Carl Anderson - Academia.edu (original) (raw)

Papers by Carl Anderson

Research paper thumbnail of Calibration Transfer of a Quantitative Transmission Raman PLS Model: Direct Transfer vs. Global Modeling

Journal of Pharmaceutical Innovation, 2017

Global regulatory agencies have encouraged the use of process analytical technology (PAT) to assu... more Global regulatory agencies have encouraged the use of process analytical technology (PAT) to assure quality in the pharmaceutical industry. A frequently cited obstacle to the implementation of spectroscopy-based PAT methods is the difficulty associated with directly transferring calibration models between PAT instruments. The goal of this study was to compare model transfer strategies for method transfer between two transmission Raman spectroscopy (TRS) instruments. The calibration and test samples were pharmaceutical compacts of acetaminophen and excipients. The experimental design was a 3 factor by 5 level circumscribed central composite design of active pharmaceutical ingredient, lactose, and microcrystalline cellulose concentrations. The calibration and test data were collected using two instruments. Quantitative models were constructed using partial least squares regression. Global calibration modeling and direct model transfer were compared to evaluate opportunities for situations involving method transfer, calibration update, and line extension. Models were compared using a t testbased method to evaluate performance statistics. Statistical analysis demonstrated equivalent performance of the global modeling and direct transfer methods. This work demonstrated that a quantitative transmission Raman model could be directly transferred across instruments, thus avoiding the challenges and resources necessary when creating global models.

Research paper thumbnail of Influence of moisture variation on the performance of Raman spectroscopy in quantitative pharmaceutical analyses

Journal of Pharmaceutical and Biomedical Analysis, 2019

Highlight  Raman spectral variations of the pharmaceutical materials were observed due to the pr... more Highlight  Raman spectral variations of the pharmaceutical materials were observed due to the presence of water.  Unwanted spectral baseline change due to moisture variation caused spectral inconsistency across calibration and test samples which degraded quantitative model performance.  Including moisture variations into the calibration set significantly improved Raman spectroscopic model performance. performance for API. The work demonstrated that accounting for moisture variation during method development reduced the prediction error of the multivariate prediction model.

Research paper thumbnail of Method Development and Validation of an Inline Process Analytical Technology Method for Blend Monitoring in the Tablet Feed Frame Using Raman Spectroscopy

Analytical chemistry, Jan 17, 2018

Inline process analytical technology sensors are the key elements to enable continuous manufactur... more Inline process analytical technology sensors are the key elements to enable continuous manufacturing. They facilitate real-time monitoring of critical quality attributes of both intermediate materials and finished products. The aim of this study was to demonstrate method development and validation for inline and offline calibration strategies to determine the blend content during tablet compression via Raman spectroscopy. An inline principal component regression model was developed from Raman spectra collected in the feed frame. At the same time, an offline study was conducted over a small amount of the calibration blends using an in-house moving powder setup to simulate the environment of the feed frame. The model developed offline was able to predict the active ingredient content after a bias correction and used only a fraction of the material. The offline method can serve as a simple method to facilitate calibration development when the time and access to the press is limited. Th...

Research paper thumbnail of An Improved Photocatalyst of TiO2/SiO2 Prepared by a Sol-Gel Synthesis

The Journal of Physical Chemistry, 1995

The effect of incorporation of Si02 on the behavior of a TiO2-based photocatalyst prepared by a s... more The effect of incorporation of Si02 on the behavior of a TiO2-based photocatalyst prepared by a sol-gel technique from organometallic precursors is described. Application of photocatalysts with different TiOd Si02 ratios to the photodecomposition of rhodamine-6G (R-6G) demonstrates that a ratio of 30/70 produces a catalyst about 3 times more active than Degussa P-25 TiO2. Larger amounts of Si02 decrease the activity. The adsorption of R-6G on the different materials and the photodecomposition of preadsorbed R-6G is also described. The studies suggest that photogenerated intermediates are sufficiently mobile to react with R-6G adsorbed on Si02 sites but that adsorption of R-6G on Ti02 is not a prerequisite for reaction.

Research paper thumbnail of Investigation of the Sensitivity of Transmission Raman Spectroscopy for Polymorph Detection in Pharmaceutical Tablets

Applied spectroscopy, 2017

Polymorph detection is critical for ensuring pharmaceutical product quality in drug substances ex... more Polymorph detection is critical for ensuring pharmaceutical product quality in drug substances exhibiting polymorphism. Conventional analytical techniques such as X-ray powder diffraction and solid-state nuclear magnetic resonance are utilized primarily for characterizing the presence and identity of specific polymorphs in a sample. These techniques have encountered challenges in analyzing the constitution of polymorphs in the presence of other components commonly found in pharmaceutical dosage forms. Laborious sample preparation procedures are usually required to achieve satisfactory data interpretability. There is a need for alternative techniques capable of probing pharmaceutical dosage forms rapidly and nondestructively, which is dictated by the practical requirements of applications such as quality monitoring on production lines or when quantifying product shelf lifetime. The sensitivity of transmission Raman spectroscopy for detecting polymorphs in final tablet cores was inves...

