Multivariate analysis of a direct compression pharmaceutical tablets continuous manufacturing process

Tese de mestrado, Engenharia Farmacêutica, Universidade de Lisboa, Faculdade de Farmácia, 2018In the last decade, there have been significant advances in the areas of engineering and science, allowing the implementation of pharmaceutical continuous manufacturing (CM). These advances are coupled with the adoption of the quality by design paradigm for pharmaceutical development and the advances on process analytical technology to improve design, analysis and control. These advances have contributed significantly to advances on the design and manufacturing of pharmaceutical, namely the adoption of continuous processing. Continuous manufacturing can be used for the production of medicines in multiple pharmaceutical forms. If advances are being operated in the field of continuous manufacturing, it is also true that substantial efforts are still required to fully understand how this manufacturing paradigm can be efficiently integrated within industry, for full advantages to be achieved. This work had the objective of pursuing the goal to better understand how materials behave under continuous processing. It aimed at evaluating the performance of a direct compression process for tablets production in continuous mode. Direct compression, a unit operation especially interesting for the manufacturing of tablets, has the ability to be efficiently integrated within a continuous manufacturing framework. The investigated continuous manufacturing process resourced to the continuous table production line located at the PROMIS Center at the School of Pharmacy of the University of Eastern Finland (Kuopio, Finland). The line was configured for direct compression purposes, encompassing multiple gravimetric feeders, a continuous mixer and a tableting machine. Tablets monitoring was accomplished with near-infrared spectroscopy. A formulation containing simultaneously caffeine (2.6%) and paracetamol (20%) was selected for this study. Selected process variables were varied according to an experimental design in order to understand the effects on tablets' properties. Mixer speed (350-1200 rpm), feed rate (5-10 kg/h) and the existence or not of premixture were the selected process variables. Tablets were evaluated according to the weight, hardness and thickness. Feed rate demonstrated as was expected to be fundamental for the stability of the direct compression process. For instance, experiments carried out at lower feed rates (lower than 5kg/h) revealed poor fluidity and tablets were not acceptable. The influence of process variables on tablets properties was modelled by partial least squares regression. Tablets mass is significantly affected, in a positive way, by the speed of the mixer and negatively affected by the feed rate. The range of coefficients of determination for the calibration (R2) and test (Q2) for the three responses were 0.78-0.94 for R2 and 0.56-0.88 for Q2. Near-infrared spectra collected from tablets allowed the development of PLS models for the caffeine and paracetamol content. Validation experiments reveal that the root mean square errors of prediction for caffeine and paracetamol were respectively 11.96% and 10.48%.Historicamente, a produção em descontínuo de formas de dosagem sólidas teve grande sucesso e dominou a indústria farmacêutica. Durante muito tempo a indústria entendeu não haver motivação para inovar no sentido do desenvolvimento de novas tecnologias de fabrico, dada a rentabilidade desta forma de produção. No entanto, atualmente, na era pós-blockbuster, tendo em conta que os custos dos materiais, durante o desenvolvimento de medicamentos, são significativos, que novos medicamentos, provavelmente, serão fabricados em quantidades muito menores e que, para novos tratamentos, o desenvolvimento de um processo de produção comercial não é garantido, é cada vez mais reconhecida a necessidade de novos paradigmas de produção. A produção em contínuo surge como uma alternativa à produção em (semi-) descontínuo e tem por objetivo aumentar a eficácia e a eficiência na produção farmacêutica. Esta nova abordagem exige que a indústria farmacêutica, primária e secundária, aborde de maneira diferente a forma como desenvolve e otimiza os processos de fabrico para produção de substâncias ativas e formulações farmacêuticas. É fundamental a compreensão