Forecasting oral absorption across biopharmaceutics classification system classes with physiologically based pharmacokinetic models

Predictions of tissue concentrations of myclobutanil, oxyfluorfen, and pronamide in rat and human after oral exposures via GastroPlusTM physiologically based pharmacokinetic modelling

Heritage agrochemicals like myclobutanil, oxyfluorfen, and pronamide, are extensively used in agriculture, with well-established studies on their animal toxicity. Yet, human toxicity assessment relies on conventional human risk assessment approaches including the utilization of animal-based ADME (Absorption, Distribution, Metabolism, and Excretion) data. In recent years, Physiologically Based Pharmacokinetic (PBPK) modelling approaches have played an increasing role in human risk assessment of many chemicals including agrochemicals. This study addresses the absence of PBPK-type data for myclobutanil, oxyfluorfen, and pronamide by generating in vitro data for key input PBPK parameters (Caco-2 permeability, rat plasma binding, rat blood to plasma ratio, and rat liver microsomal half-life), followed by generation of PBPK models for these three chemicals via the GastroPlusTM software. Incorporating these experimental input parameters into PBPK models, the prediction accuracy of plasma AUC (area under curve) was significantly improved. Validation against rat oral administration data demonstrated substantial enhancement. Steady-state plasma concentrations (Css) of pronamide aligned well with published data using measured PBPK parameters. Following validation, parent-based tissue concentrations for these agrochemicals were predicted in humans and rats after single or 30-day repeat exposure of 10 mg/kg/day. These predicted concentrations contribute valuable information for future human toxicity risk assessments of these agrochemicals.

A Design-Conversed Strategy Establishes the Performance Safe Space for Doxorubicin Nanosimilars

Nanomedicines exhibit multifaceted performances, yet their biopharmaceutics remain poorly understood and present several challenges in the translation from preclinical to clinical research. To address this issue and promote the production of high-quality nanomedicines, a systematic screening of the design space and in vivo performance is necessary. Establishing formulation performance specifications early on enables an informed selection of candidates and promotes the development of nanosimilars. The deconvolution of the pharmacokinetics enables the identification of key characteristics that influence their performances and disposition. Using an in vitro-in vivo rank-order relationship for doxorubicin nanoformulations, we defined in vitro release specifications for Doxil/Caelyx-like follow-on products. Additionally, our model predictions were used to establish the bioequivalence of Lipodox, a nanosimilar of Doxil/Caelyx. Furthermore, a virtual safe space was established, providing crucial insights into expected disposition kinetics and informing formulation development. By addressing bottlenecks in biopharmaceutics and formulation screening, our research advances the translation of nanomedicine from bench to bedside.

PBPK Modeling as an Alternative Method of Interspecies Extrapolation that Reduces the Use of Animals: A Systematic Review

INTRODUCTION

Physiologically based pharmacokinetic (PBPK) modeling is a computational approach that simulates the anatomical structure of the studied species and presents the organs and tissues as compartments interconnected by arterial and venous blood flows.

AIM

The aim of this systematic review was to analyze the published articles focused on the development of PBPK models for interspecies extrapolation in the disposition of drugs and health risk assessment, presenting to this modeling an alternative to reduce the use of animals.

METHODS

For this purpose, a systematic search was performed in PubMed using the following search terms: "PBPK" and "Interspecies extrapolation". The revision was performed according to PRISMA guidelines.

RESULTS

In the analysis of the articles, it was found that rats and mice are the most commonly used animal models in the PBPK models; however, most of the physiological and physicochemical information used in the reviewed studies were obtained from previous publications. Additionally, most of the PBPK models were developed to extrapolate pharmacokinetic parameters to humans and the main application of the models was for toxicity testing.

CONCLUSION

PBPK modeling is an alternative that allows the integration of in vitro and in silico data as well as parameters reported in the literature to predict the pharmacokinetics of chemical substances, reducing in large quantity the use of animals that are required in traditional studies.

