1,720,968 research outputs found
Digitalizing pharmaceutical development and manufacturing: advanced mathematical modeling for operation design, process monitoring and process control
Full text linkFor pharmaceutical companies, the economic return on investments on research and development has recently been decreasing, mainly due to the large cost (~2 billion) and time (~10 years) for bringing a new product to the market in the latest years. At the same time, an alarming number of drug shortages and recalls for quality concerns has been registered by regulators. These events affect companies, from the financial side, but also patients, who might experience increasingly large costs for drugs, or unavailability of essential medicines. The lack of adoption of modern technology and approaches for pharmaceutical development and manufacturing is acknowledged as a main actor for these events. A recent example is the sluggish rollout of COVID-19 vaccines, which has been significantly affected by technological limitations in pharmaceutical development and manufacturing, especially regarding process scale-up.
In the early 2000s, a modernization momentum of the sector was initiated, culminated into the Quality-by-Design (QbD) initiative. Within the QbD initiative, regulators defined a novel pharmaceutical development and manufacturing paradigm, rooted in product and process understanding and based on sound science and quality risk management.
However, much effort is still needed by the pharmaceutical sector to catch up with other industries on the adoption of modern development and manufacturing technologies. Recently, QbD is evolving towards a new phase, that features the adoption of novel emerging technology, the most important ones being continuous processing, active (i.e., closed-loop) quality control and increased use of mathematics.
Mathematical modeling can be used for developing digital tools pivotal to the efficient and rapid implementation of QbD, and its adoption has also been recommended by regulators with dedicated guidelines. Mathematical methodologies can support all stages of the pharmaceutical life cycle, and enable the implementation of continuous processing and active quality control. Within this context, the role and expertise of chemical engineers, especially of the process systems engineering field, are of utmost importance.
The objective of this Dissertation is to promote the use of advanced mathematical modeling techniques within pharmaceutical development and manufacturing environments to: i) reduce pharmaceutical development time and cost; ii) increase the efficiency and the robustness of pharmaceutical manufacturing.
These objectives are achieved by developing and implementing mathematical methodologies in key areas of pharmaceutical development and manufacturing: operation design, process monitoring and process control. The case studies span across the whole pharmaceutical flowsheet, but are particularly focused on continuous manufacturing processes. Applications of mathematical modeling are specifically addressed to tackle current bottlenecks towards the transition to end-to-end continuous pharmaceutical processing.
The results presented and discussed in this Dissertation make several steps forward in the journey to adopt model-based methodologies for modernizing pharmaceutical development and manufacturing. Enabling technologies for the novel Quality-by-Control paradigm and for the transition to end-to-end continuous manufacturing have been developed. In particular, the presented results are expected to promote the adoption of advanced fault detection and diagnosis, digital operation design and closed-loop quality control routines in the pharmaceutical industry
A review on the modernization of pharmaceutical development and manufacturing – Trends, perspectives, and the role of mathematical modeling
No full textRecently, the pharmaceutical industry has been facing several challenges associated to the use of outdated development and manufacturing technologies. The return on investment on research and development has been shrinking, and, at the same time, an alarming number of shortages and recalls for quality concerns has been registered. The pharmaceutical industry has been responding to these issues through a technological modernization of development and manufacturing, under the support of initiatives and activities such as quality-bydesign (QbD), process analytical technology, and pharmaceutical emerging technology. In this review, we analyze this modernization trend, with emphasis on the role that mathematical modeling plays within it. We begin by outlining the main socio-economic trends of the pharmaceutical industry, and by highlighting the lifecycle stages of a pharmaceutical product in which technological modernization can help both achieve consistently high product quality and increase return on investment. Then, we review the historical evolution of the
pharmaceutical regulatory framework, and we discuss the current state of implementation and future trends of QbD. The pharmaceutical emerging technology is reviewed afterwards, and a discussion on the evolution of QbD into the more effective quality-by-control (QbC) paradigm is presented. Further, we illustrate how mathematical modeling can support the implementation of QbD and QbC across all stages of the pharmaceutical life-cycle. In this respect, we review academic and industrial applications demonstrating the impact of mathematical modeling on three key activities within pharmaceutical development and manufacturing, namely design space description, process monitoring, and active process control. Finally, we discuss some future research opportunities on the use of mathematical modeling in industrial pharmaceutical environments
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
A hybrid framework for process monitoring: Enhancing data-driven methodologies with state and parameter estimation
Full text linkIn this study we bridge traditional standalone data-driven and knowledge-driven process monitoring approaches by proposing a novel hybrid framework that exploits the advantages of both simultaneously. Namely, we design a process monitoring system based on a data-driven model that includes two different data types: i) ‘‘actual’’ data coming from sensor measurements, and ii) ‘‘virtual’’ data coming from a state estimator, based on a first-principles model of the system under investigation. We test the proposed approach on two simulated case studies: a continuous polycondensation process for the synthesis of poly-ethylene terephthalate, and a fed-batch fermentation process for the manufacturing of penicillin. The hybrid monitoring model shows superior fault detection and diagnosis performances with respect to conventional monitoring techniques, even when the first-principles model is relatively simple and process/model mismatch exists
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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