Research paper thumbnail of Investigating the Effect of Experimental Design and Pre-processing Techniques on Multivariate Figures of Merit

Research paper thumbnail of Classical least squares for quantitative analysis of pharmaceutical solid dosage forms: Part 1—Effect of experimental design

NIR news, 2012

acetaminophen, microcrystalline cellulose, croscarmellose-sodium, magnesium stearate Table 1. Ful... more acetaminophen, microcrystalline cellulose, croscarmellose-sodium, magnesium stearate Table 1. Full-factorial design for the first calibration set (%, w/w). P harmaceutical applications of classical least squares (CLS) for quantitative analysis of near infrared (NIR) data are not common because strict assumptions must be met in order to achieve adequate performance. These assumptions include Beer’s law, linear additivity and constant pathlength. However, more advanced methods have been recently developed that utilise CLS as a starting point and correct for assumptions that may not be satisfied; two common methods include prediction augmented CLS (PACLS) and a CLS/PLS (partial least squares) algorithm. While such methods have been shown to achieve superior prediction performance, they are still based on CLS and caution must be exercised when using them. This series of articles focuses on some practical aspects of using indirect CLS and CLS-based methods for quantitative analysis of NIR spectra, specifically for pharmaceutical applications. For a detailed synopsis of the theory behind CLS, the reader is directed to a recent article published by Fearn and the chemometrics book by Beebe, Pell and Seasholtz.

Research paper thumbnail of An efficient method-development strategy for quantitative chemical imaging using terahertz pulse spectroscopy

Journal of Pharmaceutical Innovation, 2006

The purpose of our research was to investigate efficient procedures for generating multivariate p... more The purpose of our research was to investigate efficient procedures for generating multivariate prediction vectors for quantitative chemical analysis of solid dosage forms using terahertz pulse imaging (TPI) reflection spectroscopy. A set of calibration development and validation tablet samples was created following a ternary mixture of anhydrous theophylline, lactose monohydrate, and microcrystalline cellulose (MCC). Spectral images of one side of each tablet were acquired over the range of 8 cm-1 to 60 cm-1. Calibration models were generated by partial least-squares (PLS) type II regression of the TPI spectra and by generating a purecomponent projection (PCP) basis set using net analyte signal (NAS) processing. Following generation of the calibration vectors, the performance of both methods at predicting the concentration of theophylline, lactose, and MCC was compared using the validation spectra and by generating chemical images from samples with known composition patterns. Sensitivity was observed for the PLS calibration over the range of all constituents for both the calibration and the validation datasets; however, some of the calibration statistics indicate that PLS overfits the spectra. Multicomponent prediction images verified the spatial and composition fidelity of the system. The NAS-PCP calibration procedure yielded accurate linear predictions of theophylline and lactose, whereas the results for MCC prediction were poor. The poor sensitivity for MCC is assumed to be related to the relative lack of phonon absorption bands, which concurs with the characterization of MCC as being semi-crystalline. The results of this study demonstrate the use of TPI reflection spectroscopy and efficient NAS-PCP for the quantitative analysis of crystalline pharmaceutical materials.

Research paper thumbnail of Adaptive Design Space as an Integrated Component of Quality by Design

Journal of Pharmaceutical Innovation, 2012

ABSTRACT Introduction The US Food and Drug Administration requires pharmaceutical companies to de... more ABSTRACT Introduction The US Food and Drug Administration requires pharmaceutical companies to develop extensive process understanding prior to routine manufacturing of drug products. Through development and validation, drug manufacturers enhance their process understanding and identify an acceptable range of process parameters for each unit operation; this is referred to as the design space. Typically, limited work is done to study the effect of long-term raw material variations on the robustness of the design space. In the present study, the development of a design space for a tablet formulation containing two APIs (acetaminophen, caffeine) through a direct compression process was investigated. Material and Methods A design of experiment including different excipient ratios of microcrystalline cellulose and lactose, two croscarmellose sodium levels, four tablet compression forces, and four blend parameters was created using an industrial-size press to define a knowledge space. Quality attributes (disintegration time, dissolution, radial tensile strength, and friability) were measured and a design space derived. In order to test the robustness of the design space, raw material properties, specifically particle size of acetaminophen and ratio of lactose anhydrous to monohydrate, were modified. Also, compression parameters were varied. Results Tablets were analyzed for relevant critical quality attributes (CQAs) to investigate how variability in raw materials can change the design space. The modification of the process parameters was used as a means of compensating for raw material variability to produce tablets that met CQA requirements. An adaptive design space approach based on the adaptation of critical process parameters is proposed to facilitate the creation of tablets meeting specifications despite variation in raw material properties.

Research paper thumbnail of Efficient Near-Infrared Spectroscopic Calibration Methods for Pharmaceutical Blend Monitoring

Journal of Pharmaceutical Innovation, 2011

Near-infrared (NIR) spectroscopy is an important analytical tool for online process monitoring of... more Near-infrared (NIR) spectroscopy is an important analytical tool for online process monitoring of pharmaceutical unit operations. Traditionally, the development and maintenance of robust, precise, and accurate quantitative NIR calibrations requires a substantial investment for the creation of sample sets. This study demonstrates the ability to develop efficient NIR calibrations using reduced sample sets. Prediction performance of several multivariate algorithms was compared on two different NIR spectrometers for pharmaceutical blend monitoring. Classical least-squares (CLS)-based algorithms took advantage of pure component scans to produce the most sensitive quantitative calibrations using reduced sample sets when compared to partial least squares (PLS) regression and two nonlinear methods. The PLS algorithm and the nonlinear methods produced models with low error but lacked the sensitivity needed to model subtle blending trends. The CLS-based methods produced models with adequate sensitivity for blend monitoring. The robustness of the CLS-based methods was further demonstrated in the ease of transfer between instruments using only a bias correction of the predictions.

