Peter L.D. Wildfong

A Near-Infrared Spectroscopic Investigation of Relative Density and Crushing Strength in Four-Component Compacts

Near-infrared spectroscopy (NIRS) is commonly employed for the analysis of chemical and physical attributes of intact pharmaceutical compacts. Specifically, NIRS has proven useful in the nondestructive measurement of tablet hardness or crushing strength. Near-infrared (NIR) reflectance and transmittance spectra were acquired for 174 13-mm compacts, which were produced according to a four-constituent mixture design (29 points) composed of anhydrous theophylline, lactose monohydrate, microcrystalline cellulose, and soluble starch. Six compacts were produced for each design point by compacting at multiple pressures. Physical testing and regression analyses were used to model the effect of variation in relative density (and crushing strength) on NIR spectra. Chemometric analyses demonstrated that the overall spectral variance was strongly influenced by anhydrous theophylline as a result of the experimental design and the components spectroscopic signature. The calibration for crushing strength was more linear than the relative density model, although accuracy was poorer in comparison to the density model due to imprecision of the reference measurements. Based on the consideration of reflectance and transmittance measurements, a revised rationalization for NIR sensitivity to compact hardness is presented.

Aqueous Solubility Enhancement Through Engineering of Binary Solid Composites: Pharmaceutical Applications

Limits to the aqueous solubility of emerging new chemical entities, as well as older drug molecules, represent a barrier to solid oral dosage form development. Numerous techniques are conventionally employed in aqueous solubility enhancement, although a universal strategy has proven elusive. Formation of binary solid composites, such as eutectics or amorphous solid dispersions, offers an alternative to traditional solubility enhancement techniques. The reality of these systems, however, is that very few examples have been made commercially available, ultimately stemming from a lack of understanding regarding structural and thermodynamic stability-indicating phenomena associated with higher-energy solid materials. In the present work, a comprehensive structurally based review of the fundamental solid-state properties of binary composite materials is presented. Specific emphasis is placed on current topics of research in the area of binary composite formation and the relationship to the underutilization of this technology with the pharmaceutical industry.

Informatic Calibration of a Materials Properties Database for Predictive Assessment of Mechanically Activated Disordering Potential for Small Molecule Organic Solids

The potential for small molecule organic crystalline materials to become disordered as a result of high shear mechanical processing was investigated. A data-driven model was generated from a database of critical materials properties, which were expected to correlate with the potential of a small molecule organic crystalline solid to become fully disordered by the application of mechanical energy. The model was compared with a previously published disordering model based on fundamental thermodynamic relationships. Samples of 23 crystalline solids were subjected to extensive comminution under controlled temperature conditions; powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC) were used to confirm disordering. Logistic regression was used to investigate the significance of each materials property with respect to the prediction of disordering potential. Seven materials properties (glass transition temperature, melting temperature, heat of fusion, crystallographic density, Youngs modulus, molar volume and attachment energy) were identified as having a significant correlation with the potential for material disordering. Stepwise multivariate logistic regression was used to further assess the correlation between disordering potential and each of the seven properties. A linear probability model based on two materials properties (glass transition temperature and molar volume) was developed for the prediction of disordering potential.

A Structural Investigation into the Compaction Behavior of Pharmaceutical Composites Using Powder X-ray Diffraction and Total Scattering Analysis

PurposeTo use advanced powder X-ray diffraction (PXRD) to characterize the structure of anhydrous theophylline following compaction, alone, and as part of a binary mixture with either α-lactose monohydrate or microcrystalline cellulose.Materials and MethodsCompacts formed from (1) pure theophylline and (2) each type of binary mixture were analyzed intact using PXRD. A novel mathematical technique was used to accurately separate multi-component diffraction patterns. The pair distribution function (PDF) of isolated theophylline diffraction data was employed to assess structural differences induced by consolidation and evaluated by principal components analysis (PCA).ResultsChanges induced in PXRD patterns by increasing compaction pressure were amplified by the PDF. Simulated data suggest PDF dampening is attributable to molecular deviations from average crystalline position. Samples compacted at different pressures were identified and differentiated using PCA. Samples compacted at common pressures exhibited similar inter-atomic correlations, where excipient concentration factored in the analyses involving lactose.ConclusionsPractical real-space structural analysis of PXRD data by PDF was accomplished for intact, compacted crystalline drug with and without excipient. PCA was used to compare multiple PDFs and successfully differentiated pattern changes consistent with compaction-induced disordering of theophylline as a single component and in the presence of another material.

