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

SIMDOT-AbMe: microphysiologically based simulation tool for quantitative prediction of systemic and local bioavailability of targeted oral delivery formulations

The purpose of this study was to develop a physiologically based simulation tool that is able to predict local as well as systemic bioavailability of 5-aminosalicylic acid (5-ASA)-targeted delivery formulations using the existing understanding of the transport and metabolism mechanisms of 5-ASA. The model accounts for active and passive transcellular transport (absorptive and efflux), passive paracellular transport, intestinal biotransformation, and systemic metabolism and clearance. The intestinal physiology was represented by transverse segments for ileum and proximal colon and longitudinal compartments for the microphysiology of the intestinal tissue. The tool, equipped with an optimization routine that enables tuning model parameters, was developed in Matlab and uses a user-friendly graphical interface for data input and output. Physiologic and kinetic model parameters were estimated either from literature monolayer transport studies using nonlinear curve fitting or obtained directly from the literature. 5-ASA clinical pharmacokinetic profiles of a once-daily (one 4-g/day dose) and twice-daily (two 2-g/day doses) dosing regimen were used to partially calibrate and validate the model, respectively. Simulation results showed that drug C(max) in the gut mucosal layers reached a higher level and was achieved sooner than in the systemic blood level. The computed relative local bioavailability with respect to the systemic bioavailability was 0.063. With use of the model, the relative local bioavailability of different formulations can be established for fast performance verification of new preparations based on measured systemic bioavailability. These types of models play a critical role in designing such preparations and rapidly assessing their effectiveness and will foster efficient experimental designs, saving time and resources.

Understanding the effect of API properties on bioavailability through absorption modeling

Selection of API phase is one of the first decision points in the formulation development process. Subsequent to phase selection, the focus shifts to the API physical properties such as particle size. Oftentimes, such properties are closely monitored throughout the drug development, as they can have a direct impact on the formulation bioperformance. The purpose of this mini-review was to describe the potential for application of absorption modeling in understanding the effect of API properties on bioavailability. Examples are provided to demonstrate how absorption modeling can be applied both early on to set the formulation strategy as well as during the development process to help with setting of specifications around the API. Limitations of the existing models and areas of possible expansion of such tools are also discussed.

Whole body physiologically-based pharmacokinetic models: their use in clinical drug development

BACKGROUND

Whole-body physiologically-based pharmacokinetic (WB-PBPK) models mathematically describe an organism as a closed circulatory system consisting of compartments that represent the organs important for compound absorption, distribution, metabolism and elimination.

OBJECTIVES

To review the current state of WB-PBPK model use in the clinical phases of drug development.

METHODS

A qualitative description of the WB-PBPK model structure is included along with a review of the varying methods available for input parameterisation. Current and potential WB-PBPK model application in clinical development is discussed.

CONCLUSIONS

This modelling tool is at present used for small and large molecule drug development primarily as a means to scale pharmacokinetics from animals to humans based on physiology. The pharmaceutical industry is active in employing these models to clinical drug development although the applications in use now are narrow in comparison to the potential. Expanded integration of WB-PBPK models into the drug development process will only be achieved with staff training, managerial will, success stories and regulatory agency openness.

Drug absorption modeling as a tool to define the strategy in clinical formulation development

The purpose of this mini review is to discuss the use of physiologically-based drug absorption modeling to guide the formulation development. Following an introduction to drug absorption modeling, this article focuses on the preclinical formulation development. Case studies are presented, where the emphasis is not only the prediction of absolute exposure values, but also their change with altered input values. Sensitivity analysis of technologically relevant parameters, like the drug's particle size, dose and solubility, is presented as the basis to define the clinical formulation strategy. Taking the concept even one step further, the article shows how the entire design space for drug absorption can be constructed. This most accurate prediction level is mainly foreseen once clinical data is available and an example is provided using mefenamic acid as a model drug. Physiologically-based modeling is expected to be more often used by formulators in the future. It has the potential to become an indispensable tool to guide the formulation development of challenging drugs, which will help minimize both risks and costs of formulation development.

Clinical relevance of dissolution testing in quality by design

Quality by design (QbD) has recently been introduced in pharmaceutical product development in a regulatory context and the process of implementing such concepts in the drug approval process is presently on-going. This has the potential to allow for a more flexible regulatory approach based on understanding and optimisation of how design of a product and its manufacturing process may affect product quality. Thus, adding restrictions to manufacturing beyond what can be motivated by clinical quality brings no benefits but only additional costs. This leads to a challenge for biopharmaceutical scientists to link clinical product performance to critical manufacturing attributes. In vitro dissolution testing is clearly a key tool for this purpose and the present bioequivalence guidelines and biopharmaceutical classification system (BCS) provides a platform for regulatory applications of in vitro dissolution as a marker for consistency in clinical outcomes. However, the application of these concepts might need to be further developed in the context of QbD to take advantage of the higher level of understanding that is implied and displayed in regulatory documentation utilising QbD concepts. Aspects that should be considered include identification of rate limiting steps in the absorption process that can be linked to pharmacokinetic variables and used for prediction of bioavailability variables, in vivo relevance of in vitro dissolution test conditions and performance/interpretation of specific bioavailability studies on critical formulation/process variables. This article will give some examples and suggestions how clinical relevance of dissolution testing can be achieved in the context of QbD derived from a specific case study for a BCS II compound.

