Purpose. To develop a quantitative biopharmaceutics drug classification system (QBCS) based on fundamental parameters controlling rate and extent of absorption. Methods. A simple absorption model that considers transit flow, dissolution, and permeation processes stochastically was used to illustrate the primary importance of dose/solubility ratio and permeability on drug absorption. Simple mean time considerations for dissolution, uptake, and transit were used to identify relationships between the extent of absorption and a drug's dissolution and permeability characteristics. Results. The QBCS developed relies on a ( permeability, dose/ solubility ratio) plane with cutoff points 2 x 10(-6) - 10(-5) cm/s for the permeability and 0.5 - 1 (unitless) for the dose/ solubility ratio axes. Permeability estimates, P-app are derived from Caco-2 studies, and a constant intestinal volume content of 250 ml is used to express the dose/ solubility ratio as a dimensionless quantity, q. A physiologic range of 250 - 500 ml was used to account for variability in the intestinal volume. Drugs are classified into the four quadrants of the plane around the cutoff points according to their Papp, q values, establishing four drug categories, i.e., I (P-app > 10(-5) cm/s, q less than or equal to 0.5), II (P-app > 10(-5) cm/s, q > 1), III (P-app < 2 x 10(-6) cm/s, q <= 0.5), and IV (P-app < 2 x 10(-6) cm/s, q > 1). A region for borderline drugs (2 x 10(-6) < P-app < 10(-5) cm/s, 0.5 < q < 1) was defined too. For category I, complete absorption is anticipated, whereas categories II and III exhibit dose/ solubility ratio - limited and permeability-limited absorption, respectively. For category IV, both permeability and dose/ solubility ratio are controlling drug absorption. Semiquantitative predictions of the extent of absorption were pointed out on the basis of mean time considerations for dissolution, uptake, and transit in conjunction with drug's dose/ solubility ratio and permeability characteristics. A set of 42 drugs were classified into the four categories, and the predictions of intestinal drug absorption were in accord with the experimental observations. Conclusions. The QBCS provides a basis for compound classification into four explicitly defined drug categories using the fundamental biopharmaceutical properties, permeability, and dose/ solubility ratio. Semiquantitative predictions for the extent of absorption are essentially based on these drug properties, which either determine or are strongly related to the in vivo kinetics of drug dissolution and intestinal wall permeation.

We have re-examined the random release of particles from fractal polymer matrices using Monte Carlo simulations, a problem originally studied by Bunde {[}J. Chem. Phys. 83, 5909 (1985)]. A certain population of particles diffuses on a fractal structure, and as particles reach the boundaries of the structure they are removed from the system. We find that the number of particles that escape from the matrix as a function of time can be approximated by a Weibull (stretched exponential) function, similar to the case of release from Euclidean matrices. The earlier result that fractal release rates are described by power laws is correct only at the initial stage of the release, but it has to be modified if one is to describe in one picture the entire process for a finite system. These results pertain to the release of drugs, chemicals, agrochemicals, etc., from delivery systems. (C) 2003 American Institute of Physics.

This study, explores the utility of quantitative structure-pharmacokinetic relationship models of the disposition parameters: clearance (CL), apparent volume of drug distribution (V-ap), fractal clearance (CLf), and fractal volume (v(f)), for a series of 23 cephalosporins used in therapeutics. Data for CL, V-ap and elimination half-life were obtained from literature, whereas CL, and vf were calculated from the literature data for CL and V-ap, respectively. A variety of descriptors expressing acidity/basicity, lipophilicity, molecular size and hydrogen bonding properties were estimated using computer packages. For each pharmacokinetic parameter, projection to latent structures (PLS) was applied to the total dataset. Adequate PLS models, with one principal component, were derived for CL, CLf, V-ap and v(f). Identical descriptors were found to be significant for the two clearance as well as for the two volume of distribution terms. CL and CLf expressed similar performance while the predictive performance of v(f) was much higher than that of V-ap. Multiple linear and non-linear regression models were developed. The regression results were in agreement with the PLS models. The non-linear models were superior to the relevant linear relationships. The worst models found were for V-ap (R-2 = 0.523 and R-2 = 0.571 for the linear and non-linear model, respectively) and the best models found were for v(f) (R-2 = 0.729 and R-2 = 0.824 for the linear and non-linear model, respectively). (C) 2003 Elsevier B.V. All fights reserved.

