Process Analytical Technology (PAT) is framed with the objective of the design and development of processes to ensure predefined quality of the product at the end of manufacturing. PAT implementation includes better understanding of process, reduction in production time with use of in-line, at-line and on-line measurements, yield improvement and energy and cost reductions. Hot Melt Extrusion process (HME) used in the present work is proving increasingly popular in industry for its continuous and green processing which is beneficial over traditional batch processing. The present work was focused on applications of Raman spectroscopy as off - line and in - line monitoring techniques as a PAT for production of pharmaceutical solid dispersions and co-crystals. Solid dispersions (SDs) of the anti-convulsant Carbamazepine (CBZ) with two pharmaceutical grade polymers have been produced using HME at a range of drug loadings and their amorphous nature confirmed using a variety of analytical techniques. Off-line and in-line Raman spectroscopy has been shown to be suitable techniques for proving preparation of these SDs. Through calibration curves generated from chemometric analysis in-line Raman spectroscopy was shown to be more accurate than off-line measurements proving the quantification ability of Raman spectroscopy as well as a PAT tool. Pure co-crystals of Ibuprofen-Nicotinamide and Carbamazepine-Nicotinamide have been produced using solvent evaporation and microwave radiation techniques. Raman spectroscopy proved its superiority over off-line analytical techniques such as DSC, FTIR and XRD for co-crystal purity determination adding to its key advantage in its ability to be used as an in-line, non-destructive technique.

Orientador: Ronei Jesus Poppi / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-13T21:27:37Z (GMT). No. of bitstreams: 1 Trevisan_MarcelloGarcia_D.pdf: 3921294 bytes, checksum: 59fe442f53af8cb6eaeb8166b7b6980f (MD5) Previous issue date: 2009 / Resumo: Esta tese tem como objetivo desenvolver um conjunto de metodologias que incorporem a utilização da espectroscopia na região do infravermelho médio/próximo com métodos de estatística multivariada (quimiometria) em aplicações com enfoque em Química Analítica de Processos (QAP). Para atingir estes objetivos, este trabalho conta com um capítulo introdutório e três aplicações propriamente ditas. A introdução (capítulo 1) tem como finalidade divulgar a importância da QAP no âmbito acadêmico e indutrial, além de estabelecer algumas terminologias que serão discutidas nos capítulos posteriores. A primeira aplicação deste trabalho envolve o monitoramento de uma reação de biotransformação que foi acompanhada por infravermelho médio e por cromatografia gasosa, sem etapas de extração ou pré-concentração, permitindo o desenvolvimento de um modelo multivariado capaz de fazer a previsão da concentração dos componentes analisados ao longo do tempo. A segunda e terceira aplicações se referem ao monitoramento espectroscópico da reação de transesterificação do óleo de soja na região do infravermelho médio e próximo, respectivamente. Neste segundo trabalho, foi utilizado um acessório de reflectância total atenuada para monitorar a transesterificação. Os resultados foram comparados com aqueles obtidos por RMN H, permitindo a construção de um modelo multivariado que se mostrou robusto para descrever a variação da concentração intra e extra bateladas, por meio de uma correção efetuada pela 'análise de fatores evolucionários¿ (EFA). Na última aplicação, um conjunto maior de bateladas reacionais foi obtido, incorporando-se bateladas consideradas normais e outras com falhas, monitorando-se no infravermelho próximo. Construindo-se o modelo com as bateladas sob-controle, foi possível obter um modelo matemático que permitiu prever a variação da concentração do rendimento intra e extra batelada, além de identificar as falhas ocorridas através da construção de cartas multivariadas de controle. Estes resultados foram avaliados utilizando dois modelos diferentes, propostos pela estatística multivariada para controle de processos / Abstract: The goal of this thesis is to develop a set of research works with a combination of infrared spectroscopy and multivariate statistical techniques (chemometrics) for applications in the Process Analytical Technology (PAT). To reach the goal, this work has an introductory chapter and three applications. The introduction (Chapter 1) contributed to the scientific divulgation of the importance of PAT in the academic and manufactures fields and also had the definition of some terminologies used in the forward chapters. The first application is about the monitoring of a bioreaction based on biotransformation with yeast by middle infrared spectroscopy and by GC-MS, enabling the development of a multivariate model based on Partial Least Squares (PLS). This application was carried out without extraction steps and pre-concentration processes. The second and the third applications consist of a soy bean oil transesterification reaction monitored by middle and near infrared spectroscopy, respectively. In the second application, an attenuated total reflectance (ATR) accessory was used to perform the reaction monitoring. The reaction was also monitored by H NMR, enabling the construction of a robust multivariate model to describe the variation in the analyte concentration intra and extra reaction batches, throughout a temporal correction by Evolving Factor Analysis (EFA). In the last application, a larger set of batches were obtained with batches under control and another ones with process fails. All the batches were monitored by near infrared spectroscopy with an Acousto-Optic Tunable Filter (AOTF). A multivariate model constructed with batches obtained under control conditions allowed a predictable model for sequential batches and also to detect fails around the batches, using the multivariate control charts. The data were evaluated using two different methods proposed to Multivariate Statistical Process Control (MSPC) and compared each other / Doutorado / Quimica Analitica / Doutor em Ciências