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1-4 by Virtual Bioequivalence Model

To evaluate the influence of solubility and permeability on the pharmacokinetic prediction performance of orally administered drugs using avirtual bioequivalence (VBE) model, a total of 23 orally administered drugs covering Biopharmaceutics Classification System (BCS) classes 1-4 were selected. A VBE model (i.e., a physiologically based pharmacokinetic model integrated with dissolution data) based on a B²O simulator was applied for pharmacokinetic (PK) prediction in a virtual population. Parameter sensitivity analysis was used for input parameter selection. The predictive performances of PK parameters (i.e., AUC_0-t, C_max, and T_max), PK profiles, and bioequivalence (BE) results were evaluated using the twofold error, average fold error (AFE), absolute average fold error (AAFE), and BE reassessment metrics. All models successfully simulated the mean PK profiles, with AAFE < 2 and AFE ranging from 0.58 to 1.66. As for the PK parameters, except for the time of peak concentration, T_max, of isosorbide mononitrate, other simulated PK parameters were all within a twofold error. The simulated PK behaviors were comparable to the observed ones, both for test (T) and reference (R) products, and the simulated T/R arithmetic mean ratios were all within 0.88-1.16 of the observed values. These four evaluation metrics were distributed equally among BCS class 1-4 drugs. The VBE model showed powerful performance to predict the PK behavior of orally administered drugs with various combinations of solubility and permeability, irrespective of the BCS category.

A Physiologically-Based Pharmacokinetic Model of Ruxolitinib and Posaconazole to Predict CYP3A4-Mediated Drug-Drug Interaction Frequently Observed in Graft versus Host Disease Patients

Ruxolitinib (RUX) is approved for the treatment of steroid-refractory acute and chronic graft versus host disease (GvHD). It is predominantly metabolized via cytochrome P450 (CYP) 3A4. As patients with GvHD have an increased risk of invasive fungal infections, RUX is frequently combined with posaconazole (POS), a strong CYP3A4 inhibitor. Knowledge of RUX exposure under concomitant POS treatment is scarce and recommendations on dose modifications are inconsistent. A physiologically based pharmacokinetic (PBPK) model was developed to investigate the drug-drug interaction (DDI) between POS and RUX. The predicted RUX exposure was compared to observed concentrations in patients with GvHD in the clinical routine. PBPK models for RUX and POS were independently set up using PK-Sim^® Version 11. Plasma concentration-time profiles were described successfully and all predicted area under the curve (AUC) values were within 2-fold of the observed values. The increase in RUX exposure was predicted with a DDI ratio of 1.21 (C_max) and 1.59 (AUC). Standard dosing in patients with GvHD led to higher RUX exposure than expected, suggesting further dose reduction if combined with POS. The developed model can serve as a starting point for further simulations of the implemented DDI and can be extended to further perpetrators of CYP-mediated PK-DDIs or disease-specific physiological changes.

Predicting nonlinear relationships between external and internal concentrations with physiologically based pharmacokinetic modeling

Although external concentrations are more readily quantified and often used as the metric for regulating and mitigating exposures to environmental chemicals, the toxicological response to an environmental chemical is more directly related to its internal concentrations than the external concentration. The processes of absorption, distribution, metabolism, and excretion (ADME) determine the quantitative relationship between the external and internal concentrations, and these processes are often susceptible to saturation at high concentrations, which can lead to nonlinear changes in internal concentrations that deviate from proportionality. Using generic physiologically-based pharmacokinetic (PBPK) models, we explored how saturable absorption or clearance influence the shape of the internal to external concentration (IEC) relationship. We used the models for hypothetical chemicals to show how differences in kinetic parameters can impact the shape of an IEC relationship; and models for styrene and caffeine to explore how exposure route, frequency, and duration impact the IEC relationships in rat and human exposures. We also analyzed available plasma concentration data for 2,4-dichlorophenoxyacetic acid to demonstrate how a PBPK modeling approach can be an alternative to common statistical methods for analyzing dose proportionality. A PBPK modeling approach can be a valuable tool used in the early stages of a chemical safety assessment program to optimize the design of longer-term animal toxicity studies or to interpret study results.

