Application of Mixed-Effect Modeling to Improve Mechanistic Understanding and Predictability of Oral Absorption

Abstract: Several sophisticated techniques to study in vivo GI transit and regional absorption of pharmaceuticals are available and increasingly used. Examples of such methods are Magnetic Marker Monitoring (MMM) and local drug administration with remotely operated capsules. Another approach is the paracetamol and sulfapyridine double marker method which utilizes observed plasma concentrations of the two substances as markers for GI transit. Common for all of these methods is that they generate multiple types of observations e.g. tablet GI position, drug release and plasma concentrations of one or more substances. This thesis is based on the hypothesis that application of mechanistic nonlinear mixed-effect models could facilitate a better understanding of the interrelationship between such variables and result improved predictions of the processes involved in oral absorption.Mechanistic modeling approaches have been developed for application to data from MMM studies, paracetamol and sulfapyridine double marker studies and for linking in vitro and in vivo drug release. Models for integrating information about tablet GI transit, in vivo drug release and drug plasma concentrations measured in MMM studies was outlined and utilized to describe drug release and absorption properties along the GI tract for felodipine and the investigational drug AZD0837. A mechanistic link between in vitro and in vivo drug release was established by estimation of the mechanical stress in different regions of the GI tract in a unit equivalent to rotation speed in the in vitro experimental setup. The effect of atropine and erythromycin on gastric emptying and small intestinal transit was characterized with a semi-mechanistic model applied to double marker studies in fed and fasting dogs.The work with modeling of in vivo drug absorption has highlighted the need for, and led to, further development of mixed-effect modeling methodology with respect to model diagnostics and the handling of censored observations.