Tohru Kokubo1, Shigeyuki Matsui, Makio Ishiguro. 1. The Graduate University for Advanced Studies, Shonan Village, Hayama, Kanagawa, 240-0193, Japan. tohru.kokubo@qualicaps.co.jp
Abstract
PURPOSE: Computer simulations are utilized during pharmaceutical development in order to design appropriate formulation based on the absorption, distribution, metabolism, and excretion (ADME) and physicochemical properties of target compounds, so that adequate prescriptions are offered to patients. Oro-cecal transit time (OCTT) is an important factor affecting these simulations because the absorption of drug that administered orally and the resultant pharmacokinetic profile are expressed as a function of time. Given the large intra- and inter-individual variance in OCTT, it is unsurprising that an accurate model has not yet been proposed. METHODS: We conducted a meta-analysis using subject-level data to construct a statistical model that predicted OCTT. Literature that utilized lactulose to measure OCTT was identified and analyzed using a mixed-effects model. RESULTS: The OCTTs of fasting healthy subjects were expressed using a linear model, with the amount of lactulose as the single significant explanatory factor. We found that this model could statistically distinguish the OCTTs of subjects with altered physical status from those of healthy people. Specifically, cystic fibrosis and celiac disease most significantly affected OCTT. CONCLUSION: The OCTT models developed herein incorporate inter-subject variations and can contribute to providing more accurate predictions of drug pharmacokinetic profiles.
PURPOSE: Computer simulations are utilized during pharmaceutical development in order to design appropriate formulation based on the absorption, distribution, metabolism, and excretion (ADME) and physicochemical properties of target compounds, so that adequate prescriptions are offered to patients. Oro-cecal transit time (OCTT) is an important factor affecting these simulations because the absorption of drug that administered orally and the resultant pharmacokinetic profile are expressed as a function of time. Given the large intra- and inter-individual variance in OCTT, it is unsurprising that an accurate model has not yet been proposed. METHODS: We conducted a meta-analysis using subject-level data to construct a statistical model that predicted OCTT. Literature that utilized lactulose to measure OCTT was identified and analyzed using a mixed-effects model. RESULTS: The OCTTs of fasting healthy subjects were expressed using a linear model, with the amount of lactulose as the single significant explanatory factor. We found that this model could statistically distinguish the OCTTs of subjects with altered physical status from those of healthy people. Specifically, cystic fibrosis and celiac disease most significantly affected OCTT. CONCLUSION: The OCTT models developed herein incorporate inter-subject variations and can contribute to providing more accurate predictions of drug pharmacokinetic profiles.
Authors: Jesse A Berlin; Jill Santanna; Christopher H Schmid; Lynda A Szczech; Harold I Feldman Journal: Stat Med Date: 2002-02-15 Impact factor: 2.373
Authors: K D Wutzke; W E Heine; C Plath; P Leitzmann; M Radke; C Mohr; I Richter; H U Gülzow; D Hobusch Journal: Eur J Clin Nutr Date: 1997-01 Impact factor: 4.016