Assessing parameter uncertainty in small-n pharmacometric analyses: value of the log-likelihood profiling-based sampling importance resampling (LLP-SIR) technique

• Published in: Journal of pharmacokinetics and pharmacodynamics Vol. 47; no. 3; pp. 219 - 228
• Main Authors: Broeker, Astrid, Wicha, Sebastian G.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2020; Springer Nature B.V
• Subjects: Bayesian analysis; Biochemistry; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Datasets; Drug development; Original Paper; Pharmacology/Toxicology; Pharmacy; Sampling; Veterinary Medicine/Veterinary Science; Log-likelihood profiling; Bootstrap; LLP-SIR; Small datasets; Sampling importance resampling; Parameter uncertainty

Assessing parameter uncertainty is a crucial step in pharmacometric workflows. Small datasets with ten or fewer subjects appear regularly in drug development and therapeutic use, but it is unclear which method to assess parameter uncertainty is preferable in such situations. The aim of this study wa...