Dissolution-Hollow Fiber Membrane (D-HFM) System to Anticipate Biopharmaceutics Risk of Tablets and Capsules.

A dissolution-hollow fiber membrane (D-HFM) system with relatively high area/volume ratio was previously characterized and showed favorably high percent drug absorption. Also, it's in vitro permeation constant (Kp.Ç.) was close to in vivo human permeation constant (kp). The objective of the current study was to predict the in vivo human absorption profile and biopharmaceutic performance of five drug products using the D-HFM system. Four immediate-release (IR) and one extended-release (ER) solid oral dosage form were subjected to the D-HFM system. Tablets and capsule dissolution were also measured using USP apparatus II. Drug solutions were also subjected to D-HFM testing. Predicted and observed absorption profiles in D-HFM system showed close agreement for each solid oral dosage form. Levy-Polli plots from D-HFM system successfully predicted the four IR products to be low biopharmaceutic risk due to permeation rate limited or mixed dissolution/permeation rate limited absorption, and successfully predicted metoprolol ER product to be high biopharmaceutic risk due to dissolution rate limited absorption. These observations showed potential of the in vitro D-HFM system to be utilized in biopharmaceutics risk assessment of in vivo tablet and capsule performance.

Characterization of Dissolution-Permeation System using Hollow Fiber Membrane Module and Utility to Predict in Vivo Drug Permeation Across BCS Classes.

A dissolution-permeation system has potential to provide insight into the kinetic contributions of dissolution and permeation to overall drug absorption. The goals of the study were to characterize a dissolution-hollow fiber membrane (D-HFM) system and compare its resulting in vitro drug permeation constants (Kp') to in vivo clinical permeation constants (kp), for four drugs in various Biopharmaceutics Classification System (BCS) classes. Model predictions for D-HFM were made based on derived mixing tank (MT) and complete radial (CRM) flow models and independent measurement of membrane permeability. Experimental D-HFM studies included donor flow rate and donor volume sensitivity studies, and drug permeation profile studies. Additionally, for the four drugs, Kp'from D-HFM system was compared to (kp) from literature, as well as Kp' values from side-by-side diffusion cell and dissolution/Caco-2 system. Results show progressive D-HFM system development as a dissolution-permeation tool. Results indicated that D-HFM models using MT or CRM provided close agreement between predicted and observed drug permeation profiles. Drug permeation in D-HFM system was volume dependent, as predicted. Favorably, more drug permeated through the D-HFM system (10-20% in 60 min) compared to side-by-side diffusion cell (1%) and dissolution/Caco-2 system (0.1%). Kp' from D-HFM system was also closer to in vivo kp; the two other in vitro models showed lower Kp'. Overall, studies reflect that HFM module has potential to incorporate drug permeation into the in vitro assessment of in vivo tablet and capsule performance.

Lipid composition effect on permeability across PAMPA.

The parallel artificial membrane permeability assay (PAMPA) system has promise to rapidly screen drug candidate passive permeability, but has been poorly described in terms of its lipid membrane structure and function. The objective was to investigate the role of PAMPA lipid composition on the permeability of five model compounds. PAMPA was used and employed individual phospholipids that varied in phosphate head group and acyl chain unsaturation. Transport of benzoic acid, taurocholic acid, metoprolol, sucrose, and mannitol was measured. Membrane fluidity was assessed by 1,3-diphenylhexatriene fluorescence anisotropy. Results indicate that compound permeability across PAMPA differed in their sensitivity to membrane lipid composition, where compounds with appreciable permeability (i.e. at least 0.2 x 10(-6)cm/s) were possibly sensitive to membrane fluidity and apparent ion pair effects. Benzoic acid permeability ranged 51-fold across membrane types, suggesting acyl chain effect on membrane fluidity. Mannitol, sucrose, and taurocholic acid permeabilities were low and independent of lipid composition. Metoprolol permeability ranged 17-fold and exhibited a markedly high permeability across 1,2-dioleoyl-sn-glycero-3-[phospho-L-serine] due to apparent ion pair-facilitated transport. Compound permeability was lowest across the phosphatidylcholines, which is consistent with phosphatidylcholine exhibiting relatively high membrane rigidity. In contrast to results from phosphatidylethanolamines and phosphatidylserines, acyl chain unsaturation had no effect on permeability across phosphatidylcholines. In conclusion, while much remains unknown about PAMPA structure and subsequent PAMPA permeability, results here from five solutes suggest that, for solutes with appreciable permeability, lipid composition modulated drug permeability through possible membrane fluidity and apparent ion pair influences.

Computational model for predicting chemical substituent effects on passive drug permeability across parallel artificial membranes.