Process Analytical Technology (PAT) is framed with the objective of the design and development of processes to ensure predefined quality of the product at the end of manufacturing. PAT implementation includes better understanding of process, reduction in production time with use of in-line, at-line and on-line measurements, yield improvement and energy and cost reductions. Hot Melt Extrusion process (HME) used in the present work is proving increasingly popular in industry for its continuous and green processing which is beneficial over traditional batch processing. The present work was focused on applications of Raman spectroscopy as off - line and in - line monitoring techniques as a PAT for production of pharmaceutical solid dispersions and co-crystals. Solid dispersions (SDs) of the anti-convulsant Carbamazepine (CBZ) with two pharmaceutical grade polymers have been produced using HME at a range of drug loadings and their amorphous nature confirmed using a variety of analytical techniques. Off-line and in-line Raman spectroscopy has been shown to be suitable techniques for proving preparation of these SDs. Through calibration curves generated from chemometric analysis in-line Raman spectroscopy was shown to be more accurate than off-line measurements proving the quantification ability of Raman spectroscopy as well as a PAT tool. Pure co-crystals of Ibuprofen-Nicotinamide and Carbamazepine-Nicotinamide have been produced using solvent evaporation and microwave radiation techniques. Raman spectroscopy proved its superiority over off-line analytical techniques such as DSC, FTIR and XRD for co-crystal purity determination adding to its key advantage in its ability to be used as an in-line, non-destructive technique.

Innovations and process understanding is the current focus in pharmaceutical industry. The objective of this research was to explore application of high power ultrasound in the slurry crystallisation and application of low power ultrasound (3.5 MHz) as process analytical technology (PAT) tool to understand pharmaceutical processing such as hot melt extrusion. The effect of high power ultrasound (20 kHz) on slurry co-crystallisation of caffeine / maleic acid and carbamazepine / saccharin was investigated. To validate low power ultrasound monitoring technique, it was compared with the other techniques (PAT tools) such as in-line rheology and in-line NIR spectroscopy. In-line rheological measurements were used to understand melt flow behaviour of theophylline / Kollidon VA 64 system in the slit die attached to the hot melt extruder. In-line NIR spectroscopic measurements were carried out for monitoring any molecular interactions occurring during extrusion. Physical mixtures and the processed samples obtained from all experiments were characterised using powder X-ray diffraction, thermogravimetry analysis, differential scanning calorimetry, scanning Electron Microscopy, dielectric spectroscopy and high performance liquid chromatography, rotational rheology, fourier transform infrared spectroscopy and near infrared spectroscopy. The application of high power ultrasound in slurry co-crystallisation of caffeine / maleic acid helped in reducing equilibrium time required for co-crystal formation. During carbamazepine / saccharin co-crystallisation high power ultrasound induced degradation of carbamazepine was negligible. Low power ultrasound can be used as a PAT tool as it was found to be highly sensitive to the changes in processing temperatures and drug concentration.