Applications of physiologically based absorption models in drug discovery and development

This article describes the use of physiologically based models of intestinal drug absorption to guide the research and development of new drugs. Applications range from lead optimization in the drug discovery phase through clinical candidate selection and extrapolation to human to phase 2 formulation development. Early simulations in preclinical species integrate multiple screening data and add value by transforming these individual properties into a prediction of in vivo absorption. Comparison of simulations to plasma levels measured after oral dosing in animals highlights unexpected behavior, and parameter sensitivity analysis can explore the impact of uncertainties in key properties, point toward factors which are limiting absorption and contribute to assessment of compound developability. Physiological models provide reliable prediction of human absorption and with refinement based on phase 1 data are useful guides to further market formulation development. Improvements in the accuracy of simulations are expected as better in vitro methods generate more in vivo relevant solubility and permeability data, and modeling will play a central role in the development of more predictive methods for transporter-related effects on drug absorption.

Application of gastrointestinal simulation for extensions for biowaivers of highly permeable compounds

The goal of this study was to apply gastrointestinal simulation technology and integration of physiological parameters to predict biopharmaceutical drug classification. GastroPlus was used with experimentally determined physicochemical and pharmacokinetic drug properties to simulate the absorption of several weak acid and weak base BCS class II compounds. Simulation of oral drug absorption given physicochemical drug properties and physicochemical parameters will aid justification of biowaivers for selected BCS class II compounds.

Physical and biological considerations for the use of nonaqueous solvents in oral bioavailability enhancement

This review addresses the use of nonaqueous solvents as components of oral formulations in discovery and preclinical studies. Pharmacology, pharmacokinetic, and safety studies are frequently conducted with solution formulations that use a solvent to solubilize poorly aqueous soluble drugs. The physical chemical basis for solubilization and the precipitation of solubilized drug following administration both contribute to the utility of nonaqueous solvent solutions as oral vehicles. While many of these solvents are considered nontoxic, they are not completely inert biologically. The effects of common nonaqueous solvents on the structural integrity of the epithelia, the inherent permeability of and flux across the GI membrane, the activity of efflux and metabolic enzymes, and the effects on GI motility and GI transit times will be described through an examination of available literature. The practical relevance of these factors to the development of early formulations will be examined critically and suggestions made for the suitability of nonaqueous solvents for a variety of purposes.

Use of plasma proteins as solubilizing agents in in vitro permeability experiments: Correction for unbound drug concentration using the reciprocal permeability approach

The purpose of the present study was to explore the applicability of the reciprocal permeability approach to correct for changes in thermodynamic activity when in vitro permeability data are generated in the presence of plasma proteins. Diazepam (DIA), digoxin (DIG), and propranolol (PRO) permeability was assessed in the presence of bovine serum albumin (BSA) and bovine alpha-1-acid glycoprotein (AAG). The reciprocal permeability approach was subsequently employed to calculate the true permeability coefficient (Papp(corr)) and the operational protein association constant (nK(a)). For BSA binding, good agreement was observed between the Papp(corr) values and Papp values obtained in the absence of protein. For PRO and AAG, where binding affinity was high, deviation in the reciprocal permeability plots was evident suggesting ligand depletion at low drug/high protein concentrations. Bidirectional DIG permeability data in the presence of either BSA or AAG indicated that neither protein had an effect on the efflux transporters involved in DIG permeability. The data suggest that plasma proteins can be utilized in permeability experiments with no adverse effects on transporter function and that the reciprocal permeability approach can be used to correct permeability data for changes in unbound drug concentration.

Early identification of drug-induced impairment of gastric emptying through physiologically based pharmacokinetic (PBPK) simulation of plasma concentration-time profiles in rat

Inhibition of gastric emptying rate can have adverse effects on the absorption of food and nutrients. The absorption phase of the plasma concentration-time profile of a compound administered orally to pre-clinical species reflects among others, the gastric and intestinal transit kinetics, and can thus assist in the early identification of delayed gastric emptying. The purpose of this article is to demonstrate the value of Physiologically Based Pharmacokinetic (PBPK) modelling in the early identification of drug induced impairment of gastric emptying from pharmacokinetic profiles. To our knowledge, this is first time that the value of a generic PBPK model for hypothesis testing has been demonstrated with examples. A PBPK model built in-house using MATLAB package and incorporating absorption, metabolism, distribution, biliary and renal elimination models has been employed for the simulation of concentration-time profiles. PBPK simulations of a few compounds that are currently in drug discovery projects show that the observed initial absorption phase of their concentration-time profiles in rat were consistent with reduced gastric emptying rates. The slow uptake of these compounds into the systemic circulation is reflected in their pharmacokinetic profiles but it is not obvious until PBPK simulations are done. Delayed gastric emptying rates of these compounds in rats were also independently observed in x-ray imaging. PBPK simulations can provide early alerts to drug discovery projects, besides aiding the understanding of complex mechanisms that determine the lineshapes of pharmacokinetic profiles. The application of PBPK simulations in the early detection of gastric emptying problems with existing data and without the need to resort to additional animal studies, is appealing both from an economic and ethical standpoint.