In silico predictions of absorption of MDI substances after dermal or inhalation exposures to support a category based read-across assessment

Methylenediphenyl diisocyanate (MDI) substances used polyurethane production can range from their simplest monomeric forms (e.g., 4,4'-MDI) to mixtures of the monomers with various homologues, homopolymer, and prepolymer derivatives. The relative dermal or inhalation absorption of 39 constituents of these substances in human were predicted using the GastroPlus® program. Predicted dermal uptake and absorption of the three MDI monomers from an acetone vehicle was 84-86% and 1.4-1.5%, respectively, with lower uptake and absorption predicted for the higher MW analogs. Lower absorption was predicted from exposures in a more lipophilic vehicle (1-octanol). Modeled inhalation exposures afforded the highest pulmonary absorption for the MDI monomers (38-54%), with 3-27% for the MW range of 381-751, and <0.1% for the remaining, higher MW derivatives. Predicted oral absorption, representing mucociliary transport, ranged from 5 to 10% for the MDI monomers, 10-25% for constituents of MW 381-751, and ≤3% for constituents with MW > 900. These in silico evaluations should be useful in category-based, worst-case, Read-Across assessments for MDI monomers and modified MDI substances for potential systemic effects. Predictions of appreciable mucociliary transport may also be useful to address data gaps in oral toxicity testing for this category of compounds.

An Update to Dialysis-Based Drug Release Testing-Data Analysis and Validation Using the Pharma Test Dispersion Releaser

Currently, a wide variety of complex non-oral dosage forms are entering the global healthcare market. Although many assays have been described in recent research, harmonized procedures and standards for testing their in vitro performance remain widely unexplored. Among others, dialysis-based techniques such as the Pharma Test Dispersion Releaser are developed for testing the release of drugs from nanoparticles, liposomes, or extracellular vesicle preparations. Here, we provide advanced strategies and practical advice for the development and validation of dialysis-based techniques, including documentation, analysis, and interpretation of the raw data. For this purpose, key parameters of the release assay, including the hydrodynamics in the device at different stirring rates, the selectivity for particles and molecules, as well as the effect of excipients on drug permeation were investigated. At the highest stirring rate, a more than twofold increase in the membrane permeation rate (from 0.99 × 10⁻³ to 2.17 × 10⁻³ cm²/h) was observed. Additionally, we designed a novel computer model to identify important quality parameters of the dialysis experiment and to calculate error-corrected release profiles. Two hydrophilic creams of diclofenac, Voltaren^® Emulgel, and Olfen^® gel, were tested and provide first-hand evidence of the robustness of the assay in the presence of semisolid dosage forms.

Application of physiologically based biopharmaceutics modeling to understand the impact of dissolution differences on in vivo performance of immediate release products: The case of bisoprolol

Merck KGaA observed slight differences in the dissolution of Concor® (bisoprolol) batches over the years. The purpose of this work was to assess the impact of in vitro dissolution on the simulated pharmacokinetics of bisoprolol using in vitro-in vivo relationship established with available in vitro dissolution and corresponding plasma concentrations-time data for several bisoprolol batches. A mechanistic absorption model/physiologically based pharmacokinetics model linked with a biopharmaceutics tool such as dissolution testing, namely, physiologically based biopharmaceutics modeling (PBBM), can be valuable in determining a dissolution "safe space." A PBBM for bisoprolol was built using in vitro, in silico, and clinical data. We evaluated potential influences of variability in dissolution of bisoprolol batches on its clinical performance through PBBM and virtual bioequivalence (BE) trials. We demonstrated that in vitro dissolution was not critical for the clinical performance of bisoprolol over a wide range of tested values. Based on virtual BE trials, safe space expansion was explored using hypothetical dissolution data. A formulation with in vitro dissolution reaching 70% dissolved in 15 min and 79.5% in 30 min was shown to be BE to classical fast dissolution of bisoprolol (>85% within 15 min), as point estimates and 90% confidence intervals of the maximum plasma concentration and area under the concentration-time curve were within the BE limits (0.8-1.25).

