Predicting the impact of physiological and biochemical processes on oral drug bioavailability

The corrected traditional equations for calculation of hepatic clearance that account for the difference in drug ionization in extracellular and intracellular tissue water and the corresponding corrected PBPK equation

The estimation of hepatic clearance, Clh, using in vitro data on metabolic stability of compound, its protein binding and blood–plasma equilibrium concentration ratio is commonly performed using well-stirred, parallel tube or dispersion models. It appears that for ionizable drugs there is a difference of the steady-state concentrations in extracelluar and intracellular water (at hepatocytes), where metabolism takes place. This occurs due to the different pH of extra- and intracellular water (7.4 and 7.0, respectively). The account of this fact leads to the novel equations for Clh . These equations include the additional parameter named ionization factor, FI, which is the ratio of the unionized drug fractions in plasma and intracellular tissue water (or the ratio of the unbound drug concentrations in intracellular tissue water and plasma at equilibrium). For neutral drugs FI = 1 and the novel equations coincide with the traditional ones. It is shown that the account of this factor may yield the calculated Clh up to 6.3-fold greater than that obtained by the traditional equations for the strong diprotic basic compounds, and up to 6.3-fold smaller for the strong diprotic acidic compounds. For triprotic acids and bases the difference could be as much as 15-fold. The account of pH difference between extra- and intracellular water also results in the change of the term commonly used to describe drug metabolic elimination rate in physiologically based pharmacokinetic (PBPK) equation. This consequently may lead to a noticeable change of drug concentration-time profiles in plasma and tissues. The effect of ionization factor is especially pronounced for the low-extraction ratio drugs. The examples of significant improvement in the prediction of hepatic clearance due to the account of ionization factor are provided. A more general equation for hepatic clearance, which accounts for ionization factor and possible drug uptake and efflux, is obtained.

Simulation of human intravenous and oral pharmacokinetics of 21 diverse compounds using physiologically based pharmacokinetic modelling

BACKGROUND

The importance of predicting human pharmacokinetics during compound selection has been recognized in the pharmaceutical industry. To this end there are many different approaches that are applied.

METHODS

In this study we compared the accuracy of physiologically based pharmacokinetic (PBPK) methodologies implemented in GastroPlus™ with the one-compartment approach routinely used at Pfizer for human pharmacokinetic plasma concentration-time profile prediction. Twenty-one Pfizer compounds were selected based on the availability of relevant preclinical and clinical data. Intravenous and oral human simulations were performed for each compound. To understand any mispredictions, simulations were also performed using the observed clearance (CL) value as input into the model.

RESULTS

The simulation results using PBPK were shown to be superior to those obtained via traditional one-compartment analyses. In many cases, this difference was statistically significant. Specifically, the results showed that the PBPK approach was able to accurately predict passive distribution and absorption processes. Some issues and limitations remain with respect to the prediction of CL and active transport processes and these need to be improved to further increase the utility of PBPK modelling. A particular advantage of the PBPK approach is its ability to accurately predict the multiphasic shape of the pharmacokinetic profiles for many of the compounds tested.

CONCLUSION

The results from this evaluation demonstrate the utility of PBPK methodology for the prediction of human pharmacokinetics. This methodology can be applied at different stages to enhance the understanding of the compounds in a particular chemical series, guide experiments, aid candidate selection and inform clinical trial design.

Preclinical and clinical pharmacokinetics of PF-02413873, a nonsteroidal progesterone receptor antagonist

The recently discovered selective nonsteroidal progesterone receptor (PR) antagonist 4-[3-cyclopropyl-1-(methylsulfonylmethyl)-5-methyl-1H-pyrazol-4-yl]oxy-2,6-dimethylbenzonitrile (PF-02413873) was characterized in metabolism studies in vitro, in preclinical pharmacokinetics in rat and dog, and in an initial pharmacokinetic study in human volunteers. Clearance (CL) of PF-02413873 was found to be high in rat (84 ml · min(-1) · kg(-1)) and low in dog (3.8 ml · min(-1) · kg(-1)), consistent with metabolic stability determined in liver microsomes and hepatocytes in these species. In human, CL was low in relation to hepatic blood flow, consistent with metabolic stability in human in vitro systems, where identified metabolites suggested predominant cytochrome P450 (P450)-catalyzed oxidative metabolism. Prediction of CL using intrinsic CL determined in human liver microsomes (HLM), recombinant human P450 enzymes, and single species scaling (SSS) from pharmacokinetic studies showed that dog SSS and HLM scaling provided the closest estimates of CL of PF-02413873 in human. These CL estimates were combined with a physiologically based pharmacokinetic (PBPK) model to predict pharmacokinetic profiles after oral suspension administration of PF-02413873 in fasted and fed states in human. Predicted plasma concentration versus time profiles were found to be similar to those observed in human over the PF-02413873 dose range 50 to 500 mg and captured the enhanced exposure in fed subjects. This case study of a novel nonsteroidal PR antagonist underlines the utility of PBPK modeling techniques in guiding prediction confidence and design of early clinical trials of novel chemical agents.