Prediction of human pharmacokinetics--gastrointestinal absorption

Permeability (P(e)) and solubility/dissolution are two major determinants of gastrointestinal (GI) drug absorption. Good prediction of these is crucial for predicting doses, exposures and potential interactions, and for selecting appropriate candidate drugs. The main objective was to evaluate screening methods for prediction of GI P(e), solubility/dissolution and fraction absorbed (f(a)) in humans. The most accurate P(e) models for prediction of f(a) of passively transported and highly soluble compounds appear to be the 2/4/A1 rat small intestinal cell model (in-vitro and in-silico), a newly developed artificial-membrane method, and a semi-empirical approach based on in-vitro membrane affinity to immobilized lipid bilayers, effective molecular weight and physiological GI variables. The predictability of in-vitro Caco-2, in-situ perfusion and other artificial membrane methods seems comparably low. The P(e) and f(a) in humans for compounds that undergo mainly active transport were predicted poorly by all models investigated. However, the rat in-situ perfusion model appears useful for prediction of active uptake potential (complete active uptake is generally well predicted), and Caco-2 cells are useful for studying bidirectional active transport, respectively. Human intestinal in-vitro P(e), which correlates well with f(a) for passively transported compounds, could possibly also have potential to improve/enable predictions of f(a) for actively transported substances. Molecular descriptor data could give an indication of the passive absorption potential. The 'maximum absorbable dose' and 'dose number' approaches, and solubility/dissolution data obtained in aqueous media, appear to underestimate in-vivo dissolution to a considerable extent. Predictions of in-vivo dissolution should preferably be done from in-vitro dissolution data obtained using either real or validated simulated GI fluids.

Implementation of a transit compartment model for describing drug absorption in pharmacokinetic studies

PURPOSE

To compare the performance of the standard lag time model (LAG model) with the performance of an analytical solution of the transit compartment model (TRANSIT model) in the evaluation of four pharmacokinetic studies with four different compounds.

METHODS

The population pharmacokinetic analyses were performed using NONMEM on concentration-time data of glibenclamide, furosemide, amiloride, and moxonidine. In the TRANSIT model, the optimal number of transit compartments was estimated from the data. This was based on an analytical solution for the change in drug concentration arising from a series of transit compartments with the same first-order transfer rate between each compartment. Goodness-of-fit was assessed by the decrease in objective function value (OFV) and by inspection of diagnostic graphs.

RESULTS

With the TRANSIT model, the OFV was significantly lower and the goodness-of-fit was markedly improved in the absorption phase compared with the LAG model for all drugs. The parameter estimates related to the absorption differed between the two models while the estimates of the pharmacokinetic disposition parameters were similar.

CONCLUSION

Based on these results, the TRANSIT model is an attractive alternative for modeling drug absorption delay, especially when a LAG model poorly describes the drug absorption phase or is numerically unstable.

Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs

The aim of this study was to evaluate different physiologically based modeling strategies for the prediction of human pharmacokinetics. Plasma profiles after intravenous and oral dosing were simulated for 26 clinically tested drugs. Two mechanism-based predictions of human tissue-to-plasma partitioning (P(tp)) from physicochemical input (method Vd1) were evaluated for their ability to describe human volume of distribution at steady state (V(ss)). This method was compared with a strategy that combined predicted and experimentally determined in vivo rat P(tp) data (method Vd2). Best V(ss) predictions were obtained using method Vd2, providing that rat P(tp) input was corrected for interspecies differences in plasma protein binding (84% within 2-fold). V(ss) predictions from physicochemical input alone were poor (32% within 2-fold). Total body clearance (CL) was predicted as the sum of scaled rat renal clearance and hepatic clearance projected from in vitro metabolism data. Best CL predictions were obtained by disregarding both blood and microsomal or hepatocyte binding (method CL2, 74% within 2-fold), whereas strong bias was seen using both blood and microsomal or hepatocyte binding (method CL1, 53% within 2-fold). The physiologically based pharmacokinetics (PBPK) model, which combined methods Vd2 and CL2 yielded the most accurate predictions of in vivo terminal half-life (69% within 2-fold). The Gastroplus advanced compartmental absorption and transit model was used to construct an absorption-disposition model and provided accurate predictions of area under the plasma concentration-time profile, oral apparent volume of distribution, and maximum plasma concentration after oral dosing, with 74%, 70%, and 65% within 2-fold, respectively. This evaluation demonstrates that PBPK models can lead to reasonable predictions of human pharmacokinetics.

When poor solubility becomes an issue: from early stage to proof of concept

Drug absorption, sufficient and reproducible bioavailability and/or pharmacokinetic profile in humans are recognized today as one of the major challenges in oral delivery of new drug substances. The issue arose especially when drug discovery and medicinal chemistry moved from wet chemistry to combinatorial chemistry and high throughput screening in the mid-1990s. Taking into account the drug product development times of 8-12 years, the apparent R&D productivity gap as determined by the number of products in late stage clinical development today, is the result of the drug discovery and formulation development in the late 1990s, which were the early and enthusiastic times of the combinatorial chemistry and high throughput screening. In parallel to implementation of these new technologies, tremendous knowledge has been accumulated on biological factors like transporters, metabolizing enzymes and efflux systems as well as on the physicochemical characteristics of the drug substances like crystal structures and salt formation impacting oral bioavailability. Research tools and technologies have been, are and will be developed to assess the impact of these factors on drug absorption for the new chemical entities. The conference focused specifically on the impact of compounds with poor solubility on analytical evaluation, prediction of oral absorption, substance selection, material and formulation strategies and development. The existing tools and technologies, their potential utilization throughout the drug development process and the directions for further research to overcome existing gaps and influence these drug characteristics were discussed in detail.

