"Measurement Errors in Blood Sampling Time in Population Pharmacokinetic Models"
Presenter: Leena Choi, PhD - Click Here
. Assistant Professor, Department of Biostatistics, Vanderbilt University School of Medicine
Observational population pharmacokinetic (PK) data collected from routine clinical practice is a potentially rich source of valuable information. In contrast to PK data collected from a clinical trial or a well controlled environment, the analysis of observational population PK data poses several statistical challenges. In particular, accurate time information for blood sample draw is often missing, resulting in measurement errors in the sampling time variable. We investigate the effects on inference on the model parameters when a scheduled time is used instead of the actual blood sampling time\; a method for correcting for measurement error is proposed. Simulation studies for a variety of scenarios are used to evaluate the effect of measurement error in the sampling time variable on PK parameter estimates.
Based on these results, recommendations are provided for future studies: 1) when the curvature of PK profiles is small, the conventional population PK modeling approach is highly robust to even large measurement errors in the sampling time\; and 2) when the curvature is moderate or large, our proposed method significantly reduces bias in PK parameter estimates.
Contact: Audrey Carvajal