do processo como um todo, bem como inovação ao nível empresarial. É crucial entender e minimizar a variabilidade das matérias-primas, executar medições contínuas durante o processo, definir uma amostragem representativa e caracterizar a propagação de alterações e distúrbios através do sistema. Ao contrário da produção em descontínuo, em que o controlo local de cada equipamento é considerado suficiente, na produção em contínuo, o controlo local é não só obrigatório, como todo o fluxo do processo deve ser coordenado e equipado com sistemas de controlo de segundo nível, supervisionando e controlando todas as operações unitárias. Monitorizar e controlar a composição de um produto durante todo o seu processo de fabrico, com a finalidade de alcançar a qualidade e robustez pretendida, é um importante objetivo a ser alcançado numa produção em modo contínuo. Um passo importante para a implementação da produção em contínuo foi dado em 2004, quando a Food and Drug Administration publicou uma diretriz de tecnologias analíticas de processo (PAT), que promove a adoção de tecnologias inovadoras para realizar medições oportunas em atributos críticos de qualidade de materiais brutos e em processo, permitindo alcançar uma melhor compreensão e controlo do processo. O conceito PAT está intimamente ligado à ideia do desenho pela qualidade a qual considera não apenas a avaliação de risco para a qualidade e o conhecimento sobre o processo, mas também a forma como as operações unitárias afetam a qualidade e estabilidade do produto. A espectroscopia de infravermelho próximo tem sido utilizada como uma ferramenta de controlo PAT. Esta ferramenta de controlo combinada com a análise de dados multivariados tornou-se uma ferramenta interessante na análise farmacêutica, tanto a nível qualitativo como quantitativo. Esta tese foi realizada utilizando a linha de produção contínua de comprimidos do PROMIS Centre (Escola de Farmácia, Universidade do Leste da Finlândia) em Kuopio, Finlândia. A monitorização do processo foi realizada em tempo real, por um sistema de infravermelho próximo com uma câmara espectral SPECIM e um sensor ImSpector (SPECIM, Finlândia). Com o propósito de avaliar o processo de compressão direta em modo contínuo foram definidas um conjunto de experiências variando a velocidade do misturador (350 a 1200 rpm), fluxo (5 a 10 kg/h). Foi ainda avaliada importância de existência de etapa de pré-mistura. Como respostas foram avaliados a massa, dureza e espessura dos comprimidos. A análise de componentes principais foi usada como método de análise exploratória dos espetros obtidos, assim como para identificar medições atípicas. A monitorização da taxa de alimentação, elemento fundamental na compressão direta, decorreu sem grandes variações em relação aos set points definidos para cada matéria prima. Deste modo, os dados analisados, relativamente à taxa de alimentação de cafeína e paracetamol, permitiram perspetivar que as concentrações dos mesmos, nos comprimidos seriam as esperadas. Durante a realização das experiências ficou ainda visível que as que tinham uma taxa de alimentação de 5 kg/h, evidenciavam uma fraca fluidez, já com valores de 10 kg/h a fluidez melhorava significativamente. De acordo com os modelos de regressão múltipla (PLS) para avaliar a influência das variáveis alteradas nas respostas selecionadas, a massa de cada comprimido é significativamente afetada, de uma forma positiva, pela velocidade do misturador e negativamente afetada pela taxa de fluxo. Para além disso, este modelo prevê que a dureza seja afetada pela existência ou não de pré-mistura. Para os três modelos o R2 não se verificou muito elevado, variando entre 0.78 e 0.94. Relativamente ao valor de Q2, este variou entre 0.56 e 0.88, valores um pouco a baixo dos valores ideais. Assim, pode-se concluir que este não será um modelo com uma capacidade preditiva muito elevada. Relativamente aos modelos PLS, baseados nos espetros NIR para estimar a concentração de paracetamol e cafeina, foi possível concluir que a capacidade preditiva foi boa com erros quadrados médios (RMSEP) de 12 e 10% para o paracetamol e cafeína respetivamente.The experimental work was performed in PROMIS continuous tablet manufacturing line (University of Eastern Finland, School of Pharmacy, Kuopio, Finland). All the facilities, equipments, materials and support were gently provided by University of Eastern Finland