Physiologically-based pharmacokinetics in drug development and regulatory science

The application of physiologically-based pharmacokinetic (PBPK) modeling is coming of age in drug development and regulation, reflecting significant advances over the past 10 years in the predictability of key pharmacokinetic (PK) parameters from human in vitro data and in the availability of dedicated software platforms and associated databases. Specific advances and contemporary challenges with respect to predicting the processes of drug clearance, distribution, and absorption are reviewed, together with the ability to anticipate the quantitative extent of PK-based drug-drug interactions and the impact of age, genetics, disease, and formulation. The value of this capability in selecting and designing appropriate clinical studies, its implications for resource-sparing techniques, and a more holistic view of the application of PK across the preclinical/clinical divide are considered. Finally, some attention is given to the positioning of PBPK within the drug development and approval paradigm and its future application in truly personalized medicine.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 4: prediction of plasma concentration-time profiles in human from in vivo preclinical data by using the Wajima approach

The objective of this study was to evaluate the performance of the Wajima allometry (Css -MRT) approach published in the literature, which is used to predict the human plasma concentration-time profiles from a scaling of preclinical species data. A diverse and blinded dataset of 108 compounds from PhRMA member companies was used in this evaluation. The human intravenous (i.v.) and oral (p.o.) pharmacokinetics (PK) data were available for 18 and 107 drugs, respectively. Three different scenarios were adopted for prediction of human PK profiles. In the first scenario, human clearance (CL) and steady-state volume of distribution (Vss ) were predicted by unbound fraction corrected intercept method (FCIM) and Øie-Tozer (OT) approaches, respectively. Quantitative structure activity relationship (QSAR)-based approaches (TSrat-dog ) based on compound descriptors together with rat and dog data were utilized in the second scenario. Finally, in the third scenario, CL and Vss were predicted using the FCIM and Jansson approaches, respectively. For the prediction of oral pharmacokinetics, the human bioavailability and absorption rate constant were assumed as the average of preclinical species. Various statistical techniques were used for assessing the accuracy of the simulation scenarios. The human CL and Vss were predicted within a threefold error range for about 75% of the i.v. drugs. However, the accuracy in predicting key p.o. PK parameters appeared to be lower with only 58% of simulations falling within threefold of observed parameters. The overall ability of the Css -MRT approach to predict the curve shape of the profile was in general poor and ranged between low to medium level of confidence for most of the predictions based on the selected criteria.

Application of physiologically based pharmacokinetic modeling to understanding the clinical pharmacokinetics of UK-369,003

5-[2-Ethoxy-5-(4-ethyl-piperazine-1-sulfonyl)-pyridin-3-yl]-3-ethyl-2-(2-methoxy-ethyl)-2,6-dihydro-pyrazolo[4,3-d]pyrimidin-7-one (UK-369,003) is a phosphodiesterase-5 inhibitor in clinical development at Pfizer. UK-369,003 is predominantly metabolized by cytochrome P450 3A4 and is also a substrate for the efflux transporter P-glycoprotein. The pharmacokinetics of UK-369,003 has been profiled after oral administration of 1 to 800 mg of an immediate release formulation to healthy volunteers. Nonlinearity was observed in the systemic exposure at doses of 100 mg and greater. In addition, the pharmacokinetics of UK-369,003 has also been investigated after oral administration of the more therapeutically attractive modified release formulation. Systemic exposure was prolonged with the modified release formulation, but bioavailability was reduced in comparison with that of the immediate release formulation. Physiologically based pharmacokinetic modeling strategies are commonly used in drug discovery and development. This work describes application of the physiologically based pharmacokinetic software GastroPlus to understand the pharmacokinetics of UK-369,003. The impact of gut wall and hepatically mediated CYP3A4 metabolism, in addition to the actions of P-glycoprotein, in causing the nonlinear pharmacokinetics of the immediate release formulation and the reduced bioavailability of the modified release form, was investigated. The model accurately described the systemic exposure of UK-369,003 after intravenous and both immediate and modified release oral administration and suggested that CYP3A4 is responsible for the majority of the nonlinearity in systemic exposure observed after administration of the immediate release form. Conversely, the reduced bioavailability of the modified release formulation is believed to be caused by incomplete release from the device, incomplete absorption of released drug, and, to a lesser extent, CYP3A4 metabolism.

