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. 2019 Sep:142:364-376.
doi: 10.1016/j.ejpb.2019.07.005. Epub 2019 Jul 5.

Rat intestinal drug permeability: A status report and summary of repeated determinations

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Rat intestinal drug permeability: A status report and summary of repeated determinations

I R Dubbelboer et al. Eur J Pharm Biopharm. 2019 Sep.

Abstract

Intestinal permeability is a key biopharmaceutical variable in pharmaceutical research and development, and regulatory assessment. In situ rat models are often used to predict the corresponding human intestinal permeability data. The rat single-pass intestinal perfusion (SPIP) and intestinal closed loop (ICL) models are commonly applied. The primary objective of this study was to collect, summarize, and evaluate all the available intestinal permeability data for drugs that have been obtained using these two in-situ rat models. The permeability data were also investigated for variability between the experimental designs. The literature survey found 635 permeability determinations for 90 drugs. The studies were performed on the jejunum (n = 284), whole small intestine (n = 111), colon (n = 108), ileum (n = 101), and duodenum (n = 30). All the SPIP (n = 484) and ICL (n = 147) permeability values were summarized in an easily accessible database. There was wide variability in the intestinal permeability to each drug between studies, which was unrelated to the permeability class of the drug. There was no relationship between rat intestinal permeability and luminal pH, luminal drug concentration, rat strain, experimental method, or intestinal region. There was, however, a correlation between permeability values determined in the same laboratory. This report showed that the SPIP and ICL methods are important in situ models for understanding and predicting intestinal drug absorption. However, conclusions based on permeability values sourced from different laboratories may not be reliable. Because each permeability study is unique and because between- and even within-laboratory variability can be substantial, data from individual studies should preferably be interpreted separately.

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