Continuous blending of dry pharmaceutical powders

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 269-279).Conventional batch blending of pharmaceutical powders coupled with long quality analysis times increases the production cycle time leading to strained cash flows. Also, scale-up issues faced in process development causes delays in transforming a drug in research to a drug under commercial production. Continuous blending is as an attractive alternative design choice to batch process and is examined in this work. This work proposes to examine the feasibility of applying continuous blending in pharmaceutical manufacturing. Two kinds of blenders, a double helical ribbon blender and a Zigzag R blender were chosen as experimental systems representing high shear and moderate shear equipment. This work first focuses on developing a process understanding of continuous blending by examining the ow behavior of powders in experimental blenders using impulse stimulus response experiments and subsequent residence time distribution analysis. Powder ow behavior was modeled using an residence time distribution models like axial dispersion models. These ow behavior studies were followed by blender performance studies. The dependence of the mixing performance of the continuous blending system on different operational variables like rotation rates of mixing elements and raw material properties like particle size, shape and cohesion were studied. Mean residence time and time period of fluctuation in the concentration of active ingredient coming at the inlet were the two most important operational variables that affected blender performance. Larger particles and particles with less cohesion were seen to mix well with higher dispersion coefficients in a ribbon blender. A residence time distribution based process model for continuous blending was investigated and shown to depict the process well within experimental errors in determining the parameters of the residence time distribution model.(cont.) The predictive capability of the process model was found to dependent on the scale of scrutiny of the powder mixture in the blender. Choosing the correct scale of scrutiny was demonstrated to be of critical importance in determination of blend quality. Growing pressures on pharmaceutical industry due to patent expirations has forced manufacturers to look beyond the US and EU for potential manufacturing locations in addition to invest in novel manufacturing methods and technologies. The capstone work in this thesis proposes a framework that managers of pharmaceutical and biologics manufacturing can utilize to identify critical issues in globalization of manufacturing and in making strategic manufacturing location decisions.by Lakshman Pernenkil.Ph.D

On The Application Of Computational Modeling To Complex Food Systems Issues

Transdisciplinary food systems research aims to merge insights from multiple fields, often revealing confounding, complex interactions. Computational modeling offers a means to discover patterns and formulate novel solutions to such systems-level problems. The best models serve as hubs—or boundary objects—which ground and unify a collaborative, iterative, and transdisciplinary process of stakeholder engagement. This dissertation demonstrates the application of agent-based modeling, network analytics, and evolutionary computational optimization to the pressing food systems problem areas of livestock epidemiology and global food security. It is comprised of a methodological introduction, an executive summary, three journal-article formatted chapters, and an overarching discussion section. Chapter One employs an agent-based computer model (RUSH-PNBM v.1.1) developed to study the potential impact of the trend toward increased producer specialization on resilience to catastrophic epidemics within livestock production chains. In each run, an infection is introduced and may spread according to probabilities associated with the various modes of contact between hog producer, feed mill, and slaughter plant agents. Experimental data reveal that more-specialized systems are vulnerable to outbreaks at lower spatial densities, have more abrupt percolation transitions, and are characterized by less-predictable outcomes; suggesting that reworking network structures may represent a viable means to increase biosecurity. Chapter Two uses a calibrated, spatially-explicit version of RUSH-PNBM (v.1.2) to model the hog production chains within three U.S. states. Key metrics are calculated after each run, some of which pertain to overall network structures, while others describe each actor’s positionality within the network. A genetic programming algorithm is then employed to search for mathematical relationships between multiple individual indicators that effectively predict each node’s vulnerability. This “meta-metric” approach could be applied to aid livestock epidemiologists in the targeting of biosecurity interventions and may also be useful to study a wide range of complex network phenomena. Chapter Three focuses on food insecurity resulting from the projected gap between global food supply and demand over the coming decades. While no single solution has been identified, scholars suggest that investments into multiple interventions may stack together to solve the problem. However, formulating an effective plan of action requires knowledge about the level of change resulting from a given investment into each wedge, the time before that effect unfolds, the expected baseline change, and the maximum possible level of change. This chapter details an evolutionary-computational algorithm to optimize investment schedules according to the twin goals of maximizing global food security and minimizing cost. Future work will involve parameterizing the model through an expert informant advisory process to develop the existing framework into a practicable food policy decision-support tool

Development and Applications of a Novel Intermittent Solids Feeder for Pyrolysis Reactors