Knowledge-driven approaches for the guidance of first-in-children dosing

Pediatric pharmacokinetic and pediatric safety and efficacy studies are, in most cases, a mandatory activity during the drug development process in North America and Europe. Pharmacokinetic modeling in anticipation of the pediatric clinical trial should take a data or knowledge-driven approach by employing either top-down or bottom-up approaches to assessing differential age-related dosing. These two approaches depend on different starting information and are likely to be used in conjunction with each other for the purposes of defining pediatric dosing guidelines. This review primarily focuses on the available bottom-up, mechanistic models for predicting age-dependent drug absorption, distribution and elimination, and their integration through the whole-body physiologically based pharmacokinetic (PBPK) model. The bottom-up approach incorporating adult and pediatric whole-body PBPK models for optimizing age-related dosing is detailed for a drug currently undergoing pediatric development.

QSARs for PBPK modelling of environmental contaminants

Physiologically-based pharmacokinetic (PBPK) models are increasingly finding use in risk assessment applications of data-rich compounds. However, it is a challenge to determine the chemical-specific parameters for these models, particularly in time- and resource-limiting situations. In this regard, SARs, QSARs and QPPRs are potentially useful for computing the chemical-specific input parameters of PBPK models. Based on the frequency of occurrence of molecular fragments (CH(3), CH(2), CH, C, C=C, H, benzene ring and H in benzene ring structure) and exposure conditions, the available QSAR-PBPK models facilitate the simulation of tissue and blood concentrations for some inhaled volatile organic chemicals. The application domain of existing QSARs for developing PBPK models is limited, due to lack of relevant data for diverse chemicals and mechanisms. Even though this approach is conceptually applicable to non-volatile and high molecular weight organics as well, it is more challenging to predict the other PBPK model parameters required for modelling the kinetics of these chemicals (particularly tissue diffusion coefficients, association constants for binding and oral absorption rates). As the level of our understanding of the mechanistic basis of toxicokinetic processes improves, QSARs to provide a priori predictions of key chemical-specific PBPK parameters can be developed to expedite the internal dose-based health risk assessments in data-poor situations.

In vitro-in vivo correlation for gliclazide immediate-release tablets based on mechanistic absorption simulation

The aim of this study was to develop a drug-specific absorption model for gliclazide (GLK) using mechanistic gastrointestinal simulation technology (GIST) implemented in GastroPlus(TM) software package. A range of experimentally determined, in silico predicted or literature data were used as input parameters. Experimentally determined pH-solubility profile was used for all simulations. The human jejunum effective permeability (P (eff)) value was estimated on the basis of in vitro measured Caco-2 permeability (literature data). The required PK inputs were taken from the literature. The results of the simulations were compared with actual clinical data and revealed that the GIST-model gave accurate prediction of gliclazide oral absorption. The generated absorption model provided the target in vivo dissolution profile for in vitro-in vivo correlation and identification of biorelevant dissolution specification for GLK immediate-release (IR) tablets. A set of virtual in vitro data was used for correlation purposes. The obtained results suggest that dissolution specification of more than 85% GLK dissolved in 60 min may be considered as "biorelevant" dissolution acceptance criteria for GLK IR tablets.

On the accuracy of estimation of basic pharmacokinetic parameters by the traditional noncompartmental equations and the prediction of the steady-state volume of distribution in obese patients based upon data derived from normal subjects

The steady-state and terminal volumes of distribution, as well as the mean residence time of drug in the body (V(ss), V(β), and MRT) are the common pharmacokinetic parameters calculated using the drug plasma concentration-time profile C(p) (t) following intravenous (i.v. bolus or constant rate infusion) drug administration. These calculations are valid for the linear pharmacokinetic system with central elimination (i.e., elimination rate being proportional to drug concentration in plasma). Formally, the assumption of central elimination is not normally met because the rate of drug elimination is proportional to the unbound drug concentration at elimination site, although equilibration between systemic circulation and the site of clearance for majority of small molecule drugs is fast. Thus, the assumption of central elimination is practically quite adequate. It appears reasonable to estimate the extent of possible errors in determination of these pharmacokinetic parameters due to the absence of central elimination. The comparison of V(ss), V(β), and MRT calculated by exact equations and the commonly used ones was made considering a simplified physiologically based pharmacokinetic model. It was found that if the drug plasma concentration profile is detected accurately, determination of drug distribution volumes and MRT using the traditional noncompartmental calculations of these parameters from C(p) (t) yields the values very close to that obtained from exact equations. Though in practice, the accurate measurement of C(p) (t), especially its terminal phase, may not always be possible. This is particularly applicable for obtaining the distribution volumes of lipophilic compounds in obese subjects, when the possibility of late terminal phase at low drug concentration is quite likely, specifically for compounds with high clearance. An accurate determination of V(ss) is much needed in clinical practice because it is critical for the proper selection of drug treatment regimen. For that reason, we developed a convenient method for calculation of V(ss) in obese (or underweight) subjects. It is based on using the V(ss) values obtained from pharmacokinetic studies in normal subjects and the physicochemical properties of drug molecule. A simple criterion that determines either the increase or decrease of V(ss) (per unit body weight) due to obesity is obtained. The accurate determination of adipose tissue-plasma partition coefficient is crucial for the practical application of suggested method.