Research paper thumbnail of Comparison of Terahertz Pulse Imaging and Near-Infrared Spectroscopy for Rapid, Non-Destructive Analysis of Tablet Coating Thickness and Uniformity

Journal of Pharmaceutical Innovation, 2007

In this study, coating thickness and uniformity of production-scale pharmaceutical tablets were i... more In this study, coating thickness and uniformity of production-scale pharmaceutical tablets were investigated using near-infrared (NIR) and terahertz pulse imaging (TPI) spectroscopy. Two coating formulations were considered; samples for each coating formulation were obtained at 0, 1, 2, 3, 4, and 5% coating weight. NIR spectra were collected, and regressed with respect to batch percent weight gain. While standard errors of calibration (SEC) less than 0.5% were observed for both formulations, the calibrations were not specifically sensitive to coating thickness. An upper limit for NIR coating thickness analysis was estimated to be~4-6% weight gain for this system. The NIR calibrations were used as filters to choose subsets of samples for TPI, and as a secondary method for validation of TPI results. The features in TPS time-domain spectra result when an incident THz plane wave meets a refractive index interface, which may be converted to an absolute distance. Therefore, assuming that a discernible difference in refractive index between coating material and core exists, coating thickness can be determined non-destructively. Coating thickness measurements from TPI and NIR spectroscopy were compared to estimate the lower limit for quantitative TPI coating analysis; a lower limit of~35 mm was obtained for this system. Optical microscopy was employed on a subset of samples to validate absolute thickness values; reasonable correlations between the three methods were obtained. TPI was considered advantageous relative to the other methods, as similar results were obtained without the need for destructive sampling or empirical calibration development.

Research paper thumbnail of Hybrid Controls Combining First-Principle Calculations with Empirical Modeling for Fully Automated Fluid Bed Processing

Journal of Pharmaceutical Innovation, 2012

Introduction The US Food and Drug Administration has encouraged the use of the guidelines put for... more Introduction The US Food and Drug Administration has encouraged the use of the guidelines put forth by the International Conference on Harmonization (ICH-Q8) that allow for operational flexibility within a validated design space. These guidelines make possible fully automated control systems that incorporate information about a process back into the system to adjust process variables to consistently hit product quality targets. Traditionally, fluid bed control systems have used either first-principle calculations to control the internal process environment or purely empirical methods that incorporate online process measurements with process models and real-time data management. This study demonstrates the development and implementation of a novel hybrid control system that combines the two traditional approaches. Material and Methods Granules containing gabapentin, and hydroxypropyl cellulose were prepared in a high-shear granulator and dried in a fluid bed processing system (Diosna Minilab). The fluid bed dryer was outfitted with near-infrared (NIR), pressure, temperature, and flow sensors which were connected to a distributed control system (DCS) that was used to exercise control of the system. The control system itself consisted of a Delta V DCS (Emerson Process Management, Equipment and Controls, Inc., Lawrence, PA, USA) that was used to interface the fluid bed dryer with SynTQ (Optimal, Bristol, UK). The dried granules were characterized by median particle size and quantity of gabapentin lactam formed (a chemical degradant). Results Control of a fluid bed dryer utilizing both a firstprinciple control strategy and empirical model-based controls was demonstrated. First-principle control was based on an environmental equivalency factor model to maintain a constant thermodynamic environment. Empirical models included a pressure drop across the bed and NIR measurement of water content. These systems were combined effectively to consistently dry granules prepared by high-shear wet granulation. Utilization of this system greatly reduced the number of experiments necessary to characterize the performance of the system and facilitated control of the process with respect to the two properties of interest, median particle size and chemical stability during drying.

Research paper thumbnail of Online Monitoring of Pharmaceutical Materials Using Multiple NIR Sensors—Part II: Blend End-point Determination

Journal of Pharmaceutical Innovation, 2013

The effect of various blend end-point algorithms on the observed blending time of pharmaceutical ... more The effect of various blend end-point algorithms on the observed blending time of pharmaceutical powders and content uniformity of subsequent tablets was investigated for a five-component system. The blending process was monitored online, in real time, using two near-infrared sensors. Algorithms based on the standard deviation, average, and distributions of concentration predictions were tested for all major blend constituents, respectively. The potential to combine sensor outputs in the end-point decision was contrasted by the consideration of the two sensor outputs individually or simultaneously. The algorithms employed demonstrated highly variable end-points when compared with the final tablet quality, although blends were deemed to have reached homogeneity faster when only the active ingredient was considered. Some algorithms proved to be either too sensitive to local mixing and demixing phenomena or not sensitive enough, yielding results not consistent with the observed tablet content uniformity. Results showed that the choice of an end-point algorithm must be directed by the product of interest (nature of the active, therapeutic window, etc.), the particular characteristics that the delivery forms should have (immediate release, sustained release), and most significantly, the purpose of blending. A single algorithm is not expected to be adequate across all formulations. However, as the complexity of the blending process increases (multiple sensors, trends of multiple ingredients to follow, etc.) the decision process becomes more complex with not only calibration maintenance issues to consider, but also calibration transfer, relevance of the criteria for the actives, and the desired final product properties.

Research paper thumbnail of Improvement of pharmaceutical near infrared calibrations by empirical target distribution optimisation

Journal of Near Infrared Spectroscopy, 2011

ABSTRACT Using process samples to develop near infrared prediction models can generate artefacts ... more ABSTRACT Using process samples to develop near infrared prediction models can generate artefacts in the calibration set, potentially reducing model performance. Due to the inherent variability of manufacturing processes, the assumption that all samples from a given batch have the same concentration for the compound of interest is incorrect. A tablet press will produce compacts with different drug concentrations, distributed around a nominal value, due to mechanical effects, vibrations and powder segregation that occur in the hopper. Differences in tablet crushing strength may also be observed for those same reasons. Consequently, using such samples and their associated nominal concentrations for the development of a calibration model for the prediction of content uniformity of tablets might produce models with rather high error while able to cope with a large range of process variability. The objective of this work was to investigate empirical approaches for optimising the target (reference) concentrations of prediction samples to best match the underlying spectral variance in an attempt to mitigate interferences that may be responsible for select portions of calibration error. Three approaches were developed. The first used samples presenting a low residual from an original model to re-predict high residual samples. The second approach was an iterative search of the best target value for each sample. The third method used target values generated from a normal distribution. These approaches were compared with the classical slope and bias correction methods on their ability to predict two independent validation sets. While several methods showed significant over-fitting and a high validation error, the iterative search routine enhanced calibration performance compared to post-regression correction methods and was proven to be a viable alternative to current industry practices.

