Model-Based Analysis of Biopharmaceutic Experiments To Improve Mechanistic Oral Absorption Modeling: An Integrated in Vitro in Vivo Extrapolation Perspective Using Ketoconazole as a Model Drug

Abstract

Mechanistic modeling of in vitro data generated from metabolic enzyme systems (viz., liver microsomes, hepatocytes, rCYP enzymes, etc.) facilitates in vitro-in vivo extrapolation (IVIV_E) of metabolic clearance which plays a key role in the successful prediction of clearance in vivo within physiologically-based pharmacokinetic (PBPK) modeling. A similar concept can be applied to solubility and dissolution experiments whereby mechanistic modeling can be used to estimate intrinsic parameters required for mechanistic oral absorption simulation in vivo. However, this approach has not widely been applied within an integrated workflow. We present a stepwise modeling approach where relevant biopharmaceutics parameters for ketoconazole (KTZ) are determined and/or confirmed from the modeling of in vitro experiments before being directly used within a PBPK model. Modeling was applied to various in vitro experiments, namely: (a) aqueous solubility profiles to determine intrinsic solubility, salt limiting solubility factors and to verify pK; (b) biorelevant solubility measurements to estimate bile-micelle partition coefficients; (c) fasted state simulated gastric fluid (FaSSGF) dissolution for formulation disintegration profiling; and (d) transfer experiments to estimate supersaturation and precipitation parameters. These parameters were then used within a PBPK model to predict the dissolved and total (i.e., including the precipitated fraction) concentrations of KTZ in the duodenum of a virtual population and compared against observed clinical data. The developed model well characterized the intraluminal dissolution, supersaturation, and precipitation behavior of KTZ. The mean simulated AUC of the total and dissolved concentrations of KTZ were comparable to (within 2-fold of) the corresponding observed profile. Moreover, the developed PBPK model of KTZ successfully described the impact of supersaturation and precipitation on the systemic plasma concentration profiles of KTZ for 200, 300, and 400 mg doses. These results demonstrate that IVIV_E applied to biopharmaceutical experiments can be used to understand and build confidence in the quality of the input parameters and mechanistic models used for mechanistic oral absorption simulations in vivo, thereby improving the prediction performance of PBPK models. Moreover, this approach can inform the selection and design of in vitro experiments, potentially eliminating redundant experiments and thus helping to reduce the cost and time of drug product development.

On the Usefulness of Two Small-Scale In Vitro Setups in the Evaluation of Luminal Precipitation of Lipophilic Weak Bases in Early Formulation Development

“…At later stages of the development process, formulations can be tested using a full-scale in vitro method, which can provide a better representation of the gastrointestinal transit and luminal conditions, such as the BioGIT [42] or the so-called transfer model [43]. Information obtained from full-scale in vitro testing could then be included in the PBPK model to improve the modelling output [30,48]. In this way, the small-scale biphasic dissolution testing and the full-scale in vitro testing can be viewed as complementary in vitro tools used at different points of the developmental process.…”

“…PBPK modelling was carried out using the ADAM (Advanced Dissolution, Absorption, and Metabolism) model, which is available as part of the Simcyp PBPK simulator (Version 18, Release 2). Modelling was carried out in a stepwise fashion using an in vitro-in vivo extrapolation (IVIV_E) of dissolution and solubility, as outlined previously by Pathak et al [25,30] and Hens et al [35] Aqueous and bile micelle-mediated solubility data were estimated using the SIVA (Simcyp In Vitro Analysis) toolkit, using solubility data from Section 2.2.1 and other literature sources [18,25,30]. Initially, the intrinsic solubility and solubility factor were calculated using the experimental pH solubility profile in SIVA.…”

Integrating Drug- and Formulation-Related Properties With Gastrointestinal Tract Variability Using a Product-Specific Particle Size Approach: Case Example Ibuprofen

“…A stepwise IVIVE modeling approach previously described by Pathak et al 8 and illustrated in Figure 1 was applied to mitigate identifiability issues when estimating parameters from in vitro experiments. The Simcyp In Vitro Data Analysis Toolkit (SIVA® v3) was used to model in vitro experiments (i.e., solubility and dissolution) aiming to improve mechanistic understanding and estimate key parameters for simulating in vivo formulation performance and intraluminal drug disposition taking interindividual variability into account.…”

“…13 The solubility model in SIVA® is based on the Henderson-Hasselbalch equation together with a bile-micelle solubilization enhancement component that has already been detailed elsewhere. 8 Parameter estimation was performed using a built-in Nelder-Mead algorithm in SIVA®.…”

“…The empirical equation described by a Weibull or an empirical firstorder model have been successfully used to, respectively, describe experimental dissolution data and estimate precipitation parameters from transfer experiments. [6][7][8][9][10] However, the lack of mechanistic basis may limit the predictive capacity of this IVIVE approach to anticipate the impact of variations in critical material attributes or critical processes parameters on the intraluminal fate of the drug. Ideally, the IVIVE model should include a mechanistic implementation of formulation-or manufacturing-related variables relevant for drug dissolution and precipitation.…”