Utility of physiologically based absorption modeling in implementing Quality by Design in drug development

To implement Quality by Design (QbD) in drug development, scientists need tools that link drug products properties to in vivo performance. Physiologically based absorption models are potentially useful tools; yet, their utility of QbD implementation has not been discussed or explored much in the literature. We simulated pharmacokinetics (PK) of carbamazepine (CBZ) after administration of four oral formulations, immediate-release (IR) suspension, IR tablet, extended-release (XR) tablet and capsule, under fasted and fed conditions and presented a general diagram of a modeling and simulation strategy integrated with pharmaceutical development. We obtained PK parameters and absorption scale factors (ASFs) by deconvolution of the PK data for IR suspension under fasted condition. The model was validated for other PK profiles of IR formulations and used to predict PK for XR formulations. We explored three key areas where a modeling and simulation approach impacts QbD. First, the model was used to help identify optimal in vitro dissolution conditions for XR formulations. Second, identification of critical formulations variables was illustrated by a parameter sensitivity analysis of mean particle radius for the IR tablet that showed a PK shift with decreased particle radius, C (max) was increased and T (max) was decreased. Finally, virtual trial simulations allowed incorporation of inter-subject variability in the model. Virtual bioequivalence studies performed for two test formulations suggested that an in vitro dissolution test may be a more sensitive discriminative method than in vivo PK studies. In summary, a well-validated predictive model is a potentially useful tool for QbD implementation in drug development.

Physiologically based predictions of the impact of inhibition of intestinal and hepatic metabolism on human pharmacokinetics of CYP3A substrates

The first objective of the present study was to predict the pharmacokinetics of selected CYP3A substrates administered at a single oral dose to human. The second objective was to predict pharmacokinetics of the selected drugs in presence of inhibitors of the intestinal and/or hepatic CYP3A activity. We developed a whole-body physiologically based pharmacokinetics (WB-PBPK) model accounting for presystemic elimination of midazolam (MDZ), alprazolam (APZ), triazolam (TRZ), and simvastatin (SMV). The model also accounted for concomitant administration of the above-mentioned drugs with CYP3A inhibitors, namely ketoconazole (KTZ), itraconazole (ITZ), diltiazem (DTZ), saquinavir (SQV), and a furanocoumarin contained in grape-fruit juice (GFJ), namely 6',7'-dihydroxybergamottin (DHB). Model predictions were compared to published clinical data. An uncertainty analysis was performed to account for the variability and uncertainty of model parameters when predicting the model outcomes. We also briefly report on the results of our efforts to develop a global sensitivity analysis and its application to the current WB-PBPK model. Considering the current criterion for a successful prediction, judged satisfied once the clinical data are captured within the 5th and 95th percentiles of the predicted concentration-time profiles, a successful prediction has been obtained for a single oral administration of MDZ and SMV. For APZ and TRZ, however, a slight deviation toward the 95th percentile was observed especially for C(max) but, overall, the in vivo profiles were well captured by the PBPK model. Moreover, the impact of DHB-mediated inhibition on the extent of intestinal pre-systemic elimination of MDZ and SMV has been accurately predicted by the proposed PBPK model. For concomitant administrations of MDZ and ITZ, APZ and KTZ, as well as SMV and DTZ, the in vivo concentration-time profiles were accurately captured by the model. A slight deviation was observed for SMV when coadministered with ITZ, whereas more important deviations have been obtained between the model predictions and in vivo concentration-time profiles of MDZ coadministered with SQV. The same observation was made for TRZ when administered with KTZ. Most of the pharmacokinetic parameters predicted by the PBPK model were successfully predicted within a two-fold error range either in the absence or presence of metabolism-based inhibition. Overall, the present study demonstrated the ability of the PBPK model to predict DDI of CYP3A substrates with promising accuracy.