Predicting pharmacokinetic food effects using biorelevant solubility media and physiologically based modelling

BACKGROUND

Food-induced changes in gastric emptying time, gastric pH and/or intestinal fluid composition may have an impact on the pharmacokinetics of drugs. The aim of this work was to use mathematical models describing physiology in fed and fasted states together with biorelevant solubility and degradation data to simulate food effects for six compounds from recent Roche projects.

METHODS

The solubility of each compound was measured in different biorelevant media: simulated human gastric fluid for the fasted and fed state, simulated human intestinal fluid for the fasted, fed and high-fat state, and simulated human colonic fluid for the upper and the lower colon. A physiologically based absorption model was developed in GastroPlustrade mark for each compound using permeability, solubility, metabolism and distribution data. By incorporating the appropriate physiological parameters and solubility data into the model, the oral pharmacokinetics of each drug was simulated under fasted, fed and/or high-fat conditions. Predicted and observed plasma concentration-time profiles and food effects were compared for a range of doses to assess the accuracy of the simulations.

RESULTS

The models were able to distinguish between minor and significant food effects. The simulation captured well the magnitude of the food effects and for the six compounds correctly predicted the observed plasma exposure in fasted, fed and high-fat conditions.

CONCLUSION

Biorelevant solubility tests can be used together with physiologically based absorption models to predict clinical food effects caused by solubility and/or dissolution rate limitations.

Development and application of physiologically based pharmacokinetic-modeling tools to support drug discovery

Physiologically based pharmacokinetic (PBPK) modeling integrates physicochemical (PC) and in vitro pharmacokinetic (PK) data using a mechanistic framework of principal ADME (absorption, distribution, metabolism, and excretion) processes into a physiologically based whole-body model. Absorption, distribution, and clearance are modeled by combining compound-specific PC and PK properties with physiological processes. Thereby, isolated in vitro data can be upgraded by means of predicting full concentration-time profiles prior to animal experiments. The integrative process of PBPK modeling leads to a better understanding of the specific ADME processes driving the PK behavior in vivo, and has the power to rationally select experiments for a more focussed PK project support. This article presents a generic disposition model based on tissue-composition-based distribution and directly scaled hepatic clearance. This model can be used in drug discovery to identify the critical PK issues of compound classes and to rationally guide the optimization path of the compounds toward a viable development candidate. Starting with a generic PBPK model, which is empirically based on the most common PK processes, the model will be gradually tailored to the specifics of drug candidates as more and more experimental data become available. This will lead to a growing understanding of the 'drug in the making', allowing a range of predictions to be made for various purposes and conditions. The stage is set for a wide penetration of PK modeling and simulations to form an intrinsic part of a project starting from lead discovery, to lead optimization and candidate selection, to preclinical profiling and clinical trials.

pH-independent drug release of an extremely poorly soluble weakly acidic drug from multiparticulate extended release formulations

Extended release mini matrix tablets for 8-Prenylnaringenin (8-PN), an extremely poorly soluble weakly acidic drug, were developed by using polyvinylacetate/polyvinylpyrrolidone as matrix former. Mini matrix tablets were manufactured by direct compression or wet granulation technique. With conventional modified release formulations, the drug demonstrated pH-dependent release due to pH-dependent solubility of the drug substance (i.e., increasing solubility at higher pH-values). In order to achieve pH-independent drug release two classes of pH-modifying agents (water-soluble vs. water-insoluble) were studied with respect to their effect on the dissolution of 8-PN. Addition of water-soluble salts of weak acids (sodium carbonate and sodium citrate) failed in order to achieve pH-independent 8-PN release. In contrast, addition of water insoluble salts of a strong base (magnesium hydroxide and magnesium oxide) was found to maintain high pH-values within the mini matrix tablets during release of 8-PN at pH 1 over a period of 10 h. The micro-environmental conditions for the dissolution of the weakly acidic drug were kept almost constant, thus resulting in pH-independent drug release. Compound release from mini matrix tablets prepared by wet granulation was faster compared to the drug release from tablets prepared by direct compression.

Kinetic model of drug distribution in the urinary bladder wall following intravesical instillation

Intravesical administration of cytotoxic agents is commonly used in urological practice for treatment of superficial bladder cancer. The leading motive is optimisation of drug delivery near the site of action and reduction of systemic toxicity. Bladder pharmacokinetics is complicated by several mechanisms. The objectives of this work were to develop a kinetic model of drug distribution in the bladder wall following intravesical instillation and to study the effect of various parameters on tissue and systemic drug exposure and explore the potential benefits of permeability enhancing effects of chitosan (CH) and polycarbophil (PC) through simulation. Key elements of the model are variable urinary drug concentration due to urine formation and voiding, biphasic diffusion in the bladder tissue and systemic absorption. Model parameters were estimated from bladder-tissue concentration profiles obtained in previous in vitro experiments with pipemidic acid (PPA) as a model drug. The results support further investigations on application of CH and PC in intravesical drug delivery. Both polymers increase permeability of the bladder wall by diffusion enhancement in the urothelium and presumably by improving the contact with the bladder surface. The developed mathematical model could serve for optimisation of intravesical drug delivery and future development of intravesical drug delivery systems.

