Introduction
coronavirus disease 2019
CORONAVIRUS, CORONAVIRUS DISEASE 2019, SEVERE ACUTE RESPIRATORY SYNDROME
Clinical trial datasets are becoming larger and increasingly complex with innovative advances in biomarker including genomic, transcriptomic, proteomic, and metabolomic measurements, mobile or wearable patient surveillance, and the use of real-world dataPharmacometricians are experts in data review, processing, and analysis in clinical and preclinical pharmacology. Reproducibility, defined as reaching the same outcome when repeating an analysisThe coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), became a world-wide pandemic. It particularly put a serious strain on the health care system of South AfricaThe objective of this work was therefore to create a reproducible pharmacometric workflow for data processing, reporting, and analysis in order to support the data safety monitoring board (DSMB) and allow for efficient, timely, and reproducible data analysis. We focussed on understanding of, and confidence in handling the growing clinical trial dataset, fast and reliable frequent reporting of aggregated and per-arm data, and consistency between the reporting and the subsequent pharmacometric analysis dataset. We present here the reproducible pharmacometrics workflow that led to the rapid pharmacometrics analyses of the trial, which are not the focus on this work and the outcome of which are reported separately.