Influence of molecular properties on oral bioavailability of lipophilic drugs - mapping of bulkiness and different measures of polarity

The biopharmaceutical assessment of new drug candidates based on their chemical structure is important in drug discovery and development. The scope of this study is to focus on lipophilic drugs and to clarify the role of their chemical predictors on oral bioavailability in humans. First their chemical properties were calculated from molecular modeling and the bioavailability data was obtained from the literature. The data was then analyzed by a partial least square method including non-linear terms. Significant coefficients were identified from a group of polarity- and solubility-related properties. Contour plots were constructed mapping molecular weight together with different polarity factors. Depending on the molecular weight a maximal bioavailability was found at solubility parameters of about 31-35 (J/cm(3))(1/2) and HLB values of roughly 4-12. The mapping of lipophilic drugs also revealed that a solubility parameter of less than 20 (J/cm(3))(1/2) or a HLB of smaller than unity is critical for the drug-likeness of new compounds.

Effects of experimental setup on the apparent concentration dependency of active efflux transport in in vitro cell permeation experiments

P-Glycoprotein mediated efflux is one of the barriers limiting drug absorption from the intestine. Predictions of the intestinal P-glycoprotein function need to take into account the concentration dependency because high intestinal drug concentrations may saturate P-glycoprotein. However, the substrate binding site of P-glycoprotein lies inside the cells and the drug concentration at the binding site cannot be measured directly. Therefore, rigorous determination of concentration dependent P-glycoprotein kinetics is challenging. In this study, the effects of the aqueous boundary layers, extracellular pH and cellular retention on the apparent saturation kinetics of P-glycoprotein mediated transport of quinidine in an in vitro cell permeation setting were explored. The changes in the experimental conditions caused 1 order of magnitude variation in the apparent affinity to P-glycoprotein (K(m,app)) and a 5-fold difference in the maximum effective P-glycoprotein mediated transport rate of quinidine (V(max,app)). However, fitting the concentration data into a compartmental model which accounted for the aqueous boundary layers, cell membranes and cellular retention suggested that the P-glycoprotein function per se was not altered, it was the differences in the passive transfer of quinidine which changed the apparent transport kinetics. These results provide further insight into the dynamics of the P-glycoprotein mediated transport and on the roles of several confounding factors involved in in vitro experimental setting. Further, the results confirm the applicability of compartmental model based data analysis approach in the determination of active transporter kinetics.

The use of biopharmaceutic classification of drugs in drug discovery and development: current status and future extension

Bioavailability (BA) and bioequivalence (BE) play a central role in pharmaceutical product development and BE studies are presently being conducted for New Drug Applications (NDAs) of new compounds, in supplementary NDAs for new medical indications and product line extensions, in Abbreviated New Drug Applications (ANDAs) of generic products and in applications for scale-up and post-approval changes. The Biopharmaceutics Classification System (BCS) has been developed to provide a scientific approach for classifying drug compounds based on solubility as related to dose and intestinal permeability in combination with the dissolution properties of the oral immediate-release (IR) dosage form. The aim of the BCS is to provide a regulatory tool for replacing certain BE studies by accurate in-vitro dissolution tests. The aim of this review is to present the status of the BCS and discuss its future application in pharmaceutical product development. The future application of the BCS is most likely increasingly important when the present framework gains increased recognition, which will probably be the case if the BCS borders for certain class II and III drugs are extended. The future revision of the BCS guidelines by the regulatory agencies in communication with academic and industrial scientists is exciting and will hopefully result in an increased applicability in drug development. Finally, we emphasize the great use of the BCS as a simple tool in early drug development to determine the rate-limiting step in the oral absorption process, which has facilitated the information between different experts involved in the overall drug development process. This increased awareness of a proper biopharmaceutical characterization of new drugs may in the future result in drug molecules with a sufficiently high permeability, solubility and dissolution rate, and that will automatically increase the importance of the BCS as a regulatory tool over time.

Preparation and evaluation of self-microemulsifying drug delivery systems (SMEDDS) containing atorvastatin

Atorvastatin is insoluble in aqueous solution and the bioavailability after oral administration is low. Self-microemulsifying drug delivery systems (SMEDDS) containing atorvastatin have been successfully prepared to improve its bioavailability. SMEDDS is a mixture of lipid, surfactant, and cosurfactant, which are emulsified in aqueous medium under gentle digestive motility in the gastrointestinal tract. Pseudo-ternary phase diagrams composed of various excipients were plotted. Droplet size, zeta-potential and long-term physical stability of the formulations were investigated. The release of atorvastatin from SMEDDS capsules was studied using the dialysis bag method in 0.1 m HCl and phosphate buffer (pH 7.4), compared with the release of atorvastatin from a conventional tablet. A pharmacokinetic study was performed in 6 beagle dogs after oral administration of 6 mg kg−1 atorvastatin. The bioavailability of atorvastatin SMEDDS capsules was significantly increased compared with that of the conventional tablet. SMEDDS capsules consisting of Labrafil, propylene glycol and Cremophor RH40 provided the greatest bioavailability. Our studies indicate that the use of SMEDDS for the delivery of atorvastatin can improve its bioavailability.