Drug permeability is often a limiting step in drug action, requiring chemical optimization of a drug candidate to improve this property. Such optimization is typically performed in the context of a congeneric series, where substituents are varied to optimize the target property. Motivated by this need the present work examines the influence of chemical substituents on passive permeability (log P pass) across parallel artificial membranes (PAMPA) undertaken for three congeneric series of compounds; benzoic acids, pyridines and quinolines. PAMPA showed pyridine and quinoline to have high permeability and chemical substituents to typically reduce the permeability. On the contrary, benzoic acid showed poor permeability and chemical substituents typically increased the permeability. To quantitate these effects with respect to physical properties, models were built to explain and predict the permeability of these classes of compounds based on computed molecular descriptors. Models for the benzoic acid series in the ionized state indicated the solvent accessible surface area, cavity dispersion and the free energy of solvation in hexane as well as in water to dominate permeability. However, when the acid group is treated as neutral, the free energy of solvation in water, the fraction polar surface area, the polar surface area and difference in the free energy of solvation between hexane and water were important; these terms, among others, were also important for the neutral pyridine-quinoline series. Considering that the permeability of the benzoic acid series is about 2 orders of magnitude lower than the pyridines and quinolines and that a shift of approximately two pH units in the p K a of the acid group of benzoic acid will allow for the neutral species of the molecule to dominate under experimental conditions (pH = 6.5), these results suggest that the additional energy barrier associated with permeation of the benzoic acid series is associated with the need to protonate the acidic group, thereby forming the neutral species which may then cross the hydrophobic region of the membrane.

Highly variable drugs: observations from bioequivalence data submitted to the FDA for new generic drug applications.

INTRODUCTION: It is widely believed that acceptable bioequivalence studies of drugs with high within-subject pharmacokinetic variability must enroll higher numbers of subjects than studies of drugs with lower variability. We studied the scope of this issue within US generic drug regulatory submissions. MATERIALS AND METHODS: We collected data from all in vivo bioequivalence studies reviewed at FDA's Office of Generic Drugs (OGD) from 2003-2005. We used the ANOVA root mean square error (RMSE) from bioequivalence statistical analyses to estimate within-subject variability. A drug was considered highly variable if its RMSE for C (max) and/or AUC was > or =0.3. To identify factors contributing to high variability, we evaluated drug substance pharmacokinetic characteristics and drug product dissolution performance. RESULTS AND DISCUSSION: In 2003-2005, the OGD reviewed 1,010 acceptable bioequivalence studies of 180 different drugs, of which 31% (57/180) were highly variable. Of these highly variable drugs, 51%, 10%, and 39% were either consistently, borderline, or inconsistently highly variable, respectively. We observed that most of the consistent and borderline highly variable drugs underwent extensive first pass metabolism. Drug product dissolution variability was high for about half of the inconsistently highly variable drugs. We could not identify factors causing variability for the other half. Studies of highly variable drugs generally used more subjects than studies of lower variability drugs. CONCLUSION: About 60% of the highly variable drugs we surveyed were highly variable due to drug substance pharmacokinetic characteristics. For about 20% of the highly variable drugs, it appeared that formulation performance contributed to the high variability.

Chemical substituent effect on pyridine permeability and mechanistic insight from computational molecular descriptors.

The objective was (1) to evaluate the chemical substituent effect on Caco-2 permeability, using a congeneric series of pyridines, and (2) compare molecular descriptors from a computational chemistry approach against molecular descriptors from the Hansch approach for their abilities to explain the chemical substituent effect on pyridine permeability. The passive permeability of parent pyridine and 14 monosubstituted pyridines were measured across Caco-2 monolayers. Computational chemistry analysis was used to obtain the following molecular descriptions: solvation free energies, solvent accessible surface area, polar surface area, and cavitation energy. Results indicate that the parent pyridine was highly permeable and that chemical substitution was able to reduce pyridine permeability almost 20-fold. The substituent effect on permeability provided the following rank order: 3-COO- < 4-NH2 < 3-CONH2 < 3-Cl < 3-CHO < 3-OH < 3-CH2OH < 3-C6H5 < 3-NH2 < 3-CH2C6H5 < 3-C2H5 < 3-H < 3-CH3 < 3-F < 4-C6H5. This substituent effect was better explained via molecule descriptors from the computational chemistry approach than explained by classic descriptors from Hansch. Computational descriptors indicate that aqueous desolvation, but not membrane partitioning per se, dictated substituent effect on permeability.

Novel metrics to compare dissolution profiles.

PURPOSE: To evaluate four novel metrics that compare dissolution profiles and assess their performance characteristics by comparing dissolution profiles of FAST and SLOW immediate release metoprolol tartrate tablets. METHODS: The four novel metrics (rho, rho m, delta a, and delta s), along with f2, were applied to dissolution data from FAST and SLOW metoprolol tartrate tablets. For example, rho m is defined as: [formula: see text] where Rt is the percent dissolved of the reference product at time t, Tt the percent dissolved of the test product at time t, and RATIOt the larger of either Rt/Tt or Tt/Rt. The mean metric values, upper (or lower) confidence limits, and skewness values were calculated, in order to characterize the performance of each metric. RESULTS: The mean values of rho, rho m, delta a, delta s, and f2 were 1.80, 0.80, 0.47, 0.36, and 19.6, respectively. The novel metrics indicate that greater than a 50% relative difference exists between the FAST and SLOW profiles. The upper 95% confidence limits for rho, rho m, delta a, and delta s were 1.84, 0.83, 0.48, and 0.38, respectively, with f2 having a lower limit of 19.1. Skewness values for ln-transformed rho, rho m, delta a, delta s, and f2 were 0.81, 0.71, 0.86, 0.47, and -0.94, respectively, suggesting favorable metric distribution properties. CONCLUSIONS: The direct curve comparison metrics rho, rho m, delta a, and delta s appear to be viable methods to compare dissolution profiles, particularly rho m.