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

Clinical laboratory data Clinical review Clinical trial Data exploration Interactive data visualization Question-based visualization

Journal

Therapeutic innovation & regulatory science
ISSN: 2168-4804
Titre abrégé: Ther Innov Regul Sci
Pays: Switzerland
ID NLM: 101597411

Informations de publication

Date de publication:
11 2021
Historique:
received: 08 02 2021
accepted: 18 06 2021
pubmed: 2 7 2021
medline: 16 10 2021
entrez: 1 7 2021
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 34196957
doi: 10.1007/s43441-021-00318-4
pii: 10.1007/s43441-021-00318-4
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1220-1229

Commentaires et corrections

Type : ErratumIn
Type : CommentIn
Type : CommentIn

Informations de copyright

© 2021. The Drug Information Association, Inc.

Références

Kulmann H, Muysers C, Dmitrienko A, Röhmel J. The biostatistics innovation center at Bayer. Biopharm Rep. 2016;23:1–5.
Bradley L, Singh S, Simon J, Gemzell-Danielsson K, Petersdorf K, Groettrup-Wolfers E, Ren X, Zvolanek M, Seitz C. Vilaprisan in women with uterine fibroids: the randomized phase 2b ASTEROID 1 study. Fertil Steril. 2019;111:240–8.
doi: 10.1016/j.fertnstert.2018.10.012
Hahsler M, Hornik K, Buchta C. Getting things in order: an introduction to the R package seriation.J Stat Softw. 2008;25:1–34.
doi: 10.18637/jss.v025.i03
Hahsler M, Buchta C, Hornik K. Seriation: infrastructure for ordering objects using seriation: R package version 1.2–8. Available from https://CRAN.R-project.org/package=seriation .
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2020. Available from https://www.R-project.org/
Chang W, Cheng J, Allaire J, Xie Y, McPherson J. shiny: Web application framework for R. R package version 1.5.0. Available from https://CRAN.R-project.org/package=shiny

Auteurs

Silke Janitza (S)

Research & Development, Pharmaceuticals, Statistics and Data Insights, Bayer AG, 13342, Berlin, Germany. silke.janitza@bayer.com.

Madhurima Majumder (M)

Bayer US LLC, Whippany, NJ, USA.

Franco Mendolia (F)

Bayer AG, Wuppertal, Germany.

Steffen Jeske (S)

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

Hermann Kulmann (H)

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

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Classifications MeSH