Physiologically based pharmacokinetics (PBPK)

Allometric scaling is widely used to predict human pharmacokinetic parameters from preclinical species, and many different approaches have been proposed over the years to improve its predictive performance. Nevertheless, prediction errors are commonly observed in the practical application of simple allometry, for example, in cases where the hepatic metabolic clearance is mainly determined by enzyme activities, which do not scale allometrically across species. Therefore, if good correlation was noted for some drugs, poor correlation was observed for others, highlighting the need for other conceptual approaches. Physiologically based pharmacokinetic (PBPK) models are now a well-established approach to conduct extrapolations across species and to generate simulations of pharmacokinetic profiles under various physiological conditions. While conventional pharmacokinetic models are defined by drug-related data themselves, PBPK models have richer information content and integrate information from various sources, including drug-dependent, physiological, and biological parameters as they vary in between species, subjects, or with age and disease state. Therefore, the biological and mechanistic bases of PBPK models allow the extrapolation of the kinetic behavior of drugs with regard to dose, route, and species. In addition, by providing a link between tissue concentrations and toxicological or pharmacological effects, PBPK modeling represents a framework for mechanistic pharmacokinetic-pharmacodynamic models.

Practical anticipation of human efficacious doses and pharmacokinetics using in vitro and preclinical in vivo data

Accurate predictions of human pharmacokinetic and pharmacodynamic (PK/PD) profiles are critical in early drug development, as safe, efficacious, and "developable" dosing regimens of promising compounds have to be identified. While advantages of successful integration of preclinical PK/PD data in the "anticipation" of human doses (AHD) have been recognized, pharmaceutical scientists have faced difficulties with practical implementation, especially for PK/PD profile projections of compounds with challenging absorption, distribution, metabolism, excretion and formulation properties. In this article, practical projection approaches for formulation-dependent human PK/PD parameters and profiles of Biopharmaceutics Classification System classes I-IV drugs based on preclinical data are described. Case examples for "AHD" demonstrate the utility of preclinical and clinical PK/PD modeling for formulation risk identification, lead candidate differentiation, and prediction of clinical outcome. The application of allometric scaling methods and physiologically based pharmacokinetic approaches for clearance or volume of distribution projections is described using GastroPlus. Methods to enhance prediction confidence such as in vitro-in vivo extrapolations in clearance predictions using in vitro microsomal data are discussed. Examples for integration of clinical PK/PD and formulation data from frontrunner compounds via "reverse pharmacology strategies" that minimize uncertainty with PK/PD predictions are included. The use of integrated softwares such as GastroPlus in combination with established PK projection methods allow the projection of formulation-dependent preclinical and human PK/PD profiles required for compound differentiation and development risk assessments.

An investigation into the importance of "very rapid dissolution" criteria for drug bioequivalence demonstration using gastrointestinal simulation technology

The Biopharmaceutics Classification System (BCS) is based on the mechanistic assumptions that the rate and extent of oral drug absorption are governed by drug solubility, intestinal permeability, and dissolution rate from the dosage form administered. One of the goals of BCS is to identify classes of drugs for which bioequivalence may be established based solely on the in vitro dissolution data, i.e., which would be eligible for biowaiver. On the basis of BCS, currently, the biowaiver concept is adopted and recommended for immediate release of drug products containing highly soluble and highly permeable compounds (BCS class 1 drugs). Dissolution testing properties are proposed to be more stringent: very rapid dissolution is demanded when generic drug application is submitted with the exemption of in vivo bioequivalence study. In the present paper, Gastrointestinal Simulation Technology has been applied in order to evaluate the potential for different in vitro drug dissolution kinetics to influence dosage forms in vivo behavior and the relevance of "very rapid dissolution" criteria to be met (i.e., more than 85% of dose dissolved in 15 min).