Research paper thumbnail of Characterization of pharmaceutical powder blends using in situ near-infrared chemical imaging

Chemical Engineering Science, 2014

This study demonstrates the capabilities of NIR imaging as an effective tool for characterization... more This study demonstrates the capabilities of NIR imaging as an effective tool for characterization of pharmaceutical powder blends. The powder system used in this small-scale powder blending study consists of acetaminophen (APAP, the model API), microcrystalline cellulose (MCC) and lactose monohydrate. Mixtures of these components were blended for different times for a total of ten time points (ten blending trials). Images collected from multiple locations of the blends were used to generate a qualitative description of the components' blending dynamics and a quantitative determination of both the blending end point and the distribution variability of the components. Multivariate analyses, including pure-component PCA and discriminate PLS, were used to treat the imaging data. A good correlation was observed between imaging results and a UV-Vis monitoring method for determining blend homogeneity. Score images indicated general trends of the distribution of blending constituents for all ten blending trials. The API distribution pattern throughout blending was detected and the API domain size for different blending trials was compared. Blending insights obtained from this study may be transferable to large scale powder blending. Blending process understanding obtained from this study has the potential to facilitate the optimization of blending process control in the future.

Research paper thumbnail of Development of a Neuroscience-oriented "Methods" Course for Graduate Students of Pharmacology and Toxicology

Cell Biology Education, 2006

To provide graduate students in pharmacology/toxicology exposure to, and cross-training in, a var... more To provide graduate students in pharmacology/toxicology exposure to, and cross-training in, a variety of relevant laboratory skills, the Duquesne University School of Pharmacy developed a “methods” course as part of the core curriculum. Because some of the participating departmental faculty are neuroscientists, this course often applied cutting-edge techniques to neuroscience-based systems, including experiments with brain G protein–coupled receptors. Techniques covered by the course include animal handling and behavioral testing, bacterial and mammalian cell culture, enzyme-linked immunosorbent assay, western blotting, receptor binding of radioligands, plasmid DNA amplification and purification, reverse transcriptase-polymerase chain reaction, gel electrophoresis, and UV-visible and fluorescence spectroscopy. The course also encompasses research aspects such as experimental design and record keeping, statistical analysis, and scientific writing. Students were evaluated via laborato...

Research paper thumbnail of Near-Infrared Spectroscopic Investigation of the Hydrothermal Degradation Mechanism of Wood as an Analogue of Archaeological Wood. Part II: Hardwood

Applied Spectroscopy, 2009

Near-infrared (NIR) spectroscopy and chemometrics were applied to analyze the degradation mechani... more Near-infrared (NIR) spectroscopy and chemometrics were applied to analyze the degradation mechanism of hardwood following hydrothermal treatment. NIR spectra, chemical composition, oven-dried density, equilibrium moisture content, compressive Young's modulus parallel to grain, and cellulose crystallinity of artificially degraded beech as an analogue of archaeological wood were systematically measured. Partial least squares (PLS) regression analysis was employed to predict compressive Young's modulus using NIR spectra and various properties as independent variables. Results are also compared with previous data obtained from similar treatment of softwood (Hinoki cypress). The increase in cellulose crystallinity of hardwood during the initial stage of hydrothermal treatment (up to 5 hours) was correlated with an improvement in the mechanical properties of wood. Young's modulus for both hardwood and softwood showed a gradual decrease over five hours of hydrothermal treatment...

Research paper thumbnail of Determination of figures of merit for near-infrared and raman spectrometry by net analyte signal analysis for a 4-component solid dosage system

AAPS PharmSciTech, 2007

Process analytical technology has elevated the role of sensors in pharmaceutical manufacturing. O... more Process analytical technology has elevated the role of sensors in pharmaceutical manufacturing. Often the ideal technology must be selected from many suitable candidates based on limited data. Net analyte signal (NAS) theory provides an effective platform for method characterization based on multivariate figures of merit (FOM). The objective of this work was to demonstrate that these tools can be used to characterize the performance of 2 dissimilar analyzers based on different underlying spectroscopic principles for the analysis of pharmaceutical compacts. A fully balanced, 4-constituent mixture design composed of anhydrous theophylline, lactose monohydrate, microcrystalline cellulose, and starch was generated; it consisted of 29 design points. Six 13-mm tablets were produced from each mixture at 5 compaction levels and were analyzed by near-infrared and Raman spectroscopy. Partial least squares regression and NAS analyses were performed for each component, which allowed for the computation of FOM. Based on the calibration error statistics, both instruments were capable of accurately modeling all constituents. The results of this work indicate that these statistical tools are a suitable platform for comparing dissimilar analyzers and illustrate the complexity of technology selection.

Research paper thumbnail of Process analytical technology case study part I: Feasibility studies for quantitative near-infrared method development

AAPS PharmSciTech, 2005

*The views presented in this article do not necessarily reflect those of the Food and Drug Admini... more *The views presented in this article do not necessarily reflect those of the Food and Drug Administration.