Yes / A transflectance near infra red (NIR) spectroscopy approach has been used to simultaneously measure drug and plasticiser content of polymer melts with varying opacity during hot melt extrusion. A high temperature reflectance NIR probe was mounted in the extruder die directly opposed to a highly reflective surface. Carbamazepine (CBZ) was used as a model drug, with polyvinyl pyrollidone-vinyl acetate co-polymer (PVP-VA) as a matrix and polyethylene glycol (PEG) as a plasticiser. The opacity of the molten extrudate varied from transparent at low CBZ loading to opaque at high CBZ loading. Particulate amorphous API and voids formed around these particles were found to cause the opacity. The extrusion process was monitored in real time using transflectance NIR; calibration and validation runs were performed using a wide range of drug and plasticiser loadings. Once calibrated, the technique was used to simultaneously track drug and plasticiser content during applied step changes in feedstock material. Rheological and thermal characterisations were used to help understand the morphology of extruded material. The study has shown that it is possible to use a single NIR spectroscopy technique to monitor opaque and transparent melts during HME, and to simultaneously monitor two distinct components within a formulation.

Yes / Real time measurement of melt rheology has been investigated as a Process Analytical Technology (PAT) to monitor hot melt extrusion of an Active Pharmaceutical Ingredient (API) in a polymer matrix. A developmental API was melt mixed with a commercial copolymer using a heated twin screw extruder at different API loadings and set temperatures. The extruder was equipped with an instrumented rheological slit die which incorporated three pressure transducers flush mounted to the die surface. Pressure drop measurements within the die at a range of extrusion throughputs were used to calculate rheological parameters such as shear viscosity and exit pressure, related to shear and elastic melt flow properties respectively. Results showed that the melt exhibited shear thinning behavior whereby viscosity decreased with increasing flow rate. Increase in drug loading and set extrusion temperature resulted in a reduction in melt viscosity. Shear viscosity and exit pressure measurements were found to be sensitive to API loading. These findings suggest that this technique could be used as a simple tool to measure material attributes in-line, to build better overall process understanding for hot melt extrusion.

Yes / Three-dimensional printing (3DP) has the potential to cause a paradigm shift in the manufacture of pharmaceuticals, enabling personalised medicines to be produced on-demand. To facilitate integration into healthcare, non-destructive characterisation techniques are required to ensure final product quality. Here, the use of process analytical technologies (PAT), including near infrared spectroscopy (NIR) and Raman confocal microscopy, were evaluated on paracetamol-loaded 3D printed cylindrical tablets composed of an acrylic polymer (Eudragit L100-55). Using a portable NIR spectrometer, a calibration model was developed, which predicted successfully drug concentration across the range of 4–40% w/w. The model demonstrated excellent linearity (R2 = 0.996) and accuracy (RMSEP = 0.63%) and results were confirmed with conventional HPLC analysis. The model maintained high accuracy for tablets of a different geometry (torus shapes), a different formulation type (oral films) and when the polymer was changed from acrylic to cellulosic (hypromellose, HPMC). Raman confocal microscopy showed a homogenous drug distribution, with paracetamol predominantly present in the amorphous form as a solid dispersion. Overall, this article is the first to report the use of a rapid ‘point-and-shoot’ approach as a non-destructive quality control method, supporting the integration of 3DP for medicine production into clinical practice. / Open Access funded by Engineering and Physical Sciences Research Council United Kingdom (EPSRC), UK for their financial support (EP/L01646X).