Physiologically Based Biopharmaceutics Modeling of Regional and Colon Absorption in Dogs

Colon absorption is a key determinant for the successful development of modified-release (MR) formulations, and the risk that colon absorption may limit the in vivo performance of an MR product can be assessed early by various in vitro tests or by preclinical in vivo regional absorption studies in dogs. Mechanistic physiologically based biopharmaceutics modeling (PBBM) is becoming increasingly accepted to predict in vivo performance and guide formulation development; however, no evaluation of the ability to predict colon absorption has been performed. The purpose of this study was to investigate if regional and colon absorption of drugs in dogs could be predicted with sufficient accuracy using PBBM to enable the replacement of in vivo dog studies in the early assessment of colon absorption limitation risks. This was done by predicting the regional and colon absorption and plasma exposure of 14 drugs after administration to the dog colon according to an a priori approach using the in silico absorption models GI-Sim and GastroPlus. Predictive performance was primarily assessed by comparing observed and predicted plasma concentration-time profiles, AUC_0-t, and the relative bioavailability in the colon (F_rel,colon) as compared to an oral/duodenal reference. Trends in dependency of prediction performance on predicted fraction absorbed, permeability, and solubility/dissolution rate were also investigated. For GI-Sim, the absolute average fold error (AAFE) values for AUC_0-t and F_rel,colon were within a 2-fold prediction error for both solutions (1.88 and 1.51, respectively) and suspensions (1.58 and 1.99, respectively). For GastroPlus, the AAFE values for AUC_0-t and F_rel,colon were outside the set 2-fold prediction error limit for accurate predictions for both solutions (3.63 and 2.98, respectively) and suspensions (2.94 and 2.09, respectively). No trends for over- or underprediction were observed for GI-Sim, whereas GastroPlus showed a slight trend for underprediction of both AUC_0-t and F_rel,colon for compounds with low permeability. In addition, regional differences in the plasma profiles were qualitatively predicted in the majority of cases for both software. Despite the differences in prediction performance, both models can be considered to predict regional differences in absorption as well as AUC_0-t and F_rel,colon with acceptable accuracy in an early development setting. The results of this study indicate that it is acceptable to replace in vivo regional absorption studies in dogs with the evaluated models as a method for the early assessment of the risk for colon absorption limitation of MR drug product candidates.

Physiologically Based Pharmacokinetic Models of Probenecid and Furosemide to Predict Transporter Mediated Drug-Drug Interactions

Purpose

To provide whole-body physiologically based pharmacokinetic (PBPK) models of the potent clinical organic anion transporter (OAT) inhibitor probenecid and the clinical OAT victim drug furosemide for their application in transporter-based drug-drug interaction (DDI) modeling.

Methods

PBPK models of probenecid and furosemide were developed in PK-Sim®. Drug-dependent parameters and plasma concentration-time profiles following intravenous and oral probenecid and furosemide administration were gathered from literature and used for model development. For model evaluation, plasma concentration-time profiles, areas under the plasma concentration–time curve (AUC) and peak plasma concentrations (C_max) were predicted and compared to observed data. In addition, the models were applied to predict the outcome of clinical DDI studies.

Results

The developed models accurately describe the reported plasma concentrations of 27 clinical probenecid studies and of 42 studies using furosemide. Furthermore, application of these models to predict the probenecid-furosemide and probenecid-rifampicin DDIs demonstrates their good performance, with 6/7 of the predicted DDI AUC ratios and 4/5 of the predicted DDI C_max ratios within 1.25-fold of the observed values, and all predicted DDI AUC and C_max ratios within 2.0-fold.

