Validation of a semi-physiological model for caffeine in healthy subjects and cirrhotic patients.

The objective of this paper was to validate a previously developed semi physiological model to simulate bioequivalence trials of drug products. The aim of the model was to ascertain whether the measurement of the metabolite concentration-time profiles would provide any additional information in bioequivalence studies (Fernandez-Teruel et al., 2009a,b; Navarro-Fontestad et al., 2010). The semi-physiological model implemented in NONMEM VI was used to simulate caffeine and its main metabolite plasma levels using caffeine parameters from bibliography. Data from 3 bioequivalence studies in healthy subjects at 3 different doses (100, 175 and 400mg of caffeine) and one study in cirrhotic patients (200 or 250mg) were used. The first aim was to adapt the previous semi-physiological model for caffeine, showing the hepatic metabolism with one main metabolite, paraxanthine. The second aim was to validate the model by comparison of the simulated plasma levels of parent drug and metabolite to the experimental data. The simulations have shown that the proposed semi-physiological model was able to reproduce adequately the pharmacokinetic behavior of caffeine and paraxanthine in both healthy subjects and cirrhotic patients at all the assayed doses. Therefore, the model could be used to simulate plasma concentrations vs. time of drugs with the same pharmacokinetic scheme as caffeine, as long as their population parameters are known, and it could be useful for bioequivalence trial simulation of drugs that undergo hepatic metabolism with a single main metabolite.

Semi-physiologic model validation and bioequivalence trials simulation to select the best analyte for acetylsalicylic acid.

The objective of this paper is to apply a previously developed semi-physiologic pharmacokinetic model implemented in NONMEM to simulate bioequivalence trials (BE) of acetyl salicylic acid (ASA) in order to validate the model performance against ASA human experimental data. ASA is a drug with first-pass hepatic and intestinal metabolism following Michaelis-Menten kinetics that leads to the formation of two main metabolites in two generations (first and second generation metabolites). The first aim was to adapt the semi-physiological model for ASA in NOMMEN using ASA pharmacokinetic parameters from literature, showing its sequential metabolism. The second aim was to validate this model by comparing the results obtained in NONMEM simulations with published experimental data at a dose of 1000 mg. The validated model was used to simulate bioequivalence trials at 3 dose schemes (100, 1000 and 3000 mg) and with 6 test formulations with decreasing in vivo dissolution rate constants versus the reference formulation (kD 8-0.25 h (-1)). Finally, the third aim was to determine which analyte (parent drug, first generation or second generation metabolite) was more sensitive to changes in formulation performance. The validation results showed that the concentration-time curves obtained with the simulations reproduced closely the published experimental data, confirming model performance. The parent drug (ASA) was the analyte that showed to be more sensitive to the decrease in pharmaceutical quality, with the highest decrease in Cmax and AUC ratio between test and reference formulations.

Modified nonsink equation for permeability estimation in cell monolayers: comparison with standard methods.

Cell culture permeability experiments are valuable tools in drug development and candidate selection, but the monolayer preparation protocols and the calculations procedures can affect the permeability estimation. Hence, standardization and method suitability demonstration are necessary steps for using permeability data for regulatory and in vivo prediction purposes. Much attention is usually paid to experimental procedure validation and less to the mathematical analysis of the results although the standard equations used imply several assumptions that many times do not hold. The aim of this study was to use a simulation strategy to explore the performance of a new proposed modified nonsink equation (MNS) for unidirectional apparent permeability estimation in different types of profiles (of cumulative drug amounts versus time) including those in which the initial permeation rate is altered, considering several levels of experimental variability. The second objective was to compare the MNS method with the classical sink and nonsink approaches and finally to explore its usefulness for BCS classification. Real data from permeability experiments representing atypical profiles have been used for fitting with the three approaches, MNS, sink, and nonsink equations, in order to validate the performance of the new proposed model. The results demonstrated that the MNS method is a precise and accurate equation for calculating the apparent unidirectional permeability in any type of profile and different scenarios of variability, in any sink and nonsink conditions, while the standard nonsink equation fails in obtaining good permeability estimations in those situations in which the initial permeation rate is altered. Linear regression models (S and SC) are not valid under nonsink conditions, as expected, as the underlying assumptions (sink conditions) do not hold, but also in situations in which sink conditions are fulfilled but the system variability is high.