Twin screw wet granulation (TSG) has been studied as a continuous manufacturing alternative to batch granulation for nearly twenty years. One of the main differences between batch granulation and TSG lies in the exiting granules being presented as a bimodal particle size distribution (PSD) in the latter case. Current process analytical technologies (PAT) can monitor a monomodal distribution well but there have been no techniques disclosed in the public domain so far that can accurately monitor this unusually shaped PSD. Acoustic emissions (AE) has been identified as a PAT of interest due to its ease of use (lack of calibration), low cost, and non-invasive design relative to other PATs used for monitoring PSDs. Hence the goal of this thesis was to develop AE as a process analytical technology (PAT) capable of estimating the full distribution of produced granules by TSG in real time. The first research study of this thesis focused on the development of the new technology. The AE PAT consisted of an acoustic sensor, an impact plate, and software to convert the time-domain signal of particle collisions into a time-averaged frequency-domain spectrum to be subsequently used to estimate a weight-averaged particle size distribution. A novel and much required addition to the PAT was inclusion of a digital filter based on particle mechanics parameters to overcome auditory masking which hindered accurately converting the cumulative sounds of impact into a PSD. The PAT was tested in this study with granulated lactose monohydrate and with the new digital filter, obtaining a maximum error of 1 wt% across all particle sizes tested. In the second research study, as more formulations commonly used in the industry were tested, the filter proved unable by itself to account for the differences in impact mechanics and therefore needed to be modified to incorporate the more inelastic behaviour now being seen. Two micromechanical models were explored, and the Walton-and-Braun model was found to be the most suitable for the AE PAT – reducing its error from 8 wt% down to 2.75 wt% across four formulations producing coefficients of restitution from 0.79 to 0.24. In the last research study in this thesis, the now-functional inline PAT was used to reveal mechanistic details related to the transition state in granulation as a TSG starts up, to improve the field’s understanding of the granulation mechanism. The technique was able to estimate the PSD over much shorter periods of material collection compared to sieving, allowing the evolution of the PSD as a function of time to be examined for varying degrees of fill (DF) and liquid-to-solids ratios. It was determined that the time to steady state, at both DF tested, occurred at approximately 5 times the mean residence time of the process by both PAT and sieving analyses. Particle sizes between 102-2230 μm were then tracked as a function of time below 120 s and variations of granule growth were seen for each degree of fill which added to the understanding of the granulation mechanism. This PAT shows great promise as a monitoring tool to implement quality by design principles for TSG in pharmaceutical manufacturing. / Thesis / Doctor of Philosophy (PhD)

Optical methods play an important role in process analytical technologies (PAT). Four examples of optical process and quality sensing (OPQS) are presented, which are based on three important experimental techniques: near-infrared absorption, luminescence quenching, and a novel method, photon density wave (PDW) spectroscopy. These are used to evaluate four process and quality parameters related to beer brewing and polyurethane (PU) foaming processes: the ethanol content and the oxygen (O2) content in beer, the biomass in a bioreactor, and the cellular structures of PU foam produced in a pilot production plant.

To manufacture safe, effective and affordable medicines with greater efficiency, process analytical technology (PAT) has been introduced by the Food and Drug Agency to encourage the pharmaceutical industry to develop and design well-understood processes. PAT requires chemical imaging techniques to be used to collect process variables for real-time process analysis. Multivariate statistical analysis tools and process control tools are important for implementing PAT in the development and manufacture of pharmaceuticals as they enable information to be extracted from the PAT measurements. Multivariate statistical analysis methods such as principal component analysis (PCA) and independent component analysis (ICA) are applied in this thesis to extract information regarding a pharmaceutical tablet. ICA was found to outperform PCA and was able to identify the presence of five different materials and their spatial distribution around the tablet.Another important area for PAT is in improving the control of processes. In the pharmaceutical industry, many of the processes operate in a batch strategy, which introduces difficult control challenges. Near-infrared (NIR) spectroscopy is a non-destructive analytical technique that has been used extensively to extract chemical and physical information from a product sample based on the scattering effect of light. In this thesis, NIR measurements were incorporated as feedback information into several control strategies. Although these controllers performed reasonably well, they could only regulate the NIR spectrum at a number of wavenumbers, rather than over the full spectrum.In an attempt to regulate the entire NIR spectrum, a novel control algorithm was developed. This controller was found to be superior to the only comparable controller and able to regulate the NIR similarly. The benefits of the proposed controller were demonstrated using a benchmark simulation of a batch reactor.