Conclusions

Whole-body PBPK models of probenecid and furosemide were built and evaluated, providing useful tools to support the investigation of transporter mediated DDIs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-020-02964-z.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies

Physiologically based pharmacokinetic modelling is well established in the pharmaceutical industry and is accepted by regulatory agencies for the prediction of drug-drug interactions. However, physiologically based pharmacokinetic modelling is valuable to address a much wider range of pharmaceutical applications, and new regulatory impact is expected as its full power is leveraged. As one example, physiologically based pharmacokinetic modelling is already routinely used during drug discovery for in-vitro to in-vivo translation and pharmacokinetic modelling in preclinical species, and this leads to the application of verified models for first-in-human pharmacokinetic predictions. A consistent cross-industry strategy in this application area would increase confidence in the approach and facilitate further learning. With this in mind, this article aims to enhance a previously published first-in-human physiologically based pharmacokinetic model-building strategy. Based on the experience of scientists from multiple companies participating in the GastroPlus™ User Group Steering Committee, new Absorption, Distribution, Metabolism and Excretion knowledge is integrated and decision trees proposed for each essential component of a first-in-human prediction. We have reviewed many relevant scientific publications to identify new findings and highlight gaps that need to be addressed. Finally, four industry case studies for more challenging compounds illustrate and highlight key components of the strategy.

Review of the pharmacokinetics and metabolism of triclopyr herbicide in mammals: Impact on safety assessments

A review of pharmacokinetic and metabolism studies show that triclopyr is well absorbed from the oral route in numerous species (≥80%), primarily as parent compound. Absorption is quite rapid in rats, dogs and human volunteers. Plasma or blood clearance is also rapid (t_1/2 3-9 h), except for dog (12-96 h). Systemic exposure is not dose-proportional: in the rat above 20 mg/kg (dietary) or between 3 and 60 mg/kg (gavage), or in dogs above 5 mg/kg, with systemic exposure in human more comparable to rat than dog. Triclopyr is highly bound to protein in rat, dog and human plasma (≥97% at or below 7 μg/mL), indicating that species differences in systemic exposure are not due to differences in the free fraction of this test material in plasma. An in vitro flux study in renal proximal tubule cells showed that net renal transport of triclopyr is in the direction of secretion in rat and human donors, while reabsorption predominated in the dog, possibly via organic anion transporters such as OAT1/3. These results fit well into the framework of utilizing metabolism and toxicokinetics across species and exposure levels to allow for toxicity testing in the most relevant species as well as at proper dose levels.

A physiologically-based nanocarrier biopharmaceutics model to reverse-engineer the in vivo drug release

Over the years, a wide variety of nanomedicines has entered global markets, providing a blueprint for the emerging generics industry. They are characterized by a unique pharmacokinetic behavior difficult to explain with conventional methods. In the present approach a physiologically-based nanocarrier biopharmaceutics model has been developed. Providing a compartmental framework of the distribution and elimination of nanocarrier delivery systems, this model was applied to human clinical data of the drug products Doxil®, Myocet®, and AmBisome® as well as to the formulation prototypes Foslip® and NanoBB-1-Dox. A parameter optimization by differential evolution led to an accurate representation of the human data (AAFE < 2). For each formulation, separate half-lives for the carrier and the free drug as well as the drug release were calculated from the total drug concentration-time profile. In this context, a static in vitro set-up and the dynamic in vivo situation with a continuous infusion and accumulation of the carrier were simulated. For Doxil®, a total drug release ranging from 0.01 to 22.1% was determined. With the time of release exceeding the elimination time of the carrier, the major fraction was available for drug targeting. NanoBB-1-Dox released 76.2-77.8% of the drug into the plasma, leading to an accumulated fraction of approximately 20%. The mean residence time of encapsulated doxorubicin was 128 h for Doxil® and 0.784 h for NanoBB-1-Dox, giving the stealth liposomes more time to accumulate at the intended target site. For all other formulations, Myocet®, AmBisome®, and Foslip®, the major fraction of the dose was released into the blood plasma without being available for targeted delivery.