Evaluation of chemometric algorithms in quantitative X-ray powder diffraction (XRPD) of intact multi-component consolidated samples.

Quantitative X-ray powder diffraction (XRPD) data obtained from intact, consolidated samples affords the opportunity to analyze mixtures that simulate pharmaceutical drug products without the need for reversion back to powders; an analytical preparation step that destroys the contextual solid-state information intrinsic to intact consolidated samples. Traditional, standardless quantitative methods generally involve sophisticated pattern refinement procedures (e.g., Rietveld refinement) and are limited to crystalline materials. Methods that incorporate an internal standard are not optimal for compact analysis, and may often be susceptible to prediction errors associated with intensity attenuation. Chemometric-based XRPD utilizes full-pattern methods that combine analyses of both Bragg diffraction and diffuse scatter, thereby allowing for enhancement of signal-to-noise, sensitivity, and selectivity. Classical least-squares (CLS) regression, principal components regression (PCR) and partial least squares (PLS) regression are three chemometric algorithms commonly employed in spectroscopy. In the present work, quantification of a consolidated four-component system, composed of two crystalline materials and two disordered materials was analyzed intact, using two different XRPD optics geometries. Calibrations constructed for the prediction of individual constituent concentrations using the aforementioned three multi-variate algorithms were statistically compared with traditional diffraction-absorption univariate calibration. PLS regression modeling of data collected in transmission geometry provided the best statistical results for the quantification of constituent concentration. Further, this calibration was minimally affected by diffraction pattern anomalies traditionally corrected prior to phase quantification.

Informatics calibration of a molecular descriptors database to predict solid dispersion potential of small molecule organic solids

The use of a novel, in silico method for making an intelligent polymer selection to physically stabilize small molecule organic (SMO) solid compounds formulated as amorphous molecular solid dispersions is reported. 12 compounds (75%, w/w) were individually co-solidified with polyvinyl pyrrolidone:vinyl acetate (PVPva) copolymer by melt-quenching. Co-solidified products were analyzed intact using differential scanning calorimetry (DSC) and the pair distribution function (PDF) transform of powder X-ray diffraction (PXRD) data to assess miscibility. Molecular descriptor indices were calculated for all twelve compounds using their reported crystallographic structures. Logistic regression was used to assess correlation between molecular descriptors and amorphous molecular solid dispersion potential. The final model was challenged with three compounds. Of the 12 compounds, 6 were miscible with PVPva (i.e. successful formation) and 6 were phase separated (i.e. unsuccessful formation). 2 of the 6 unsuccessful compounds exhibited detectable phase-separation using the PDF method, where DSC indicated miscibility. Logistic regression identified 7 molecular descriptors correlated to solid dispersion potential (α=0.001). The atomic mass-weighted third-order R autocorrelation index (R3m) was the only significant descriptor to provide completely accurate predictions of dispersion potential. The three compounds used to challenge the R3m model were also successfully predicted.

Physical characterization of drug:polymer dispersion behavior in polyethylene glycol 4000 solid dispersions using a suite of complementary analytical techniques.

Fifteen model drugs were quenched from 3:1 (w/w) mixtures with polyethylene glycol 4000 (PEG4000). The resulting solids were characterized using powder X-ray diffraction (PXRD), analysis of pair distribution function-transformed PXRD data (where appropriate), hot-stage polarized light microscopy, and differential scanning calorimetry (DSC). Drug/polymer dispersion behavior was classified using the data from each technique, independent of the others, and limitations to single-method characterization of PEG-based systems are highlighted. The data from all characterization techniques were collectively used to classify dispersion behavior, which was compared with single-technique characterization. Of the 15 combinations, only six resulted in solids whose dispersion behavior was consistently described using each standalone technique. The other nine were misclassified using at least one standalone technique, mainly because the phase behavior was ambiguously interpreted when only the data from one technique were considered. The data indicated that a suite of complementary techniques provided better classifications of the phase behavior. Of all the quenched solids, only cimetidine was fully dispersed in PEG4000, suggesting that it solidified from a completely miscible mixture of molten drug and polymer that did not phase separate upon cooling. In contrast, ibuprofen and PEG4000 completely recrystallized during preparation, whereas the remaining 13 drugs were partially dispersed in PEG4000 at this composition.

