The diffusion layer model of drug dissolution is used for the simulation of oral drug absorption as well as for the analysis of experimental data. The governing role of saturation solubility in the rate of dissolution makes this parameter predominant for biopharmaceutical classification purposes. The hypothesis models and criteria associated with the use of solubility and dissolution for the biopharmaceutical classification of compounds and marketed drugs are reviewed in this article. The complex hydrodynamics in the in vitro dissolution apparatuses as well as the motility in the gastrointestinal tract do not allow the application of the diffusion layer model in these systems, as this has been built and verified in the rotating disk device. The solubilizing capacity of gastrointestinal fluids media is higher than the aqueous saturation solubility usually reported and used for biopharmaceutical purposes. Emphasis is given on the reaction-limited model of dissolution which provides a useful alternative not based on diffusion principles. Model independent dissolution parameters are more useful for regulators as our knowledge for the dissolution mechanism(s) under in vivo conditions is limited.

Purpsoe. Investigate the role of metabolites in bioequivalence (BE) assessment. Methods. Sets of ordinary differential equations are used to generate concentration - time data for both parent drug (P) and metabolite (M). The calculations include 24 subjects, two different formulations (Test, Reference), and a range of Test/Reference ratios for the fraction of dose absorbed and the rate of absorption. A summarized view of these results is made through the construction of three dimensional power curves. The criteria for the choice of the preferred analyte (P or M) are based on a sensitivity analysis of the bioequivalence measure (AUC, C-max). The latter depends on the relative ability of P and M to reflect better the changes of the pharmacokinetic parameters and variability. Results. The different sensitivity properties of P and M were reflected on the power curves. For AUC, the performance of metabolite is very similar to that of the parent drug for all scenarios and models examined. A more complex behaviour is evident for C-max. In most of these cases, metabolite data show higher permissiveness in the percentages of acceptance. This attribute is more evident when P exhibits high elimination rate and/or the formation of M occurs rapidly. When the Test and Reference products have similar absorption profiles, metabolite data are preferable for the determination of bioequivalence. Parent drug has the advantage for detecting better the differences in the absorption rate of two drugs. The latter is counterbalanced by the increased sensitivity of P data to the variability of the data. Conclusions. Both parent drug and metabolite share the same ability to declare BE when AUC is used as a bioequivalence measure. In case of C-max, metabolite data exhibit better performance when the T and R products are truly bioequivalent or the two formulations differ in their extent of absorption. For the pharmacokinetic scenarios studied, parent drug data were found to be more sensitive to detect differences in the rate of absorption. However, in such cases, their information is much influenced by the increased variability.

Most correlations between in vitro and in vivo data (IVIVC) rely on linear relationships. However, non-linear IVIVC can be also observed, justified and validated. The purpose of the present work was the development of a methodology for power law IVIVC, which mirror power law kinetics under in vitro and in vivo conditions. Fractional calculus was used to justify power law kinetics for zero-order processes in disordered media. Power law kinetics was observed in a large number of in vitro data sets. When ``zero-order{''} release and absorption is considered in terms of fractional calculus the following power law IVIVC between the fraction released F-r and the fraction absorbed F-alpha, is obtained: F-alpha = mu F-r(lambda) - beta, where mu is a constant related to the rate constants and the orders of the release/absorption kinetics, lambda is the ratio of the orders of the kinetics under in vitro and in vivo conditions and 13 accounts for a time shift between the in vitro and in vivo processes; We used literature data to develop power law IVIVC and derive estimates for mu, lambda and beta; the simulated pharmacokinetic profiles using the in vitro release data and the IVIVC developed compared well with the actual in vivo data. (C) 2010 Elsevier B.V. All rights reserved.

Fractional calculus, the branch of calculus dealing with derivatives of non-integer order (e.g., the half-derivative) allows the formulation of fractional differential equations (FDEs), which have recently been applied to pharmacokinetics (PK) for one-compartment models. In this work we extend that theory to multi-compartmental models. Unlike systems defined by a single ordinary differential equation (ODE), considering fractional multi-compartmental models is not as simple as changing the order of the ordinary derivatives of the left-hand side of the ODEs to fractional orders. The latter may produce inconsistent systems which violate mass balance. We present a rationale for fractionalization of ODEs, which produces consistent systems and allows processes of different fractional orders in the same system. We also apply a method of solving such systems based on a numerical inverse Laplace transform algorithm, which we demonstrate that is consistent with analytical solutions when these are available. As examples of our approach, we consider two cases of a basic two-compartment PK model with a single IV dose and multiple oral dosing, where the transfer from the peripheral to the central compartment is of fractional order alpha < 1, accounting for anomalous kinetics and deep tissue trapping, while all other processes are of the usual order 1. Simulations with the studied systems are performed using the numerical inverse Laplace transform method. It is shown that the presence of a transfer rate of fractional order produces a non-exponential terminal phase, while multiple dose and constant infusion systems never reach steady state and drug accumulation carries on indefinitely. The IV fractional system is also fitted to PK data and parameter values are estimated. In conclusion, our approach allows the formulation of systems of FDEs, mixing different fractional orders, in a consistent manner and also provides a method for the numerical solution of these systems.

The aim of this study is to develop milk-based formulations for ionized and unionized lipophilic drugs. Solubility studies of the following non-steroidal anti-inflammatory drugs (NSAIDs): mefenamic acid, tolfenamic acid, ketoprofen, meloxicam, tenoxicam and nimesulide in phosphate- and glycine-NaOH buffers at nominal pH 8-12. were performed. The solubilities of cyclosporine and danazol in water-ethanol solutions were studied. NSAIDs-, cyclosporine-, danazol-, aspirin-milk oral liquid formulations were prepared by adding the appropriate volume of (i) NSAIDs-alkaline buffer solutions, (ii) water-ethanol solutions of cyclosporine and danazol and (iii) aspirin aqueous solution to 150-200 ml of milk. All the non-steroidal anti-inflammatory drugs exhibited increased solubility in the alkaline buffers. The actual pH values (range 6.7-7.7) of the final NSAIDs-milk formulations were very close to milk pH. The higher ethanol content in ethanol-water mixtures increased the solubility of danazol and cyclosporine. A 15 mg meloxicam-, a 100 mg cyclosporine- and a 500 mg aspirin-milk formulation was administered orally to healthy volunteers. All these formulations showed a satisfactory in vivo performance. The strong buffering capacity of milk that was observed and the high solubility of unionized drugs in ethanol allow the preparation of drug-milk formulations with enhanced pharmacokinetic properties. (C) 2010 Elsevier B.V. All rights reserved.