The virtual laboratory approach to pharmacokinetics: design principles and concepts

Modeling and simulation in pharmacokinetics has turned into the focus of pharmaceutical companies, driven by the emerging consensus that in silico predictions, combined with in vitro data, have the potential to significantly increase insight into pharmacokinetic processes. To support in silico methodology adequately, software tools need to be user-friendly and, at the same time, flexible. In brief, the software has to allow the modeling of ideas that go beyond the current knowledge--in the form of a virtual laboratory. In this review, we present and discuss the necessary design principles and concepts required to do this. They have been implemented in the software package MEDICI-PK, demonstrating its feasibility and advantages.

In Silico Modeling of Non-Linear Drug Absorption for the P-gp Substrate Talinolol and of Consequences for the Resulting Pharmacodynamic Effect

PURPOSE

The aim of the present work was to demonstrate P-glycoprotein's involvement in the non-linear talinolol pharmacokinetics using an advanced compartment and transit model (ACAT) and to compare the results predicted from the model to the finding of a phase I dose escalation study with oral talinolol doses increasing from 25 to 400 mg.

MATERIALS AND METHODS

Besides minimum input parameters for the compound (pKa(s), solubility at one or more pH's, Peff, doses, formulation, diffusivity), physiological and pharmacokinetic properties, transporter data are included in these predictions. The simulations assumed higher expression levels in lower gastrointestinal regions, in particular in the colon, which is in accordance with the results of intestinal rat perfusion studies and intestinal distribution data from rats, catfishes, micropigs and humans reported in the literature. Optimized values for P-glycoprotein (P-gp) Km and Vmax were used for the final simulation results and for a stochastic virtual trial with 12 patients.

RESULTS

Talinolol, a P-gp substrate, exhibits non-linear dose AUC relationship after administration of 25, 50, 100 and 400 mg immediate-release tablets. This dose dependency is due to a decrease of efflux transport caused by saturation of P-gp by talinolol. It was found that oral bioavailability increases after administration of higher doses of talinolol. The predicted bioavailability of the p.o. 25, 50, 100 and 400 mg doses of talinolol was 64, 76, 85, 94%, respectively. Pharmacokinetic parameters (AUC, Cmax) from in silico simulations are within acceptable range comparing with data, observed in vivo. However, the in vitro value of Km for talinolol's interactions with P-gp could not be used in the simulation and still reproduce the observed non-linear dose dependence. For each of the four doses, GastroPlus was used to model pharmacodynamic (PD) response and to optimize the values of CLe, Emax, and EC5o with the effect compartment linked indirectly to the central compartment. For all simulations, EC50 was 114 nM and E0 was 83 bpm.

CONCLUSION

Comparison between the results of the in vivo study and the in silico simulations determined the quality and reliability of the in silico predictions and demonstrate the simulation of dose dependent absorption. In contrast to previous simulation work for the non-linear dose dependence of interaction with intestinal transporters or enterocyte metabolism, optimized Km and Vmax values were required to reproduce the clinically observed non-linear dose dependence. The model developed may be useful in the prediction of absorption of other P-gp substrates including pharmacodynamic consequences.

Recent progress in the computational prediction of aqueous solubility and absorption

The computational prediction of aqueous solubility and/or human absorption has been the goal of many researchers in recent years. Such an in silico counterpart to the biopharmaceutical classification system (BCS) would have great utility. This review focuses on recent developments in the computational prediction of aqueous solubility, P-glycoprotein transport, and passive absorption. We find that, while great progress has been achieved, models that can reliably affect chemistry and development are still lacking. We briefly discuss aspects of emerging scientific understanding that may lead to breakthroughs in the computational modeling of these properties.

An evaluation of the utility of physiologically based models of pharmacokinetics in early drug discovery

Generic physiologically-based models of pharmacokinetics were evaluated for early drug discovery. Plasma profiles after intravenous and oral dosing were simulated in rat for 68 compounds from six chemical classes. Input data consisted of structure based predictions of lipophilicity, ionization, and protein binding plus intrinsic clearance measured in rat hepatocytes, single measured values of aqueous solubility, and artificial membrane permeability. LogP of compounds was high with a mean of 3.9 while free fraction in plasma (mean 9%) and solubility (mean 37 microg/mL) were low. Predicted and observed clearance and volume showed mean fold-error and R2 of 1.8, 0.56, and 1.9, 0.25 respectively. Predicted bioavailability showed strong bias to under prediction correlated to very low aqueous solubility and a theoretical correction for bile salt solubilization in vivo brought some improvement in average prediction error (to 31%). Overall, this evaluation shows that generic simulation may be applicable for typical drug-like compounds to predict differences in pharmacokinetic parameters of more than twofold based upon minimal measured input data. However verification of the simulations with in vivo data for a few compounds of each compound class is recommended since recent discovery compounds may have properties beyond the scope of the current generic models.

A Novel Strategy for Physiologically Based Predictions of Human Pharmacokinetics

BACKGROUND

The major aim of this study was to develop a strategy for predicting human pharmacokinetics using physiologically based pharmacokinetic (PBPK) modelling. This was compared with allometry (of plasma concentration-time profiles using the Dedrick approach), in order to determine the best approaches and strategies for the prediction of human pharmacokinetics.

METHODS

PBPK and Dedrick predictions were made for 19 F. Hoffmann-La Roche compounds. A strategy for the prediction of human pharmacokinetics using PBPK modelling was proposed in this study. Predicted values (pharmacokinetic parameters, plasma concentrations) were compared with observed values obtained after intravenous and oral administration in order to assess the accuracy of the prediction methods.

