elaborator

elaborator facilitates exploration and analysis of laboratory data from clinical trials to identify treatment-related changes and potential safety signals.

Key Features:

• Analysis types: Supports three analysis types: identification of frequently occurring changes in laboratory values, examination of treatment-related changes, and detection of changes that exceed normal reference ranges.
• Safety signal and hypothesis generation: Analyzes patterns and anomalies in laboratory data to flag potential safety signals and generate hypotheses for follow-up analyses.
• R integration: Implemented in R and distributed as an R package available on CRAN at https://cran.r-project.org/package=elaborator.
• Data transformation and visualization: Transforms raw laboratory data into summary analyses and visualizations for review across multiple visits and treatment groups.

Scientific Applications:

• Clinical trial laboratory review: Evaluation of multiple laboratory parameters across visits and treatment arms to monitor biochemical and hematological changes.
• Safety monitoring: Identification of treatment-emergent or out-of-range laboratory changes that may indicate adverse events or safety signals.
• Regulatory submission support: Generation of summarized laboratory analyses suitable for inclusion in submissions to health authorities.
• Exploratory research: Hypothesis generation for further analyses or integration with additional data sources to investigate observed laboratory patterns.

Methodology:

Laboratory data are extracted from clinical databases and pre-processed locally, then input into elaborator for analysis performed using R (package available on CRAN).