the data collection challenges. That is why it is so important to have a data store that consolidates all the operational information to ensure the work is being performed correctly.

Operation Data: What is it?

Clinical trial operational data helps answer key questions for how the clinical trial is proceeding:

  • Are we hitting the original milestones?
  • How many subjects have been enrolled at each site?
  • How many sites have been set up?
  • Is all the regulatory paperwork been put in place to start a trial in a country?
  • Has the site signed off all its consents (e.g. IRB)
  • Have there been a lot of Issues from site visits?
  • Why are there many protocol deviations at a site?

The answers to these questions help assess key dimensions of speed, quality, and safety of the clinical study. The challenge is how to collect all this data and visualize it for study leads and senior management to make good decisions

In contrast to clinical patient study data, there are no standards like CDISC to prescribe the format of the data for interchange of information. Furthermore, most patient data comes through one system (electronic data capture) so the data formats are more easily controlled by the Sponsor. For operational data, data tends to come from many sources. See table below:


All these sources have different formats and methods to share the data. Moreover, many Biotechs and Pharmaceutical companies use multiple vendors for each data source so the interactions can become voluminous. Therefore, integration services and transformations become critical to assemble the information into useable layouts to store data—or develop Big Data approaches store and retrieve data.

In the past, a robust Clinical Trial Management System (CTMS) was seen as the answer to able to supply data collection and visualization, but now this is really the start.   A CTMS may provide good solutions for study leads for operational data but often do not provide data required manage data across studies, data for metrics or additional analysis.

Few companies have established the perfect system to integrate all the operational data needed to be effective. Furthermore some established companies struggle with existing infrastructure which may not be flexible enough to get the data they need, and emerging companies are wondering if a CTMS approach is needed at all to provide operational data.

What to do?

The following are some of the questions that IT management can work with Pharmaceutical and Biotech leadership to help solve the operational data puzzle:

  • Is Senior Management and Clinical Management leadership getting the right data to manage their trials and meet strategic goals?
  • Are we collecting the right data with consistent definitions?
  • Are we collecting and integrating the data the right way?
  • Do data providers provide the data in a timely and consistent way?
  • Can we enhance what is already in place?
  • Are there solutions in the marketplace that can meet our data needs? Or will a custom solution be required?
  • How does this affect our CTMS efforts? Should the CRO use the Sponsor’s CTMS? Should the Sponsor integrate with CRO CTMS? Do we need a CTMS?
  • What impact will changes have on SOPs / Work instructions and how the work may be performed

Knowledgent Informationists can help analyze these questions and help your data challenges to develop a solution that makes sense for your unique environment.

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