A sensitive in vitro performance assay reveals the in vivo drug release mechanisms of long-acting medroxyprogesterone acetate microparticles

Today, a growing number of subcutaneously administered depot formulations enable continuous delivery of poorly soluble compounds over a longer time period. The modified liberation is considered to be a rate-limiting step in drug absorption and thus impacts therapeutic efficacy and product safety. In the present approach, a mechanism-based pharmacokinetic model of the commercial microparticle formulation depo-subQ provera 104™ (Sauter mean diameter of 5.08 ± 1.63 µm) was established. The model was verified using human pharmacokinetic data from three different clinical trials. Further, the effects of drug release, injection site and patient population on the pharmacokinetic profile were investigated. For this purpose, the drug release was assessed using the novel dispersion releaser technology, whereby a biorelevant medium reflecting major characteristics of the subcutaneous tissue (including ion background, buffer capacity and protein concentration) was used. The established model provided an effective prediction of the key pharmacokinetic parameters, including C_max, T_max and AUC_all. Only in presence of 55% of fetal bovine serum (using a novel simulated subcutaneous interstitial fluid), the release assay was capable to discriminate between microparticles before and after storage.

Understanding the Oral Absorption of Irbesartan Using Biorelevant Dissolution Testing and PBPK Modeling

Poorly soluble weak bases form a significant proportion of the drugs available in the market thereby making it imperative to understand their absorption behavior. This work aims to mechanistically understand the oral absorption behavior for a weakly basic drug, Irbesartan (IRB), by investigating its pH dependent solubility, supersaturation, and precipitation behavior. Simulations performed using the equilibrium solubility could not accurately predict oral absorption. A multi-compartmental biorelevant dissolution testing model was used to evaluate dissolution in the stomach and duodenal compartment and mimic oral drug administration. This model exhibited sustained intestinal supersaturation (2-4-fold) even upon varying flow rates (4 mL/min, 7 mL/min, and mono-exponential transfer) from gastric to intestinal compartment. Simulation of oral absorption using GastroPlus™ and dissolution data collectively predicted plasma exposure with higher accuracy (% prediction error values within ± 15%), thereby indicating that multi-compartment dissolution testing enabled an improved prediction for oral pharmacokinetics of Irbesartan. Additionally, precipitates obtained in the intestinal compartment were characterized to determine the factors underlying intestinal supersaturation of Irbesartan. The solid form of these precipitates was amorphous with considerable particle size reduction. This indicated that following gastric transit, precipitate formation in the amorphous form coupled with an approximately 10 times particle size reduction could be potential factors leading to the generation and sustenance of intestinal drug supersaturation.

Prediction Characteristics of Oral Absorption Simulation Software Evaluated Using Structurally Diverse Low-Solubility Drugs

The purpose of the present study was to characterize current biopharmaceutics modeling and simulation software regarding the prediction of the fraction of a dose absorbed (Fa) in humans. As commercial software products, GastroPlus™ and Simcyp® were used. In addition, the gastrointestinal unified theoretical framework, a simple and publicly accessible model, was used as a benchmark. The Fa prediction characteristics for a total of 96 clinical Fa data of 27 model drugs were systematically evaluated using the default settings of each software product. The molecular weight, dissociation constant, octanol-water partition coefficient, solubility in biorelevant media, dose, and particle size of model drugs were used as input data. Although the same input parameters were used, GastroPlus™, Simcyp®, and the gastrointestinal unified theoretical framework showed different Fa prediction characteristics depending on the rate-limiting steps of oral drug absorption. The results of the present study would be of great help for the overall progression of physiologically based absorption models.

