Abstract
Estimating the in vivo absorption profile of a drug is essential when developing extended-release medications. Such estimates can be obtained by measuring plasma concentrations over time and inferring the absorption from a model of the drug’s pharmacokinetics. Of particular interest is to predict the bioavailability—the fraction of the drug that is absorbed and enters the systemic circulation. This paper presents a framework for addressing this class of estimation problems and gives advice on the choice of method. In parametric methods, a model is constructed for the absorption process, which can be difficult when the absorption has a complicated profile. Here, we place emphasis on non-parametric methods that avoid making strong assumptions about the absorption. A modern estimation method that can address very general input-estimation problems has previously been presented. In this method, the absorption profile is modeled as a stochastic process, which is estimated using Markov chain Monte Carlo techniques. The applicability of this method for extended-release formulation development is evaluated by analyzing a dataset of Bydureon, an injectable extended-release suspension formulation of exenatide, a GLP-1 receptor agonist for treating diabetes. This drug is known to have non-linear pharmacokinetics. Its plasma concentration profile exhibits multiple peaks, something that can make parametric modeling challenging, but poses no major difficulties for non-parametric methods. The method is also validated on synthetic data, exploring the effects of sampling and noise on the accuracy of the estimates.
Highlights
Extended-Release (ER) drug formulations are commonly used to improve the properties of drugs
The release/absorption profile is allowed to take any functional form as long as it matches the data and does not exhibit any unrealistic behavior, such as taking negative values. Predictions from such non-parametric methods are often sufficient for compound/formulation selection in drug discovery. This paper considers such non-parametric methods for estimating the release/absorption profile and bioavailability of extended-release formulations and gives advice on the choice of methods, given the data and system knowledge that are available
The model includes non-linear target-mediated drug disposition (TMDD) and is given by dC(t) dt u(t) Vc
Summary
Extended-Release (ER) drug formulations are commonly used to improve the properties of drugs. They can allow for less frequent dosing schedules, improving compliance and quality for the patient. They can improve safety by lowering the peak plasma concentration and enable the development and use of drugs whose pharmacokinetic (PK) properties would otherwise be unacceptable. For ER medications, the formulation design is intended to provide a targeted release or input rate that optimizes the compound PK. ER medications are typically administered orally (tablets and capsules) or injected as intramuscular/subcutaneous depot formulations.
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