Research paper thumbnail of Online Monitoring of Pharmaceutical Materials Using Multiple NIR Sensors—Part I: Blend Homogeneity

Journal of Pharmaceutical …

Research paper thumbnail of Calibration Transfer of a Quantitative Transmission Raman PLS Model: Direct Transfer vs. Global Modeling

Journal of Pharmaceutical Innovation, 2017

Global regulatory agencies have encouraged the use of process analytical technology (PAT) to assu... more Global regulatory agencies have encouraged the use of process analytical technology (PAT) to assure quality in the pharmaceutical industry. A frequently cited obstacle to the implementation of spectroscopy-based PAT methods is the difficulty associated with directly transferring calibration models between PAT instruments. The goal of this study was to compare model transfer strategies for method transfer between two transmission Raman spectroscopy (TRS) instruments. The calibration and test samples were pharmaceutical compacts of acetaminophen and excipients. The experimental design was a 3 factor by 5 level circumscribed central composite design of active pharmaceutical ingredient, lactose, and microcrystalline cellulose concentrations. The calibration and test data were collected using two instruments. Quantitative models were constructed using partial least squares regression. Global calibration modeling and direct model transfer were compared to evaluate opportunities for situations involving method transfer, calibration update, and line extension. Models were compared using a t testbased method to evaluate performance statistics. Statistical analysis demonstrated equivalent performance of the global modeling and direct transfer methods. This work demonstrated that a quantitative transmission Raman model could be directly transferred across instruments, thus avoiding the challenges and resources necessary when creating global models.

Research paper thumbnail of Influence of moisture variation on the performance of Raman spectroscopy in quantitative pharmaceutical analyses

Journal of Pharmaceutical and Biomedical Analysis, 2019

Highlight  Raman spectral variations of the pharmaceutical materials were observed due to the pr... more Highlight  Raman spectral variations of the pharmaceutical materials were observed due to the presence of water.  Unwanted spectral baseline change due to moisture variation caused spectral inconsistency across calibration and test samples which degraded quantitative model performance.  Including moisture variations into the calibration set significantly improved Raman spectroscopic model performance. performance for API. The work demonstrated that accounting for moisture variation during method development reduced the prediction error of the multivariate prediction model.

Research paper thumbnail of Method Development and Validation of an Inline Process Analytical Technology Method for Blend Monitoring in the Tablet Feed Frame Using Raman Spectroscopy

Analytical chemistry, Jan 17, 2018

Inline process analytical technology sensors are the key elements to enable continuous manufactur... more Inline process analytical technology sensors are the key elements to enable continuous manufacturing. They facilitate real-time monitoring of critical quality attributes of both intermediate materials and finished products. The aim of this study was to demonstrate method development and validation for inline and offline calibration strategies to determine the blend content during tablet compression via Raman spectroscopy. An inline principal component regression model was developed from Raman spectra collected in the feed frame. At the same time, an offline study was conducted over a small amount of the calibration blends using an in-house moving powder setup to simulate the environment of the feed frame. The model developed offline was able to predict the active ingredient content after a bias correction and used only a fraction of the material. The offline method can serve as a simple method to facilitate calibration development when the time and access to the press is limited. Th...

Research paper thumbnail of An Improved Photocatalyst of TiO2/SiO2 Prepared by a Sol-Gel Synthesis

The Journal of Physical Chemistry, 1995

The effect of incorporation of Si02 on the behavior of a TiO2-based photocatalyst prepared by a s... more The effect of incorporation of Si02 on the behavior of a TiO2-based photocatalyst prepared by a sol-gel technique from organometallic precursors is described. Application of photocatalysts with different TiOd Si02 ratios to the photodecomposition of rhodamine-6G (R-6G) demonstrates that a ratio of 30/70 produces a catalyst about 3 times more active than Degussa P-25 TiO2. Larger amounts of Si02 decrease the activity. The adsorption of R-6G on the different materials and the photodecomposition of preadsorbed R-6G is also described. The studies suggest that photogenerated intermediates are sufficiently mobile to react with R-6G adsorbed on Si02 sites but that adsorption of R-6G on Ti02 is not a prerequisite for reaction.

Research paper thumbnail of Investigation of the Sensitivity of Transmission Raman Spectroscopy for Polymorph Detection in Pharmaceutical Tablets

Applied spectroscopy, 2017

Polymorph detection is critical for ensuring pharmaceutical product quality in drug substances ex... more Polymorph detection is critical for ensuring pharmaceutical product quality in drug substances exhibiting polymorphism. Conventional analytical techniques such as X-ray powder diffraction and solid-state nuclear magnetic resonance are utilized primarily for characterizing the presence and identity of specific polymorphs in a sample. These techniques have encountered challenges in analyzing the constitution of polymorphs in the presence of other components commonly found in pharmaceutical dosage forms. Laborious sample preparation procedures are usually required to achieve satisfactory data interpretability. There is a need for alternative techniques capable of probing pharmaceutical dosage forms rapidly and nondestructively, which is dictated by the practical requirements of applications such as quality monitoring on production lines or when quantifying product shelf lifetime. The sensitivity of transmission Raman spectroscopy for detecting polymorphs in final tablet cores was inves...

