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elaborator: A Novel App for Insights into Laboratory Data of Clinical Trials

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A Correction to this article was published on 22 July 2021

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Abstract

In clinical studies there are huge numbers of laboratory parameters available that are measured at several visits for several treatment groups. The status quo for presenting laboratory data in clinical trials consists in generating large numbers of tables and data listings. Such tables and listings are required for submissions to health authorities. However, reviewing laboratory data presented in the form of tables and listings is a lengthy and tedious process. Thus, to enable efficient exploration of laboratory data we developed elaborator, a comprehensive and easy-to-use interactive browser-based application. The elaborator app comprises three analyses types for addressing different questions, for example about changes in laboratory values that frequently occur, treatment-related changes and changes beyond the normal ranges. In this way, the app can be used by study teams for identifying safety signals in a clinical trial as well as for generating hypotheses that are further inspected with detailed analyses and possibly data from other sources. The elaborator app is implemented in the statistical software R. The R package elaborator can be obtained from https://cran.r-project.org/package=elaborator. Patients’ laboratory data need to be extracted from the clinical database and pre-processed locally for feeding into the app. For exploring data by means of the elaborator, the user needs some familiarity with R but no programming knowledge is required.

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Notes

  1. As there are three possibilities for a change (i.e., increase, decrease and stability) between two adjacent visits, and 4–1 transitions from one visit to the next in the considered example, there are 27 possible time courses.

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Acknowledgements

The authors thank Nicole Mentenich for proof-reading the manuscript.

Funding

The development of elaborator and the preparation of this manuscript were sponsored by Bayer AG.

Author information

Authors and Affiliations

  1. Research & Development, Pharmaceuticals, Statistics and Data Insights, Bayer AG, 13342, Berlin, Germany

    Silke Janitza PhD & Hermann Kulmann PhD

  2. Bayer US LLC, Whippany, NJ, USA

    Madhurima Majumder PhD

  3. Bayer AG, Wuppertal, Germany

    Franco Mendolia PhD

  4. Chrestos Concept GmbH & Co. KG, Essen, Germany

    Steffen Jeske MSc

Authors
  1. Silke Janitza PhD
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  2. Madhurima Majumder PhD
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  3. Franco Mendolia PhD
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  4. Steffen Jeske MSc
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  5. Hermann Kulmann PhD
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Contributions

All authors constituted the project team that developed the app. SJ is the main contributor of the manuscript. StJ supported the team in the implementation of the app.

Corresponding author

Correspondence to Silke Janitza PhD.

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Conflict of interest

Silke Janitza, Madhurima Majumder,· Franco Mendolia, Steffen Jeske, Hermann Kulmann have no conflicts of interest.

Additional information

The original online version of this article was revised because, due to a Production error, it was published without author corrections.

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Janitza, S., Majumder, M., Mendolia, F. et al. elaborator: A Novel App for Insights into Laboratory Data of Clinical Trials. Ther Innov Regul Sci 55, 1220–1229 (2021). https://doi.org/10.1007/s43441-021-00318-4

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  • DOI: https://doi.org/10.1007/s43441-021-00318-4

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