Expert Insights

Expert Insights

Primary Considerations on Your Path to Data Integration

Primary Considerations on Your Path to Data Integration
09 August 2019

Congratulations! Your early-phase studies are going well and show promising efficacy results, combined with a reasonable safety profile. Your clinical team is planning confirmatory studies, your regulatory team is defining a submission structure, and your marketing team is discussing a branding strategy. You’re juggling a dozen different priorities and may be having trouble keeping up with everything on your desk. What else do you need to be thinking about?

The integrated summary of safety (ISS) and integrated summary of effectiveness (ISE) are critical components of the clinical efficacy and safety portions in marketing and licensing applications, according to FDA guidance [1]. As a result, the quality of the integrated clinical database is critical to the quality of the submission, although it’s a factor that may often be overlooked until later in the development program. How and when can you ensure that this database will come together as seamlessly as possible?

Integrating data across your clinical development program can be the largest and costliest project in your entire program from a Biostatistics standpoint. The timelines and costs for this effort can also vary considerably depending on the amount of prior planning that has been done. Other questions to ask in assessing data integration needs include:

  • How often has considering the requirements of the next study superseded documenting and/or archiving the previous study?
  • How have your company’s and the pharmaceutical industry’s standards evolved over the course of the program?
  • What can you do now to ensure that integration work goes smoothly?

Here are some additional steps to consider on your path to data integration:

  1. Collect information about all the studies to be integrated. Are you able to identify them all? With long development programs or compounds that are acquired during the process, even this first step can take research. Were any of the studies conducted by other companies, or were any of them investigator-initiated?
  1. Assess how much documentation you have for each of these studies. Do you have protocols, case report forms, databases, and clinical study reports for each of them? If so, what formats are they in, and if not, what’s missing for each study?
  1. After you assemble the documents and data for all the studies (or even as you’re assessing them), dig into the details. How are the data stored (e.g., Excel spreadsheets, SAS datasets, or other formats), and have the data been cleaned, queried, or verified? Are the datasets created using Clinical Data Interchange Standards Consortium (CDISC) standards? If so, what version of the standards was used for each study?
  1. Ask whether you have to define .xml files, reviewer’s guides, and other documentation and metadata for all the studies. What concomitant medication and adverse event coding has been done on your studies? How much information do you have on the units and normal ranges for any laboratory data collected?

There’s a lot to think about, but the good news is that if you start during your Phase II or Phase III studies, most of this work can be handled behind the scenes, separate from any critical-path timelines for your submission. While your clinical team plans your pivotal studies or addresses site start-up and enrollment considerations, your biostatistics team can pave the way for a smoother, quicker, less expensive submission.

Your team can collect documentation, assess the studies, and create CDISC-compliant Study Data Tabulation Model (SDTM) and Analysis Data Model (ADaM) datasets for legacy studies. Your biostatisticians can plan and write your integrated statistical analysis plans, decide how to group studies for analysis, and consider what time points and analytes to summarize. Your statistical programmers can research laboratory normal ranges and conversion factors for the data and collaborate with your coding team to decide what level of re-coding and up-versioning will be needed across the program. For more information on this, check out our recent blog post on legacy data conversion.

It’s a lot of planning, investigation, and up-front work, but putting data integration off can delay submission after the completion of your final studies. It’s easier and more cost-effective in the long run to start now.

Written by Joseph J. Murray, MS, Senior Director, Biostatistics

Contact us to learn how Synteract can help you with data integration and preparing for drug submission

[1]Guidance for Industry, Integrated Summaries of Effectiveness and Safety: Location Within the Common Technical Document, U.S. Department of Health and Human Services, Food and Drug Administration, April 2009.

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