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Presenting Clinical Data for Regulatory Submission: A Stats Perspective

Data submissions are very regulated, but every drug and drug development are different. Therefore, the data presented in the Common Technical Document (CTD) needs to be tailored to the specific submission. It’s important for statisticians involved in submission projects to not only understand the guidelines, but also what makes sense in terms of data integration and pooling. What follows is an introduction to the ISS/ISE from a stats perspective, which I recently shared at the Italian CDISC User Network on May 12, 2023.

The Common Technical Document: Relevant Modules and Guidelines

The Common Technical Document was developed in 2002 by the International Conference on Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) in order to provide a common format for submitting new drug applications to regulatory agencies worldwide. The CTD brings together all quality, safety, and efficacy data information in a common, harmonized format, which is accepted by regulators in all ICH regions.

The CTD is presented as a triangle, divided into modules: the more detailed information is contained in the lower modules, and the information is further summarized as you go up the triangle.

Florence Le Maulf_Intro to ISS ISE_Fig1

Statisticians and programmers get involved with the right part of the triangle, presenting clinical data in module 5, which includes module “Reports of Analyses for More than One Study,” where Integrated Summaries of Safety and Efficacy (ISS/ISE) can be placed, as well as modules 2.5 Clinical Overview, 2.7.3 Summary of Clinical Efficacy, and 2.7.4 Summary of Clinical Safety.

Integrated Summaries of Safety/Efficacy bring together in one place all data and analyses pertinent to a particular safety/efficacy issue or question. Looking primarily at data from individual studies or at data sets resulting from pooled data from several studies is not critical to the concept of an integrated review. Either approach, or both approaches, can be used in an integrated review. Data integrated in the ISS/ISE are then further summarized in the Summary of Clinical Efficacy and Summary of Clinical Safety (SCE/SCS), which present a detailed factual summary of all the clinical information in the CTD.

There are numerous guidelines about the CTD and its components. The following two guidelines describe further the possible content of ISS/ISEs and SCS/SCEs, depending on the specific drug development characteristics:

    • Integrated Summaries of Effectiveness and Safety: Location Within the Common Technical Document, Food and Drug Administration, Center for Drug Evaluation and Research (CDER), Center for Biologics Evaluation and Research (CBER), April 2009.
    • ICH M4E Common Technical Document for the Registration of Pharmaceuticals for Human Use — Efficacy, Scientific Guideline, 2016.


When to Use Data Pooling

It is very important at the start of a submission project to decide which data, from which studies or pooled analyses, will be used in each section of the Summary of Clinical Safety and Summary of Clinical Efficacy and whether an ISE or ISS will be required. In fact, pooled analyses are not mandatory and should only be performed if they provide additional insights beyond those observable in individual clinical trials. If pooled analyses are done, the objectives/reasons need to be explained and the validity of the pooling has to be justified.

The pooling strategy should be decided for efficacy and safety based on the ICH M4E guideline and the drug’s clinical development plan (number of studies, study designs, and so on). For example, for efficacy, it is assumed that only controlled studies should be pooled and, in general, the pooling is only valid if the studies have the same design, duration, population, endpoint, and consistent results.

The topic of whether an ISS and/or ISE will be produced and if there will be pooled analyses performed to support the ISS/ISE or the SCS/SCE needs to be agreed upon at the start of submission activities during an initial pooling strategy step. If pooling is done, then Statistical Analysis Plans (SAP) should be created for each of the ISS and ISE to describe which data from which studies will be pooled. The SAPs should also describe if extra mapping or derivations need to be performed due to differences in data collection or derivation between the studies and describe the stats methodology (such as testing for heterogeneity between studies and using methods for adjusting for differences in exposure durations).


Final Takeaways

Statisticians and programmers can contribute a lot to submission projects, helping clinical teams decide on the data pooling strategy that would best fit both the guidelines and the drug specificities. Our understanding of the characteristics of the data available for analysis from all the clinical trials is key to choosing how to best describe the drug’s whole story.

Florence Le Maulf ISS ISE Presentation photo

Interested in learning more about data submission? Download our complimentary new ebook, The Good Data Doctor on Data Submission and Data Integration:

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