Innovative in vitro method to predict rate and extent of drug delivery to the brain across the blood-brain barrier.

The relevant parameters for predicting rate and extent of access across the blood-brain barrier (BBB) are fu,plasma (unbound fraction in plasma), Vu,brain (distribution volume in brain) and Kp,uu,brain (ratio of free concentrations in plasma and brain). Their estimation still requires animal studies and in vitro low throughput experiments which make difficult the screening of new CNS candidates. The aim of the present work was to develop a new whole in vitro high throughput method to predict drug rate and extent of access across the BBB. The system permits estimation of fu,plasma, Vu,brain and Kp,uu,brain in a single experimental system, using in vitro cell monolayers in different conditions. From the ratios of the apparent permeability values (Papp) with the adequate mathematical analysis the relevant parameters can be estimated. Papp of ten model compounds has been obtained in MDCKII and MDCK-Mdr1cell monolayers in the absence and presence of albumin and brain homogenate. The ratio of Papp in the absence and presence of albumin allows estimation of in vitro fu,plasma. Papp in the presence of brain homogenate is used to estimate fu,brain and Vu,brain. Kp,uu,brain is estimated from the apical to basal versus basal to apical clearances. The BBB parameters obtained with the new method were predictive of the in vivo behavior of candidates. In vitro fu,plasma, Kp,uu,brain and Vu,brain (calculated with Papp from MDCKII cell line) presented a good correlation with in vivo fu,plasma, Kp,uu,CSF and Vu,brain published values (r=0.92; r=0.85; and r=0.99 respectively). Despite its simplicity the predictive performance is fairly good considering the reduced number of tested compounds with different physicochemical and transport properties. Further experimental modifications could be checked to optimize the method, but the present data support its feasibility. As other in vitro cell culture models, the system is suitable for miniaturization and robotization to allow high throughput screening of CNS candidates.

Computer simulations for bioequivalence trials: selection of analyte in BCS drugs with first-pass metabolism and two metabolic pathways.

The objective of this work is to use a computer simulation approach to define the most sensitive analyte for in vivo bioequivalence studies of all types of Biopharmaceutics Classification System (BCS) drugs undergoing first-pass hepatic metabolism with two metabolic pathways. A semi-physiological model was developed in NONMEM VI to simulate bioequivalence trials. Four BCS classes (from Class I to IV) of drugs, with three possible saturation scenarios (non-saturation, saturation and saturation of only the major route of metabolism), two (high or low) dose schemes, and six types of pharmaceutical quality for the drug products were simulated. The number of investigated scenarios was 144 (4 × 3 × 2 × 6). The parent drug is the most sensitive analyte for bioequivalence trials in all the studied scenarios. Metabolite data does not show sensitivity to detect differences in pharmaceutical quality or it gives the same information as the parent compound. An interesting point to notice is the case of class I drugs administered at a high dose when the principal metabolic route is saturated and the secondary one is not saturated. In this case a substantial reduction in dissolution rate (as it could occur in the case of a prolonged release formulation developed as a line extension of an immediate release formulation) leads to a considerable increase in the AUC of the major metabolite whose formation is saturated supporting the need to require pharmacokinetic and clinical data for new prolonged release medicinal products.

Computer simulations of bioequivalence trials: selection of design and analyte in BCS drugs with first-pass hepatic metabolism: linear kinetics (I).