Simulations of the nonlinear dose dependence for substrates of influx and efflux transporters in the human intestine

The purpose of this study was to develop simulation and modeling methods for the evaluation of pharmacokinetics when intestinal influx and efflux transporters are involved in gastrointestinal absorption. The advanced compartmental absorption and transit (ACAT) model as part of the computer program GastroPlus was used to simulate the absorption and pharmacokinetics of valacyclovir, gabapentin, and talinolol. Each of these drugs is a substrate for an influx or efflux transporter and all show nonlinear dose dependence within the normal therapeutic range. These simulations incorporated the experimentally derived gastrointestinal distributions of transporter expression levels for oligopeptide transporters PepT1 and HPT1 (valacyclovir); System L-amino acid transporter LAT2 and organic cation transporter OCTN1 (gabapentin); and organic anion transporter (OATP1A2) and P-glycoprotein (talinolol). By assuming a uniform distribution of oligopeptide transporter and by application of the in vitro K(m) value for valacyclovir, the simulations accurately reproduced the experimental nonlinear dose dependence. For gabapentin, LAT2 distribution produced simulation results that were much more accurate than OCTN1 distributions. For talinolol, an influx transporter distribution for OATP1A2 and the efflux transporter P-glycoprotein distributed with increasing expression in the distal small intestine produced the best results. The physiological characteristics of the small and large intestines used in the ACAT model were able to accurately account for the positional and temporal changes in concentration and carrier-mediated transport of the three drugs included in this study. The ACAT model reproduced the nonlinear dose dependence for each of these drugs.

Prediction of modified release pharmacokinetics and pharmacodynamics from in vitro, immediate release, and intravenous data

The aim of this study was to demonstrate the value of mechanistic simulations in gaining insight into the behaviors of modified release (MR) formulations in vivo and to use the properly calibrated models for prediction of pharmacokinetics (PK) and pharmacodynamics (PD). GastroPlus (Simulations Plus, Inc.) was used to fit mechanistic models for adinazolam and metoprolol that describe the absorption, PK, and PD after intravenous (i.v.) and immediate release (IR) oral (p.o.) administration. The fitted model for adinazolam was then used to predict the PD profile for a MR formulation and to design a new formulation with desired onset and duration of action. The fitted metoprolol model was used to gain insight and to explain the in vivo behaviors of MR formulations. For each drug, a single absorption/PK model was fitted that provided simulated plasma concentration-time profiles closely matching observed in vivo profiles across several different i.v. and p.o doses. Sedation score profiles of adinazolam were fitted with an indirect PD model. For metoprolol, the fitted absorption/PK model for IR p.o. doses was used to select in vitro dissolution conditions that best matched the in vivo release of MR doses. This model also explained differences in exposure after administration of MR formulations with different release rates. Mechanistic absorption/PK models allow for detailed descriptions of all processes affecting the two drugs' bioavailability, including release/dissolution, absorption, and intestinal and hepatic first pass extraction. The insights gained can be used to design formulations that more effectively overcome identified problems.

Mechanistic approaches to predicting oral drug absorption

Modeling and simulation of oral drug absorption have been widely used in drug discovery, development, and regulation. Predictive absorption models are used to determine the rate and extent of oral drug absorption, facilitate lead drug candidate selection, establish formulation development strategy, and support the development of regulatory policies. This review highlights the development of recent drug absorption models including dispersion and compartmental models. The compartmental models include the compartmental absorption and transit model; Grass model; gastrointestinal transit absorption model; advanced compartmental absorption and transit model; and advanced dissolution, absorption, and metabolism model. Compared to the early absorption models, the above models developed or extended since the mid-1990s have demonstrated greatly improved predictive performance by accounting for multiple factors such as drug degradation, gastric emptying, intestinal transit, first-pass metabolism, and intestinal transport. For future model development, more heterogeneous features of the gastrointestinal tract (villous blood flow, metabolizing enzymes, and transporters), food effects, and drug-drug interactions should be fully characterized and taken into consideration. Moreover, predicting population inter- and intravariability in oral drug absorption can be useful and important for the evaluation of clinical safety and efficacy of drugs. Establishing databases and libraries that contain accurate pharmaceutical and pharmacokinetic information for commercialized and uncommercialized drugs may also be helpful for model development and validation.

Population-based mechanistic prediction of oral drug absorption

The bioavailability of drugs from oral formulations is influenced by many physiological factors including gastrointestinal fluid composition, pH and dynamics, transit and motility, and metabolism and transport, each of which may vary with age, gender, race, food, and disease. Therefore, oral bioavailability, particularly of poorly soluble and/or poorly permeable compounds and those that are extensively metabolized, often exhibits a high degree of inter- and intra-individual variability. While several models and algorithms have been developed to predict bioavailability in an average person, efforts to accommodate intrinsic variability in the component processes are less common. An approach that incorporates such variability for human populations within a mechanistic framework is described together with examples of its application to drug and formulation development.