Requirements to Establishing Confidence in Physiologically Based Pharmacokinetic (PBPK) Models and Overcoming Some of the Challenges to Meeting Them

When scientifically well-founded, the mechanistic basis of physiologically based pharmacokinetic (PBPK) models can help reduce the uncertainty and increase confidence in extrapolations outside the studied scenarios or studied populations. However, it is not always possible to establish mechanistically credible PBPK models. Requirements to establishing confidence in PBPK models, and challenges to meeting these requirements, are presented in this article. Parameter non-identifiability is the most challenging among the barriers to establishing confidence in PBPK models. Using case examples of small molecule drugs, this article examines the use of hypothesis testing to overcome parameter non-identifiability issues, with the objective of enhancing confidence in the mechanistic basis of PBPK models and thereby improving the quality of predictions that are meant for internal decisions and regulatory submissions. When the mechanistic basis of a PBPK model cannot be established, we propose the use of simpler models or evidence-based approaches.

Application of data mining approach to identify drug subclasses based on solubility and permeability

Solubility and permeability are recognized as key parameters governing drug intestinal absorption and represent the basis for biopharmaceutics drug classification. The Biopharmaceutics Classification System (BCS) is widely accepted and adopted by regulatory agencies. However, currently established low/high permeability and solubility boundaries are the subject of the ongoing scientific discussion. The aim of the present study was to apply data mining analysis on the selected drugs data set in order to develop a human permeability predictive model based on selected molecular descriptors, and to perform data clustering and classification to identify drug subclasses with respect to dose/solubility ratio (D/S) and effective permeability (P_eff ). The P_eff values predicted for 30 model drugs for which experimental human permeability data are not available were in good agreement with the reported fraction of drug absorbed. The results of clustering and classification analysis indicate the predominant influence of P_eff over D/S. Two P_eff cut-off values (1 × 10^-4 and 2.7 × 10^-4  cm/s) have been identified indicating the existence of an intermediate group of drugs with moderate permeability. Advanced computational analysis employed in the present study enabled the recognition of complex relationships and patterns within physicochemical and biopharmaceutical properties associated with drug bioperformance.

Performance evaluation of the GastroPlusTM software tool for prediction of the toxicokinetic parameters of chemicals

The accurate prediction of toxicokinetic parameters arising from oral, dermal and inhalation routes of chemical exposure is a key element in chemical safety assessments. In this research, the physiologically based pharmacokinetic (PBPK) GastroPlus^TM software was evaluated against a series of chemicals for the prediction of toxicokinetic parameters. Overall, 67% of predicted intrinsic clearance (Clint) values were within 1- to 10-fold of empirical data for 463 compounds, and 87% of the predicted fraction unbounded in plasma (Fup) values were 1- to 3-fold of empirical data for 441 compounds. The r² (coefficient of determination) of predicted C_max (maximum plasma concentration) and AUC (Area Under Curve) values versus the corresponding empirical values from oral, inhalation and dermal exposures ranged from 0.04 to 0.92. Among the three exposures, the highest r² values, ranging from 0.80 to 0.92, were observed for oral exposure predictions, where 88% of the compounds had 1- to 10-fold differences between predicted and empirical values for C_max and AUC. The predicted plasma C_ss (steady-state plasma concentration) values were consistent with those C_ss values calculated by in vitro-to-in vivo extrapolation (IVIVE) approaches using experimental parameters. Based on the evaluation results, GastroPlus™ can be used as a QSAR/PBPK tool for toxicokinetic parameter predictions.

Physiologically based pharmacokinetic modelling to guide drug delivery in older people

Older patients are generally not included in Phase 1 clinical trials despite being the population group who use the largest number of prescription medicines. Physiologically based pharmacokinetic (PBPK) modelling provides an understanding of the absorption and disposition of drugs in older patients. In this review, PBPK models used for the prediction of absorption and exposure of drugs after parenteral, oral and transdermal administration are discussed. Comparisons between predicted drug pharmacokinetics (PK) and observed PK are presented to illustrate the accuracy of the predictions by the PBPK models and their potential use in informing clinical trial design and dosage adjustments in older patients. In addition, a case of PBPK modelling of a bioequivalence study on two controlled release products is described, where PBPK predictions reproduced the study showing bioequivalence in healthy volunteers but not in older subjects with achlorhydria, indicating further utility in prospectively identifying challenges in bioequivalence studies.