Structural interpretation in composite systems using powder X-ray diffraction: applications of error propagation to the pair distribution function.

ABSTRACTPurposeTo develop a method for drawing statistical inferences from differences between multiple experimental pair distribution function (PDF) transforms of powder X-ray diffraction (PXRD) data.MethodsThe appropriate treatment of initial PXRD error estimates using traditional error propagation algorithms was tested using Monte Carlo simulations on amorphous ketoconazole. An amorphous felodipine:polyvinyl pyrrolidone:vinyl acetate (PVPva) physical mixture was prepared to define an error threshold. Co-solidified products of felodipine:PVPva and terfenadine:PVPva were prepared using a melt-quench method and subsequently analyzed using PXRD and PDF. Differential scanning calorimetry (DSC) was used as an additional characterization method.ResultsThe appropriate manipulation of initial PXRD error estimates through the PDF transform were confirmed using the Monte Carlo simulations for amorphous ketoconazole. The felodipine:PVPva physical mixture PDF analysis determined ±3σ to be an appropriate error threshold. Using the PDF and error propagation principles, the felodipine:PVPva co-solidified product was determined to be completely miscible, and the terfenadine:PVPva co-solidified product, although having appearances of an amorphous molecular solid dispersion by DSC, was determined to be phase-separated.ConclusionsStatistically based inferences were successfully drawn from PDF transforms of PXRD patterns obtained from composite systems. The principles applied herein may be universally adapted to many different systems and provide a fundamentally sound basis for drawing structural conclusions from PDF studies.

A shared assignment to integrate pharmaceutics and pharmacy practice course concepts.

Objective. To demonstrate for first-year pharmacy students the relevance of pharmaceutics course content to pharmacy practice by implementing a joint, integrated assignment in both courses and assessing its impact. Design. Medication errors and patient safety issues relevant to ophthalmic and otic formulations were selected as the assignment topic. A homework assignment based on a mock court case involving a patient who was given an inappropriate formulation because of a pharmacists medication error was given to students. The scenario was followed by essay and calculation questions linking physical pharmacy concepts with patient safety recommendations. Assessment. Students’ average score on the crossover assignment was 88.7%. Minute papers completed before and after the assignment showed improvement in student learning. Students’ scores on examination questions related to the assignment topic were significantly higher than the previous years students’ performance on similar questions. In a survey conducted at the end of the semester, 91% of students indicated that the assignment helped them relate the covered topics to future practice, and 98% agreed that the assignment emphasized the importance of the pharmaceutics in professional practice. Conclusion. A crossover assignment was an effective means of demonstrating the connection between specific pharmaceutics concepts and practice applications to pharmacy students.

The use of net analyte signal orthogonalization in the separation of multi-component diffraction patterns obtained from X-ray powder diffraction of intact compacts.

X-ray powder diffraction (XRPD) analysis of intact multi-component consolidated mixtures has significant potential owing to the ability to non-destructively quantify and discriminate between solid phases in composite bodies with minimal sample preparation. There are, however, limitations to the quantitative power using traditional univariate methods on diffraction data containing features from all components in the system. The ability to separate multi-component diffraction data into patterns representing single constituents allows both composition as well as physical phenomena associated with the individual components of complex systems to be probed. Intact, four-component compacts, consisting of two crystalline and two amorphous constituents were analyzed using XRPD configured in both traditional Bragg-Brentano reflectance geometry and parallel-beam transmission geometry. Two empirical, model-based methods consisting of a multiple step net analyte signal (NAS) orthogonalization are presented as ways to separate multi-component XRPD patterns into single constituent patterns. Multivariate figures of merit (FOM) were calculated for each of the isolated constituents to compare method-specific parameters such as sensitivity, selectivity, and signal-to-noise, enabling quantitative comparisons between the two modes of XRPD analysis.