RESULTS

By following the proposed strategy for PBPK, a prediction would have been made prospectively for approximately 70% of the compounds. The prediction accuracy for these compounds in terms of the percentage of compounds with an average-fold error of <2-fold was 83%, 50%, 75%, 67%, 92% and 100% for apparent oral clearance (CL/F), apparent volume of distribution during terminal phase after oral administration (V(z)/F), terminal elimination half-life (t(1/2)), peak plasma concentration (C(max)), area under the plasma concentration-time curve (AUC) and time to reach C(max) (t(max)), respectively. For the other 30% compounds, unacceptable prediction accuracy was obtained in animals; therefore, a prospective prediction of human pharmacokinetics would not have been made using PBPK. For these compounds, prediction accuracy was also poor using the Dedrick approach. In the majority of cases, PBPK gave more accurate predictions of pharmacokinetic parameters and plasma concentration-time profiles than the Dedrick approach.

CONCLUSIONS

Based on the dataset evaluated in this study, PBPK gave reasonable predictions of human pharmacokinetics using preclinical data and is the recommended approach in the majority of cases. In addition, PBPK modelling is a useful tool to gain insights into the properties of a compound. Thus, PBPK can guide experimental efforts to obtain the relevant information necessary to understand the compound's properties before entry into human, ultimately resulting in a higher level of prediction accuracy.

A strategy for preclinical formulation development using GastroPlus™ as pharmacokinetic simulation tool and a statistical screening design applied to a dog study

The aim of this paper is to propose a pharmaceutical risk assessment strategy that goes beyond the usual characterisation of a clinical candidate molecule according to the biopharmaceutical classification system (BCS). This strategy was evaluated for a new CNS drug with poor solubility and good permeability. In a first step, GastroPlus was used to simulate the absorption process based on preformulation data. These input data involved a physicochemical drug characterisation including drug solubility measurements in simulated physiological media, as well as permeability determination. Further computer simulations were conducted to determine the sensitivity to changes of selected input values. Thus, oral bioavailability prediction was studied as a function of the particle size and drug solubility. The second part of the presented strategy for preclinical formulation development was to test specially designed formulations in a 2(3) screening factorial plan using the dog as the animal model. The factors were the dosage form, food effect and dose strength. One of the two experimental formulations was a capsule filled with the micronised drug, whereas the other formulation was a surfactant solution of the drug. Accordingly, a "worst case" formulation was compared with a "best case" drug solution over the clinically relevant dose range in fasted and fed dogs. The results of the computer simulation indicated that a fraction of the dose is dissolved in the stomach and precipitates partially in the small intestine. The simulation predicted almost full drug absorption during the GI transit time. Interestingly, the simulation implies that stomach drug solubility had little impact on overall fraction absorbed. The results also showed that changes of particle size and reference solubility within two orders of magnitude hardly affected the oral bioavailability. This in silico deduction was subsequently compared with the results of the dog studies. Indeed a surfactant drug solution showed no clear biopharmaceutical superiority over a solid capsule formulation on the average of both dose strengths in fasted and fed dogs. Despite the substantial variability of the in vivo data, the factorial screening design indicated marginal significant interaction between the dose level and feeding status. This can be viewed as a flag for the planning of further studies, since a potential effect of one factor may depend on the level of the other. In summary, the GastroPlus simulation together with the statistically designed dog study provided a thorough biopharmaceutical assessment of the new CNS drug. Based on these findings, it was decided to develop a standard granulate in capsules for phase I studies. More sophisticated formulation options were abandoned and so the clinical formulation development was conducted in a cost-efficient way.

The effects of food on the dissolution of poorly soluble drugs in human and in model small intestinal fluids

PURPOSE

This study was conducted to determine the effect of food on drug solubility and dissolution rate in simulated and real human intestinal fluids (HIF).

METHODS

Dissolution rate obtained via the rotating disk method and saturation solubility studies were carried out in fed and fasted state HIF, fed dog (DIF), and simulated (FeSSIF) intestinal fluid for six aprotic low solubility drugs. The intestinal fluids were characterized with respect to physical-chemical characteristics and contents.

RESULTS

Fed HIF provided a 3.5- to 30-times higher solubility compared to fasted HIF and FeSSIF, whereas fed DIF corresponded well (difference of less than 30%) to fed HIF. The increased solubility of food could mainly be attributed to dietary lipids and bile acids. The dissolution rate was also 2 to 7 times higher in fed HIF than fasted HIF. This was well predicted by both DIF and FeSSIF (difference of less than 30%).

CONCLUSIONS

Intestinal solubility is higher in fed state compared to fasted state. However, the dissolution rate does not increase to the same extent. Dog seems to be a good model for man with respect to dissolution in the small intestine after intake of a meal, whereas FeSSIF is a poorer means of determining intestinal saturation solubility in the fed state.

IV-IVC considerations in the development of immediate-release oral dosage form

Predictive scientific principles and methods to assess in vivo performance of pharmaceutical dosage forms based on in vitro studies are important in order to minimize costly animal and human experiments during drug development. Because of issues related to poor solubility and low permeability of newer drug candidates, there has in recent years been a special focus on in vitro-in vivo correlation (IV-IVC) of drug products, particularly those used orally. Various physicochemical, biopharmaceutical, and physiological factors that need to be considered in successful IV-IVC of immediate-release oral dosage forms are reviewed in this article. The physicochemical factors include drug solubility in water and physiologically relevant aqueous media, pK(a) and drug ionization characteristics, salt formation, drug diffusion-layer pH, particle size, polymorphism of drug substance, and so forth. The biopharmaceutical factors that need to be considered include effects of drug ionization, partition coefficient, polar surface area, etc., on drug permeability, and some of the physiological factors are gastrointestinal (GI) content, GI pH, GI transit time, etc. Various in silico, in vitro, and in vivo methods of estimating drug permeability and absorption are discussed. Additionally, how IV-IVC may be applied to immediate-release oral dosage form design are presented.