Research paper thumbnail of Investigating the Effect of Experimental Design and Pre-processing Techniques on Multivariate Figures of Merit

Research paper thumbnail of Classical least squares for quantitative analysis of pharmaceutical solid dosage forms: Part 1—Effect of experimental design

NIR news, 2012

acetaminophen, microcrystalline cellulose, croscarmellose-sodium, magnesium stearate Table 1. Ful... more acetaminophen, microcrystalline cellulose, croscarmellose-sodium, magnesium stearate Table 1. Full-factorial design for the first calibration set (%, w/w). P harmaceutical applications of classical least squares (CLS) for quantitative analysis of near infrared (NIR) data are not common because strict assumptions must be met in order to achieve adequate performance. These assumptions include Beer’s law, linear additivity and constant pathlength. However, more advanced methods have been recently developed that utilise CLS as a starting point and correct for assumptions that may not be satisfied; two common methods include prediction augmented CLS (PACLS) and a CLS/PLS (partial least squares) algorithm. While such methods have been shown to achieve superior prediction performance, they are still based on CLS and caution must be exercised when using them. This series of articles focuses on some practical aspects of using indirect CLS and CLS-based methods for quantitative analysis of NIR spectra, specifically for pharmaceutical applications. For a detailed synopsis of the theory behind CLS, the reader is directed to a recent article published by Fearn and the chemometrics book by Beebe, Pell and Seasholtz.

Research paper thumbnail of An efficient method-development strategy for quantitative chemical imaging using terahertz pulse spectroscopy

Journal of Pharmaceutical Innovation, 2006

The purpose of our research was to investigate efficient procedures for generating multivariate p... more The purpose of our research was to investigate efficient procedures for generating multivariate prediction vectors for quantitative chemical analysis of solid dosage forms using terahertz pulse imaging (TPI) reflection spectroscopy. A set of calibration development and validation tablet samples was created following a ternary mixture of anhydrous theophylline, lactose monohydrate, and microcrystalline cellulose (MCC). Spectral images of one side of each tablet were acquired over the range of 8 cm-1 to 60 cm-1. Calibration models were generated by partial least-squares (PLS) type II regression of the TPI spectra and by generating a purecomponent projection (PCP) basis set using net analyte signal (NAS) processing. Following generation of the calibration vectors, the performance of both methods at predicting the concentration of theophylline, lactose, and MCC was compared using the validation spectra and by generating chemical images from samples with known composition patterns. Sensitivity was observed for the PLS calibration over the range of all constituents for both the calibration and the validation datasets; however, some of the calibration statistics indicate that PLS overfits the spectra. Multicomponent prediction images verified the spatial and composition fidelity of the system. The NAS-PCP calibration procedure yielded accurate linear predictions of theophylline and lactose, whereas the results for MCC prediction were poor. The poor sensitivity for MCC is assumed to be related to the relative lack of phonon absorption bands, which concurs with the characterization of MCC as being semi-crystalline. The results of this study demonstrate the use of TPI reflection spectroscopy and efficient NAS-PCP for the quantitative analysis of crystalline pharmaceutical materials.

Research paper thumbnail of Adaptive Design Space as an Integrated Component of Quality by Design

Journal of Pharmaceutical Innovation, 2012

ABSTRACT Introduction The US Food and Drug Administration requires pharmaceutical companies to de... more ABSTRACT Introduction The US Food and Drug Administration requires pharmaceutical companies to develop extensive process understanding prior to routine manufacturing of drug products. Through development and validation, drug manufacturers enhance their process understanding and identify an acceptable range of process parameters for each unit operation; this is referred to as the design space. Typically, limited work is done to study the effect of long-term raw material variations on the robustness of the design space. In the present study, the development of a design space for a tablet formulation containing two APIs (acetaminophen, caffeine) through a direct compression process was investigated. Material and Methods A design of experiment including different excipient ratios of microcrystalline cellulose and lactose, two croscarmellose sodium levels, four tablet compression forces, and four blend parameters was created using an industrial-size press to define a knowledge space. Quality attributes (disintegration time, dissolution, radial tensile strength, and friability) were measured and a design space derived. In order to test the robustness of the design space, raw material properties, specifically particle size of acetaminophen and ratio of lactose anhydrous to monohydrate, were modified. Also, compression parameters were varied. Results Tablets were analyzed for relevant critical quality attributes (CQAs) to investigate how variability in raw materials can change the design space. The modification of the process parameters was used as a means of compensating for raw material variability to produce tablets that met CQA requirements. An adaptive design space approach based on the adaptation of critical process parameters is proposed to facilitate the creation of tablets meeting specifications despite variation in raw material properties.

Research paper thumbnail of Efficient Near-Infrared Spectroscopic Calibration Methods for Pharmaceutical Blend Monitoring

Journal of Pharmaceutical Innovation, 2011

Near-infrared (NIR) spectroscopy is an important analytical tool for online process monitoring of... more Near-infrared (NIR) spectroscopy is an important analytical tool for online process monitoring of pharmaceutical unit operations. Traditionally, the development and maintenance of robust, precise, and accurate quantitative NIR calibrations requires a substantial investment for the creation of sample sets. This study demonstrates the ability to develop efficient NIR calibrations using reduced sample sets. Prediction performance of several multivariate algorithms was compared on two different NIR spectrometers for pharmaceutical blend monitoring. Classical least-squares (CLS)-based algorithms took advantage of pure component scans to produce the most sensitive quantitative calibrations using reduced sample sets when compared to partial least squares (PLS) regression and two nonlinear methods. The PLS algorithm and the nonlinear methods produced models with low error but lacked the sensitivity needed to model subtle blending trends. The CLS-based methods produced models with adequate sensitivity for blend monitoring. The robustness of the CLS-based methods was further demonstrated in the ease of transfer between instruments using only a bias correction of the predictions.