In vitro methods to assess drug precipitation in the fasted small intestine – a PEARRL review

Objectives

Drug precipitation in vivo poses a significant challenge for the pharmaceutical industry. During the drug development process, the impact of drug supersaturation or precipitation on the in vivo behaviour of drug products is evaluated with in vitro techniques. This review focuses on the small and full scale in vitro methods to assess drug precipitation in the fasted small intestine.

Key findings

Many methods have been developed in an attempt to evaluate drug precipitation in the fasted state, with varying degrees of complexity and scale. In early stages of drug development, when drug quantities are typically limited, small-scale tests facilitate an early evaluation of the potential precipitation risk in vivo and allow rapid screening of prototype formulations. At later stages of formulation development, full-scale methods are necessary to predict the behaviour of formulations at clinically relevant doses. Multicompartment models allow the evaluation of drug precipitation after transfer from stomach to the upper small intestine. Optimisation of available biopharmaceutics tools for evaluating precipitation in the fasted small intestine is crucial for accelerating the development of novel breakthrough medicines and reducing the development costs.

Summary

Despite the progress from compendial quality control dissolution methods, further work is required to validate the usefulness of proposed setups and to increase their biorelevance, particularly in simulating the absorption of drug along the intestinal lumen. Coupling results from in vitro testing with physiologically based pharmacokinetic modelling holds significant promise and requires further evaluation.

An in silico approach to determine challenges in the bioavailability of ciprofloxacin, a poorly soluble weak base with borderline solubility and permeability characteristics

Ciprofloxacin is administered as the hydrochloride salt in immediate release formulations for the treatment of various infectious diseases in different patient populations. Due to its weakly basic properties and poor solubility, the in vivo behaviour of this compound could be influenced by both physicochemical and physiological factors. The first aim of this study was to investigate the behaviour of ciprofloxacin (Ciprobay® 500 mg tablets) in the human gastro-intestinal tract with in vitro dissolution, transfer and two-stage experiments. Ciprobay® IR tablets dissolved completely in FaSSGF-V2, but dissolution was incomplete in FaSSIF-V2 and in an achlorhydric medium (FaSSGF-achlorhydric) and slow precipitation was observed in all three media. Ciprofloxacin did not precipitate in the transfer model but in the two-stage test, a simplified version of the transfer model, some precipitation was detected. In the second part of this study the data obtained in the in vitro transfer experiment were integrated into a Physiologically Based Pharmacokinetic (PBPK) Model. Based on the in vitro results, it was concluded that precipitation of ciprofloxacin would be unlikely in vivo. When precipitation was assumed to be negligible in the PBPK model, good predictions of plasma concentration time profiles provided by Bayer Pharma AG and obtained from the open literature were attained. Parameter Sensitivity Analysis (PSA) was conducted on several parameters which may influence the in vivo behaviour of ciprofloxacin. It was shown that precipitation in the gastro-intestinal tract in humans after a dose of 500 mg is not a determinant of the PK profile. PSA further suggested that ciprofloxacin behaves in vivo as a BCS Class I drug according to the Biopharmaceutics Classification System (BCS), even though on the basis of available solubility and permeability data the compound has been categorised as a BCS II/IV drug. These findings illustrate the importance of coupling in vitro results with in silico PBPK models to better understand the in vivo behaviour of weakly basic drugs. The PBPK model of ciprofloxacin, which was set up for healthy volunteers, was also modified to predict the in vivo behaviour of ciprofloxacin in several different patient populations. It was shown on the basis of these simulations that the plasma concentration time profile may be less influenced by disease state than previously expected.