Toward an increased understanding of the barriers to colonic drug absorption in humans: implications for early controlled release candidate assessment

The purpose of this study was to increase the understanding of in vivo colonic drug absorption in humans by summarizing and evaluating all regional in vivo human absorption data with focus on the interpretation of the colonic absorption data in relation to intestinal permeability and solubility. In addition, the usefulness of the Biopharmaceutics Classification System (BCS) in early assessment of the in vivo colonic absorption potential of controlled release drug candidates was investigated. Clinical regional absorption data (Cmax, Tmax, and AUC) of 42 drugs were collected from journal articles, abstracts, and internal reports, and the relative bioavailability in the colon (Frel(colon)) was obtained directly or calculated. Bioavailability, fraction dose absorbed, and information if the compounds were substrates for P-glycoprotein (P-gp) or cytochrome P450 3A (CYP3A) were also obtained. The BCS I drugs were well absorbed in the colon (Frel(colon) > 70%), although some drugs had lower values due to bacterial degradation in the colon. The low permeability drugs (BCS III/IV) had a lower degree of absorption in the colon (Frel(colon) < 50%). There was a clear correlation between in vitro Caco-2 permeability and Frel(colon), and atenolol and metoprolol may function as permeability markers for low and high colonic absorption, respectively. No obvious effect of P-gp on the colonic absorption of the drugs in this study was detected. There was insufficient data available to fully assess the impact of low solubility and slow dissolution rate. The estimated in vivo fractions dissolved of the only two compounds administered to the colon as both a solution and as solid particles were 55% and 92%, respectively. In conclusion, permeability and solubility are important barriers to colonic absorption in humans, and in vitro testing of these properties is recommended in early assessment of colonic absorption potential.

Modelling and PBPK simulation in drug discovery

Physiologically based pharmacokinetic (PBPK) models are composed of a series of differential equations and have been implemented in a number of commercial software packages. These models require species-specific and compound-specific input parameters and allow for the prediction of plasma and tissue concentration time profiles after intravenous and oral administration of compounds to animals and humans. PBPK models allow the early integration of a wide variety of preclinical data into a mechanistic quantitative framework. Use of PBPK models allows the experimenter to gain insights into the properties of a compound, helps to guide experimental efforts at the early stages of drug discovery, and enables the prediction of human plasma concentration time profiles with minimal (and in some cases no) animal data. In this review, the application and limitations of PBPK techniques in drug discovery are discussed. Specific reference is made to its utility (1) at the lead development stage for the prioritization of compounds for animal PK studies and (2) at the clinical candidate selection and "first in human" stages for the prediction of human PK.

Predicting pharmacokinetics of drugs using physiologically based modeling--application to food effects

Our knowledge of the major mechanisms underlying the effect of food on drug absorption allows reliable qualitative prediction based on biopharmaceutical properties, which can be assessed during the pre-clinical phase of drug discovery. Furthermore, several recent examples have shown that physiologically based absorption models incorporating biorelevant drug solubility measurements can provide quite accurate quantitative prediction of food effect. However, many molecules currently in development have distinctly sub-optimal biopharmaceutical properties, making the quantitative prediction of food effect for different formulations from in vitro data very challenging. If such drugs reach clinical development and show undesirable variability when dosed with food, improved formulation can help to reduce the food effect and carefully designed in vivo studies in dogs can be a useful guide to clinical formulation development. Even so, such in vivo studies provide limited throughput for screening, and food effects seen in dog cannot always be directly translated to human. This paper describes how physiologically based absorption modeling can play a role in the prediction of food effect by integrating the data generated during pre-clinical and clinical research and development. Such data include physicochemical and in vitro drug properties, biorelevant solubility and dissolution, and in vivo pre-clinical and clinical pharmacokinetic data. Some background to current physiological absorption models of human and dog is given, and refinements to models of in vivo drug solubility and dissolution are described. These are illustrated with examples using GastroPlus to simulate the food effect in dog and human for different formulations of two marketed drugs.

Potential role of intestinal first-pass metabolism in the prediction of drug-drug interactions

BACKGROUND

The contribution of intestine to the magnitude of drug-drug interactions (DDI) may be significant, considering high levels of inhibitors in the gut lumen achieved during absorption and the abundance of metabolic enzymes in the mature enterocytes. Intestinal inhibition is incorporated in the DDI prediction models as the ratio of the intestinal wall availability in the presence and absence of the inhibitor (F(G)(') and F(G), respectively).

OBJECTIVE

This review will focus on the ability of the current approaches to estimate the extent of intestinal DDI accurately, addressing predominantly the most abundant intestinal P450 enzyme, CYP3A4.

METHODS

Considering the sensitivity of the DDI prediction models to the accuracy of the F(G) estimates, the current study focuses on 3 different in vitro and in vivo approaches to assess this parameter.

RESULTS/CONCLUSION

The advantages and limitations of each of F(G) methods are outlined. Accurate assessment of this parameter is essential for the prediction of human drug clearance and drug-drug interaction potential.