Research paper thumbnail of Comparison of Terahertz Pulse Imaging and Near-Infrared Spectroscopy for Rapid, Non-Destructive Analysis of Tablet Coating Thickness and Uniformity

Journal of Pharmaceutical Innovation, 2007

In this study, coating thickness and uniformity of production-scale pharmaceutical tablets were i... more In this study, coating thickness and uniformity of production-scale pharmaceutical tablets were investigated using near-infrared (NIR) and terahertz pulse imaging (TPI) spectroscopy. Two coating formulations were considered; samples for each coating formulation were obtained at 0, 1, 2, 3, 4, and 5% coating weight. NIR spectra were collected, and regressed with respect to batch percent weight gain. While standard errors of calibration (SEC) less than 0.5% were observed for both formulations, the calibrations were not specifically sensitive to coating thickness. An upper limit for NIR coating thickness analysis was estimated to be~4-6% weight gain for this system. The NIR calibrations were used as filters to choose subsets of samples for TPI, and as a secondary method for validation of TPI results. The features in TPS time-domain spectra result when an incident THz plane wave meets a refractive index interface, which may be converted to an absolute distance. Therefore, assuming that a discernible difference in refractive index between coating material and core exists, coating thickness can be determined non-destructively. Coating thickness measurements from TPI and NIR spectroscopy were compared to estimate the lower limit for quantitative TPI coating analysis; a lower limit of~35 mm was obtained for this system. Optical microscopy was employed on a subset of samples to validate absolute thickness values; reasonable correlations between the three methods were obtained. TPI was considered advantageous relative to the other methods, as similar results were obtained without the need for destructive sampling or empirical calibration development.

Research paper thumbnail of Hybrid Controls Combining First-Principle Calculations with Empirical Modeling for Fully Automated Fluid Bed Processing

Journal of Pharmaceutical Innovation, 2012

Introduction The US Food and Drug Administration has encouraged the use of the guidelines put for... more Introduction The US Food and Drug Administration has encouraged the use of the guidelines put forth by the International Conference on Harmonization (ICH-Q8) that allow for operational flexibility within a validated design space. These guidelines make possible fully automated control systems that incorporate information about a process back into the system to adjust process variables to consistently hit product quality targets. Traditionally, fluid bed control systems have used either first-principle calculations to control the internal process environment or purely empirical methods that incorporate online process measurements with process models and real-time data management. This study demonstrates the development and implementation of a novel hybrid control system that combines the two traditional approaches. Material and Methods Granules containing gabapentin, and hydroxypropyl cellulose were prepared in a high-shear granulator and dried in a fluid bed processing system (Diosna Minilab). The fluid bed dryer was outfitted with near-infrared (NIR), pressure, temperature, and flow sensors which were connected to a distributed control system (DCS) that was used to exercise control of the system. The control system itself consisted of a Delta V DCS (Emerson Process Management, Equipment and Controls, Inc., Lawrence, PA, USA) that was used to interface the fluid bed dryer with SynTQ (Optimal, Bristol, UK). The dried granules were characterized by median particle size and quantity of gabapentin lactam formed (a chemical degradant). Results Control of a fluid bed dryer utilizing both a firstprinciple control strategy and empirical model-based controls was demonstrated. First-principle control was based on an environmental equivalency factor model to maintain a constant thermodynamic environment. Empirical models included a pressure drop across the bed and NIR measurement of water content. These systems were combined effectively to consistently dry granules prepared by high-shear wet granulation. Utilization of this system greatly reduced the number of experiments necessary to characterize the performance of the system and facilitated control of the process with respect to the two properties of interest, median particle size and chemical stability during drying.

Research paper thumbnail of Online Monitoring of Pharmaceutical Materials Using Multiple NIR Sensors—Part II: Blend End-point Determination

Journal of Pharmaceutical Innovation, 2013

The effect of various blend end-point algorithms on the observed blending time of pharmaceutical ... more The effect of various blend end-point algorithms on the observed blending time of pharmaceutical powders and content uniformity of subsequent tablets was investigated for a five-component system. The blending process was monitored online, in real time, using two near-infrared sensors. Algorithms based on the standard deviation, average, and distributions of concentration predictions were tested for all major blend constituents, respectively. The potential to combine sensor outputs in the end-point decision was contrasted by the consideration of the two sensor outputs individually or simultaneously. The algorithms employed demonstrated highly variable end-points when compared with the final tablet quality, although blends were deemed to have reached homogeneity faster when only the active ingredient was considered. Some algorithms proved to be either too sensitive to local mixing and demixing phenomena or not sensitive enough, yielding results not consistent with the observed tablet content uniformity. Results showed that the choice of an end-point algorithm must be directed by the product of interest (nature of the active, therapeutic window, etc.), the particular characteristics that the delivery forms should have (immediate release, sustained release), and most significantly, the purpose of blending. A single algorithm is not expected to be adequate across all formulations. However, as the complexity of the blending process increases (multiple sensors, trends of multiple ingredients to follow, etc.) the decision process becomes more complex with not only calibration maintenance issues to consider, but also calibration transfer, relevance of the criteria for the actives, and the desired final product properties.

Research paper thumbnail of Improvement of pharmaceutical near infrared calibrations by empirical target distribution optimisation

Journal of Near Infrared Spectroscopy, 2011

ABSTRACT Using process samples to develop near infrared prediction models can generate artefacts ... more ABSTRACT Using process samples to develop near infrared prediction models can generate artefacts in the calibration set, potentially reducing model performance. Due to the inherent variability of manufacturing processes, the assumption that all samples from a given batch have the same concentration for the compound of interest is incorrect. A tablet press will produce compacts with different drug concentrations, distributed around a nominal value, due to mechanical effects, vibrations and powder segregation that occur in the hopper. Differences in tablet crushing strength may also be observed for those same reasons. Consequently, using such samples and their associated nominal concentrations for the development of a calibration model for the prediction of content uniformity of tablets might produce models with rather high error while able to cope with a large range of process variability. The objective of this work was to investigate empirical approaches for optimising the target (reference) concentrations of prediction samples to best match the underlying spectral variance in an attempt to mitigate interferences that may be responsible for select portions of calibration error. Three approaches were developed. The first used samples presenting a low residual from an original model to re-predict high residual samples. The second approach was an iterative search of the best target value for each sample. The third method used target values generated from a normal distribution. These approaches were compared with the classical slope and bias correction methods on their ability to predict two independent validation sets. While several methods showed significant over-fitting and a high validation error, the iterative search routine enhanced calibration performance compared to post-regression correction methods and was proven to be a viable alternative to current industry practices.