Highly potent PDE4 inhibitors with therapeutic potential

The hypothesis that the dose-limiting side effects of PDE4 inhibitors could be mediated via the central nervous system prompted us to design and synthesize a hydrophilic piperidine analog to improve the side effect profile of Ariflo 1, which is an orally active second-generation PDE4 inhibitor. During evaluation of various water-soluble piperidine analogs, 2a-b, 11b-14b, and 17a showed therapeutic potential in cross-species comparison studies. The following three findings were obtained: (1) The hydroxamic acid group, a well known metal chelator, caused a marked increase of inhibitory activity. (2) Water-soluble piperidine analogs lacked the configurational isomerism of Ariflo 1 without loss of inhibitory activity. (3) Replacement of the 4-methoxy residue with a difluoromethoxy residue led to an increase of in vivo potency. Structure-activity relationships are presented. Single-dose rat pharmacokinetic data for 11b, 12b, and 17a are also presented.

Development of a multi particulate extended release formulation for ZK 811 752, a weakly basic drug

ZK 811 752, a potent candidate for the treatment of autoimmune diseases, demonstrated pH-dependent solubility. The resulting release from conventional mini matrix tablets decreased with increasing pH-values of the dissolution medium. The aim of this study was to overcome this problem and to achieve pH-independent drug release. Mini matrix tablets were prepared by direct compression of drug, matrix former (polyvinylacetate/polyvinylpyrrolidone; Kollidon SR) and excipients (lactose, calcium phosphate or maize starch). To solve the problem of pH-dependent solubility fumaric acid was added to the drug-polymer excipient system. The addition of fumaric acid was found to maintain low pH-values within the mini tablets during release of ZK 811 752 in phosphate buffer pH 6.8. Thus, micro environmental conditions for the dissolution of the weakly basic drug were kept constant and drug release was demonstrated to be pH-independent. Incorporation of water-soluble (lactose) or highly swellable (maize starch) excipients accelerated drug release in a more pronounced manner compared to the water-insoluble excipient calcium phosphate. Stability studies demonstrated no degradation of the drug substance and reproducible drug release patterns for mini matrix tablets stored at 25 degrees C/60% RH and 30 degrees C/70% RH for up to 6 months.

Application of full physiological models for pharmaceutical drug candidate selection and extrapolation of pharmacokinetics to man

This paper describes how we are applying physiologically based models of pharmacokinetics as an integrated part in the research and preclinical development of novel drugs. The modeling and simulation tools and techniques used are briefly reviewed and the strategy for application in drug research is described. Three examples illustrate how such models may be applied at different stages ranging from early application prior to in vivo studies, through clinical candidate selection to the estimation of human kinetics and dose selection prior to clinical studies. Although there are obvious restrictions related to limited input data at the earlier stages, the examples illustrate some of the advantages of the approach compared to other more empirical methods. These advantages will be fully exploited with more widespread use of physiological models as powerful and user-friendly software make them accessible to non-specialists.

Modeling and Monte Carlo simulations in oral drug absorption

Drug dissolution, release and uptake are the principal components of oral drug absorption. All these processes take place in the complex milieu of the gastrointestinal tract and they are influenced by physiological (e.g. intestinal pH, transit time) and physicochemical factors (e.g. dose, particle size, solubility, permeability). Due to the enormous complexity issues involved, the models developed for drug dissolution and release attempt to capture their heterogeneous features. Hence, Monte Carlo simulations and population methods have been utilized since both dissolution and release processes are considered as time evolution of a population of drug molecules moving irreversibly from the solid state to the solution. Additionally, mathematical models have been proposed to determine the effect of the physicochemical properties, solubility/dose ratio and permeability on the extent of absorption for regulatory purposes, e.g. biopharmaceutics classification. The regulatory oriented approaches are based on the tube model of the intestinal lumen and apart from the drug's physicochemical properties, take into account the formulation parameters the dose and the particle size.

New Mathematical Methods in Pharmacokinetic Modeling

In recent years, several new methods for the mathematical modeling have gradually emerged in pharmacokinetics, and the development of pharmacokinetic models based on these methods has become one of the most rapidly growing and exciting application-oriented sub-disciplines of the mathematical modeling. The goals of our MiniReview are twofold: i) to briefly outline fundamental ideas of some new modeling methods that have not been widely utilized in pharmacokinetics as yet, i.e. the methods based on the following concepts: linear time-invariant dynamic system, artificial-neural-network, fuzzy-logic, and fractal; ii) to arouse the interest of pharmacological, toxicological, and pharmaceutical scientists in the given methods, by sketching some application examples which indicate the good performance and perspective of these methods in solving pharmacokinetic problems.