Modeling and simulation approaches are useful tools to assess the potential outcome of different scenarios in bioequivalence studies. The aim of this study is to propose a new and improved semi-physiological model for bioequivalence trial simulations and apply it for all BCS (Biopharmaceutic Classification System) drug classes with non-saturated first-pass hepatic metabolism. The semi-physiological model was developed in NONMEM VI to simulate bioequivalence trials. Parent drug and metabolite levels for both reference and test were simulated. Eight types of drugs (with high or low permeability and high or low solubility (class I to IV) and high or low intrinsic clearance) were considered in two variability scenarios (high-low) and in six test products of decreasing biopharmaceutic quality. The scenarios were tested in single dose and steady state studies. In case of drugs with non-saturated hepatic first-pass effect (and no gut-wall metabolism) the parent drug is usually the most sensitive analyte and the single dose design is usually the most sensitive study design to detect the worsening of the biopharmaceutic quality of the test formulation. The only exception to this general conclusion was observed in class III drugs (high solubility, low permeability) with low intrinsic clearance for which the parent drug C(max) ratio in steady state shows higher sensitivity followed by the metabolite C(max) ratio in single dose. This exceptional behaviour is caused by a limited operative absorption time (or absorption window) in class III drugs that precludes complete absorption and produces a non-linear absorption. Therefore, it can be concluded that the metabolite does not need to be measured if the drug has no gut-wall metabolism and shows linear pharmacokinetics. Interestingly, a steady state study should be conducted in this exceptional case to compare with the highest possible sensitivity. Metabolite data in most of the scenarios either shows less sensitivity to the product characteristics (resulting in C(max) ratios passing the bioequivalence criteria when the products were not bioequivalent) or it gives the same information as the parent compound.

Computer simulations of bioequivalence trials: selection of design and analyte in BCS drugs with first-pass hepatic metabolism: Part II. Non-linear kinetics.

The objective of this work is to use a computer simulation approach to define the most sensitive analyte and study design of the in vivo bioequivalence study for all types of Biopharmaceutics Classification System (BCS) drugs undergoing first-pass hepatic metabolism under non-linear conditions. A semi-physiological model was developed in NONMEM VI to simulate bioequivalence trials. Eight classes from class I to IV BCS drugs (with high or low intrinsic clearance) in two variability scenarios (high-low) and in six drug products of decreasing quality were simulated in non-linear conditions to complete a total of 96 scenarios that were tested in single dose and steady state studies and compared with the previous results obtained under linear conditions. Parent drug in single dose is the most sensitive analyte and study design for bioequivalence trials in almost all the studied scenarios. However, this general rule has an exception not only in drugs with low permeability (class III and IV) and low intrinsic clearance, for which parent drug in steady state showed differences in the rate of exposure (Cmax) and also in some occasions in the extent of absorption (AUC), that are not reflected with the same sensitivity in the single dose scenario, but it could also be possible for Cmax in class III drugs with high intrinsic clearance. Metabolite data shows less sensitivity detect differences in biopharmaceutics quality in most of the scenarios or it gives the same information as the parent compound.

Pharmacokinetics in drug discovery.

The aim of this current review is to summarize the present status of pharmacokinetics in Drug Discovery. The review is structured into four sections. The first section is a general overview of what we understand by pharmacokinetics and the different LADMET aspects: Liberation, Absorption, Distribution, Metabolism, Excretion, and Toxicity. The second section highlights the different computational or in silico approaches to estimate/predict one or several aspects of the pharmacokinetic profile of a discovery lead compound. The third section discusses the most commonly used in vitro methodologies. The fourth and last section examines the various approaches employed towards the pharmacokinetic assessment of discovery molecules; including all the LADME processes, discussing the different mathematical methodologies available to establish the PK profile of a test compound; what the main differences are and what should be the criteria for using one or another mathematical approach. The major conclusion of this review is that the use of the appropriate preclinical assays has a key role in the long-term viability of a pharmaceutical company since applying the right tools early in discovery will play a key role in determining the company's ability to discover novel safe and effective therapeutics to patients as quickly as possible.

Population modelling to describe pharmacokinetics of amiodarone in rats: relevance of plasma protein and tissue depot binding.

The objective of this paper was to characterize the disposition phase of AM in rats, after different high doses and modalities of i.v. administration. Three fitting programs, WINNONLIN, ADAPT II and NONMEM were employed. The two-stage fitting methods led to different results, none of which can adequately explain amiodarone's behaviour, although a great amount of data per subject is available. The non-linear mixed effect modelling approach allows satisfactory estimation of population pharmacokinetic parameters, and their respective variability. The best model to define the AM pharmacokinetic profile is a two-compartment model, with saturable and dynamic plasma protein binding and linear tissular depot dynamic binding. These results indicate that peripheral tissues act as depots, causing an important fall in AM plasma levels in the first moment after dosing. Later, the return of the drug from these depots causes a slow increase in serum concentration whenever the dose is reduced.