This PhD research addresses the challenge of feeding biomass residues into fluidized bed reactors for pyrolysis, through the development of a novel intermittent solid slug feeder, both for laboratory-scale and large-scale reactors. The new feeder can successfully handle biomass residues that are either too cohesive or thermally sensitive for traditional feeders. To optimize the novel feeder performance, a model for the pulsating solids flow was developed from experimental data collected with ideal slugs, as well as real biomass flow. The model was validated using both a laboratory-scale (\u3c 10 kg/hr) and large-scale feeder (\u3e 250 kg/hr). Several important variables were identified. They include the material flow properties, the pulse gas pressure and volume, and the feeding tube length and material. The goals of this study were to (a) characterize the fundamental dynamic behavior of the biomass slugs in the feeder, (b) maximize the solid-to-gas feeding ratio, and thus minimize energy consumption and cost, (c) minimize the accumulation of “straggler” biomass material in the feeding tube between pulses, and thus prevent biomass heating in the feeding tube, which can induce plugging, and (d) develop and validate a predictive model for the slug velocity at any location in the feeding tube, which can be applied to feeder design for any biomass feedstock. An advantage of the new large-scale feeder technology is that it can handle larger biomass particles than traditional feeder technologies. An issue with large particles is that they require relatively long drying, which must be optimized. A model was therefore developed for drying, which takes shrinkage, and internal and external mass transfer limitations into account. The thesis is supplemented with additional work based on the application of the novel feeder for pyrolysis studies with various biomass residues. The feeder technology made it possible to perform the first ever pyrolysis studies, in industrially-relevant equipment, on pure meat and bone meal residue, and on unmodified and undiluted Kraft lignin. Appendices include a business case-study of the implementation of the technologies developed in this thesis on large-scale pyrolysis and an additional pyrolysis study on tucumã seeds, which utilized the novel feeder

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Exploration of parameters for the continuous blending of pharmaceutical powders

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 113-119).The transition from traditional batch blending to continuous blending is an opportunity for the pharmaceutical industry to reduce costs and improve quality control. This operational shift necessitates a deeper understanding of the mixing process informed by particle dynamics and variable interdependencies. The thesis aims to establish a framework for characterizing and improving continuous pharmaceutical blending using a tiered experimental methodology and multivariate analysis. This parameter space exploration attempts to reconcile previous research within the context of cohesive pharmaceutical powders and develop general design principles for maximizing blender performance. A design of experiments was conducted to determine mixing performance with respect to three factors - physical design, operating parameters, and material properties. Multivariate analysis using projections to latent structures was employed to quantify the effect of raw and intermediate variables on the variance reduction ratio. Significant parameters identified included the choice of API, fill fraction, the number of blade passes, the mean residence time, the Bodenstein number, and the period of input feed fluctuations. The results highlight the importance of shear and radial mixing for cohesive powders, which suggest that one-dimensional axial models common in blending literature may not be a sufficient theoretical framework for pharmaceutical applications. The research yielded several insights into design principles for optimizing blending performance. Increasing mean residence time and radial mixing create more robust processing by reducing the impact of material properties and fluctuations in feed consistency. The variance reduction ratio can be improved in a cost-effective manner by determining the fill fraction which maximizes intermediate metrics such as space time, mean residence time, and the number of blade passes. Multivariate analysis was demonstrated to be a practical tool for parameter space optimization and a promising technique for characterizing the effect of material properties on processing.by Ben Chien Pang Lin.Ph.D

Advanced control schemes for wind power plants and renewable energy-based islanded microgrids

Renewable energy sources are increasingly integrated in power grids, creating significant challenges for control and system operation. Among various renewable energy sources, wind power is one of the dominant forms, mainly generated from large-scale transmission-connected wind power plants (WPPs). The grid-connected WPPs are required to follow grid codes to maintain a predefined power factor range under normal operation and supply required reactive power under faulty conditions. To meet grid code requirements, a WPP control architecture is developed in this thesis. The control system consists of a central WPP controller and a local wind turbine generator (WTG) controller, both operate in the voltage control mode. Therefore, the controller can respond faster and is robust to communication failures. Under normal operating conditions, the proposed controller regulates the WPP’s operation within its steady-state reactive power capability and meets the power factor limits. Under faulty conditions, the controller forces the WPP to its maximum capability to contribute more reactive power support to the grid. Two mathematical models representing the steady-state and maximum reactive power capability of the WPP are developed through regression and analytic approaches, respectively. In the second part of the thesis, a model predictive control (MPC)-based distributed generation (DG) controller is proposed to regulate the voltage and frequency at the point of common coupling (PCC) in an islanded microgrid. A data-driven input-output Box-Jenkins polynomial predictive model for DG control is developed using the Gauss-Newton-based nonlinear least square method with the prediction optimization focus. The model inputs are direct- and quadrature-axis components of the control signal, and the model outputs are deviations of the voltage and frequency from their nominal values at the PCC. The proposed MPC controller operates using the PCC data and does not require the microgrid’s central controllers or DG-to-DG communication networks. It can effectively compensate voltage and frequency deviations at the PCC and ensure proportional reactive power sharing among DGs without a secondary controller and a virtual impedance loop. The integrated Kalman filter in the MPC structure enables a robust controller design when subjected to impedance variations and measurement noises