Research paper thumbnail of Characterization of pharmaceutical powder blends using in situ near-infrared chemical imaging

Chemical Engineering Science, 2014

This study demonstrates the capabilities of NIR imaging as an effective tool for characterization... more This study demonstrates the capabilities of NIR imaging as an effective tool for characterization of pharmaceutical powder blends. The powder system used in this small-scale powder blending study consists of acetaminophen (APAP, the model API), microcrystalline cellulose (MCC) and lactose monohydrate. Mixtures of these components were blended for different times for a total of ten time points (ten blending trials). Images collected from multiple locations of the blends were used to generate a qualitative description of the components' blending dynamics and a quantitative determination of both the blending end point and the distribution variability of the components. Multivariate analyses, including pure-component PCA and discriminate PLS, were used to treat the imaging data. A good correlation was observed between imaging results and a UV-Vis monitoring method for determining blend homogeneity. Score images indicated general trends of the distribution of blending constituents for all ten blending trials. The API distribution pattern throughout blending was detected and the API domain size for different blending trials was compared. Blending insights obtained from this study may be transferable to large scale powder blending. Blending process understanding obtained from this study has the potential to facilitate the optimization of blending process control in the future.

Research paper thumbnail of Development of a Neuroscience-oriented "Methods" Course for Graduate Students of Pharmacology and Toxicology

Cell Biology Education, 2006

To provide graduate students in pharmacology/toxicology exposure to, and cross-training in, a var... more To provide graduate students in pharmacology/toxicology exposure to, and cross-training in, a variety of relevant laboratory skills, the Duquesne University School of Pharmacy developed a “methods” course as part of the core curriculum. Because some of the participating departmental faculty are neuroscientists, this course often applied cutting-edge techniques to neuroscience-based systems, including experiments with brain G protein–coupled receptors. Techniques covered by the course include animal handling and behavioral testing, bacterial and mammalian cell culture, enzyme-linked immunosorbent assay, western blotting, receptor binding of radioligands, plasmid DNA amplification and purification, reverse transcriptase-polymerase chain reaction, gel electrophoresis, and UV-visible and fluorescence spectroscopy. The course also encompasses research aspects such as experimental design and record keeping, statistical analysis, and scientific writing. Students were evaluated via laborato...

Research paper thumbnail of Near-Infrared Spectroscopic Investigation of the Hydrothermal Degradation Mechanism of Wood as an Analogue of Archaeological Wood. Part II: Hardwood

Applied Spectroscopy, 2009

Near-infrared (NIR) spectroscopy and chemometrics were applied to analyze the degradation mechani... more Near-infrared (NIR) spectroscopy and chemometrics were applied to analyze the degradation mechanism of hardwood following hydrothermal treatment. NIR spectra, chemical composition, oven-dried density, equilibrium moisture content, compressive Young's modulus parallel to grain, and cellulose crystallinity of artificially degraded beech as an analogue of archaeological wood were systematically measured. Partial least squares (PLS) regression analysis was employed to predict compressive Young's modulus using NIR spectra and various properties as independent variables. Results are also compared with previous data obtained from similar treatment of softwood (Hinoki cypress). The increase in cellulose crystallinity of hardwood during the initial stage of hydrothermal treatment (up to 5 hours) was correlated with an improvement in the mechanical properties of wood. Young's modulus for both hardwood and softwood showed a gradual decrease over five hours of hydrothermal treatment...

Research paper thumbnail of Determination of figures of merit for near-infrared and raman spectrometry by net analyte signal analysis for a 4-component solid dosage system

AAPS PharmSciTech, 2007

Process analytical technology has elevated the role of sensors in pharmaceutical manufacturing. O... more Process analytical technology has elevated the role of sensors in pharmaceutical manufacturing. Often the ideal technology must be selected from many suitable candidates based on limited data. Net analyte signal (NAS) theory provides an effective platform for method characterization based on multivariate figures of merit (FOM). The objective of this work was to demonstrate that these tools can be used to characterize the performance of 2 dissimilar analyzers based on different underlying spectroscopic principles for the analysis of pharmaceutical compacts. A fully balanced, 4-constituent mixture design composed of anhydrous theophylline, lactose monohydrate, microcrystalline cellulose, and starch was generated; it consisted of 29 design points. Six 13-mm tablets were produced from each mixture at 5 compaction levels and were analyzed by near-infrared and Raman spectroscopy. Partial least squares regression and NAS analyses were performed for each component, which allowed for the computation of FOM. Based on the calibration error statistics, both instruments were capable of accurately modeling all constituents. The results of this work indicate that these statistical tools are a suitable platform for comparing dissimilar analyzers and illustrate the complexity of technology selection.

Research paper thumbnail of Process analytical technology case study part I: Feasibility studies for quantitative near-infrared method development

AAPS PharmSciTech, 2005

*The views presented in this article do not necessarily reflect those of the Food and Drug Admini... more *The views presented in this article do not necessarily reflect those of the Food and Drug Administration.

Research paper thumbnail of Online Monitoring of Pharmaceutical Materials Using Multiple NIR Sensors—Part I: Blend Homogeneity

Journal of Pharmaceutical …