In silico approaches for predicting ADME properties of drugs

Combinatorial chemistry and high-throughput screening have increased the possibility of finding new lead compounds at much shorter time periods than conventional medicinal chemistry. However, too much promising drug candidates often fail because of unsatisfactory ADME properties. In silico ADME studies are expected to reduce the risk of late-stage attrition of drug development and to optimize screening and testing by looking at only the promising compounds. To this end, many in silico approaches for predicting ADME properties of compounds from their chemical structure have been developed, ranging from data-based approaches such as quantitative structure-activity relationship (QSAR), similarity searches, and 3-dimensional QSAR, to structure-based methods such as ligand-protein docking and pharmacophore modelling. In addition, several methods of integrating ADME properties to predict pharmacokinetics at the organ or body level have been studied. In this article, we briefly summarize in silico ADME approaches.

Prediction methods and databases within chemoinformatics: emphasis on drugs and drug candidates

MOTIVATION

To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process.

RESULTS

We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described.

Dissolution test as a surrogate for quality evaluation of rifampicin containing fixed dose combination formulations

The present investigation was aimed at developing a dissolution methodology to predict in vivo performance of rifampicin containing fixed dose combination (FDC) products. Six FDC formulations were used in this study, of which four had passed bioequivalence while two failed. Dissolution studies were conducted at agitation intensity of 30-100 rpm as a measure of hydrodynamic stress and at pH media corresponding to gastric and intestinal conditions. Formulations showed variable dissolution at different conditions and dissolution at 50 rpm was most sensitive and differentiated the release profiles of rifampicin under various pH conditions. It was possible to predict in vivo performance of rifampicin from FDCs when in vitro rate and extent of release at various pH was correlated with site, pH and concentration dependent absorption of rifampicin along with gastric emptying time. It was also seen that dissolution conditions recommended in USP for different types of FDCs were insensitive for the formulation changes. Based on this comprehensive evaluation, a decision tree is proposed which will act as a guideline for quality evaluation of FDC products and also will provide a fundamental knowledge for optimization of formulations failing in dissolution studies.

A physiological model for the estimation of the fraction dose absorbed in humans

A physiologically based model for gastrointestinal transit and absorption in humans is presented. The model can be used to study the dependency of the fraction dose absorbed (F(abs)) of both neutral and ionizable compounds on the two main physicochemical input parameters (the intestinal permeability coefficient (P(int)) and the solubility in the intestinal fluids (S(int))) as well as physiological parameters such as the gastric emptying time and the intestinal transit time. For permeability-limited compounds, the model produces the established sigmoidal dependence between F(abs) and P(int). In case of solubility-limited absorption, the model enables calculation of the critical mass-solubility ratio, which defines the onset of nonlinearity in the response of fraction absorbed to dose. In addition, an analytical equation to calculate the intestinal permeability coefficient based on the compound's membrane affinity and molecular weight was used successfully in combination with the physiologically based pharmacokinetic (PB-PK) model to predict the human fraction dose absorbed of compounds with permeability-limited absorption. Cross-validation demonstrated a root-mean-square prediction error of 7% for passively absorbed compounds.

A physiologic model for simulating gastrointestinal flow and drug absorption in rats

PURPOSE

The development of a physiologically based absorption model for orally administered drugs in rats is described.

METHODS

Unlike other models that use a multicompartmental approach, the GI tract is modeled as a continuous tube with spatially varying properties. The mass transport through the intestinal lumen is described via an intestinal transit function. The only substance-specific input parameters of the model are the intestinal permeability coefficient and the solubility in the intestinal fluid. With this physiologic and physicochemical information, the complete temporal and spatial absorption profile can be calculated.

RESULTS

A first performance test using portal concentration data published in the literature yielded an excellent agreement between measured and simulated temporal absorption profiles in the portal vein. Furthermore, the dose dependence of a compound with solubility-limited fraction dose absorbed in rats (chlorothiazide) could be adequately described by the model.

CONCLUSIONS

The continuous absorption model is well suited to simulate drug flow and absorption in the GI tract of rats.

Population pharmacokinetic modeling of oral cyclosporin using NONMEM: comparison of absorption pharmacokinetic models and design of a Bayesian estimator

There have been very few population pharmacokinetic (PopPK) studies and Bayesian forecasting methods dealing with cyclosporin (CsA) so far, probably because of the difficulty of modeling the particular absorption profiles of CsA. The present study was conducted in stable renal transplant patients treated with Neoral and employed the NONMEM program. Its goals were (1) to develop a population pharmacokinetic model for CsA based on an Erlang frequency distribution (which describes asymmetric S-shaped absorption profiles) combined with a 2-compartment model; (2) to compare this model with models combining a time-lag parameter and either a zero-order or first-order rate constant and with a model based on a Weibull distribution; and (3) to develop a PK Bayesian estimator for full AUC estimation based on that "Erlang model." The PopPK model was developed in an index set of 70 patients, and then individual PK parameters and AUC were estimated in 10 other patients using Bayesian estimation. The "Erlang" model best described the data, with mean absorption time (MAT), apparent clearance (CL/F), and apparent volume of the central compartment (Vc/F) of 0.78 hours, 26.3 L/h, and 76 L, respectively (interindividual variability CV = 33, 30, and 48%). Bayesian estimation allowed accurate prediction of systemic exposure using only 3 samples collected at 0, 1, and 3 hours. Regression analysis found no significant difference between the predicted and observed concentrations (10 per patient), and AUC(0-12) were estimated with a nonsignificant bias (0.6 to 8.7%) and good precision (RMSE = 5.3%). In conclusion, the Erlang distribution best described CsA absorption profiles, and a Bayesian estimator developed using this model and a mixed-effect PK modeling program provided accurate estimates of CsA systemic exposure using only 3 blood samples.