Purpose. To verify the Higuchi law and study the drug release from cylindrical and spherical matrices by means of Monte Carlo computer simulation. Methods. A one-dimensional matrix, based on the theoretical assumptions of the derivation of the Higuchi law, was simulated and its time evolution was monitored. Cylindrical and spherical three-dimensional lattices were simulated with sites at the boundary of the lattice having been denoted as leak sites. Particles were allowed to move inside it using the random walk model. Excluded volume interactions between the particles was assumed. We have monitored the system time evolution for different lattice sizes and different initial particle concentrations. Results. The Higuchi law was verified using the Monte Carlo technique in a one-dimensional lattice. It was found that Fickian drug release from cylindrical matrices can be approximated nicely with the Weibull function. A simple linear relation between the Weibull function parameters and the specific surface of the system was found. Conclusions. Drug release from a matrix, as a result of a diffusion process assuming excluded volume interactions between the drug molecules, can be described using a Weibull function. This model, although approximate and semiempirical, has the benefit of providing a simple physical connection between the model parameters and the system geometry, which was something missing from other semiempirical models.

This study addresses the utility of pharmacodynamic considerations to the assessment of bioequivalence (BE) studies. A novel methodology was developed and the performance of classic, nonclassic and novel BE indices was evaluated using extensive simulations of BE trials generated from a classic pharmacokinetic (PK)/pharmacodynamic (PD) model. Three novel indices based on drug's pharmacodynamics were developed and served as criteria for the assessment of all BE indices. Modified power curves were constructed and used for the analysis of BE trials from a PD point of view. All BE indices of either purely PK or PD nature were classified in a semiquantitative manner according to their strictness in declaring BE. The partial area until the peak concentration followed by the two newly proposed metrics (MARD, MARD(w1)) exhibited the most strict performance in declaring BE irrespective of the PK scenarios examined. The study opens new avenues in BE assessment since it places more emphasis on the PD aspects of the formulations. (C) 2003 Elsevier Science B.V. All rights reserved.

The purposes of this study were to (i) re-examine the relevance of Higuchi equation and the power la Using both simulated and experimental release data in conjunction with the linearized. in tern's of t(1/2). percent of drug release plots. (ii) demonstrate that the power law describes the entire drug release profile of several experimental data, and (iii) point out a physically based hypothesis for the Successful Use Of power law in describing the entire drug release profile. Simulated data generated from the equation of power law were further analyzed using linear regression analysis in accord with the Higuchi equation. The analysis revealed that data generated from the equation Of power law can be misinterpreted as obeying the Higuchi equation. The use of power law in describing the entire drug release curie from HPMC-based matrix tablets is validated by direct fit of power law equation to published data of other authors. A hypothesis based on the nonclassical diffusion of the solutes in the HPMC matrices is used to interpret the successful use of the power law in describing the entire release profile. (C) 2003 Elsevier Science B.V, All rights reserved.

Analysis is presented for Case II drug transport with axial and radial release from cylinders. The previously reported {[}J. Control Release 5 (1987) 37] relationships for radial release from films and slabs are special cases of the general solution derived in this study. The widely used exponential relation M-t/M-infinity = kt(n) describes nicely the first 60% of the fractional release curve when Case II drug transport with axial and radial release from cylinders is operating. (C) 2003 Elsevier Science B.V. All rights reserved.

Materials are distributed throughout the body of mammals by fractal networks of branching tubes. Based on the scaling laws of the fractal structure, the vascular tree is reduced to an equivalent one-dimensional, tube model. A dispersion-convection partial differential equation with constant coefficients describes the heterogeneous concentration profile of an intravascular tracer in the vascular tree. A simple model for the mammalian circulatory system is built in entirely physiological terms consisting of a ring shaped, one-dimensional tube which corresponds to the arterial, venular, and pulmonary trees, successively. The model incorporates the blood flow heterogeneity of the mammalian circulatory system. Model predictions are fitted to published concentration-time data of indocyanine green injected in humans and dogs. Close agreement was found with parameter values within the expected physiological range. (C) 2003 Biomedical Engineering Society. {[}DOI: 10.1114/1.1555627].

Purpose. To investigate the relationship between mean dissolution time (MDT) and dose/solubility ratio (q) using the diffusion layer model. Methods. Using the classic Noyes-Whitney equation and considering a finite dose, we derived an expression for MDT as a function of q various conditions. q was expressed as a dimensionless quantity by taking into account the volume of the dissolution medium. Our results were applied to in vitro and in vivo data taken from literature. Results. We found that MDT depends on q when q < 1 and is infinite when q > 1 and that the classic expression of MDT = 1/k, where k is the dissolution rate constant, holds only in the special case of q = 1. For the case of perfect sink conditions, MDT was found to be proportional to dose. Using dissolution data from literature with q < 1, we found better estimates of MDT when dependency on dose/solubility ratio was considered than with the classic approach. Prediction dissolution limited absorption was achieved for some of the in vivo drug examples examined. Conclusion. The mean dissolution time of a drug depends on dose/solubility ratio, even when the model considered is the simplest possible. This fact plays an important role in drug absorption when absorption is dissolution limited.