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Pharmaceutics
Special Issues
Continuous Pharmaceutical Manufacturing
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Continuous Pharmaceutical Manufacturing

A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Pharmaceutical Technology, Manufacturing and Devices".

Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 25783

Special Issue Editor

Dr. Ossi Korhonen

E-Mail Website
Guest Editor
School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70210 Kuopio, Finland
Interests: continuous manufacturing of tablets; Quality by Design (QbD); Design of Experiment (DoE); Process Analytical Techniques (PAT); multivariate spectral data analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pharmaceutical manufacturing is facing the greatest ideological revolution since industrial drug manufacturing. Drugs have been traditionally manufactured in batch mode, but now the continuous manufacturing has started to gain a serious interest in the pharmaceutical industry. The pharma industry is heavily regulated by authorizing bodies (FDA, EMA, etc.), but already, over a decade, regulatory bodies have enabled and even encouraged the change from batch to continuous manufacturing by publishing several guidelines on how to implement continuous manufacturing. Advantages of continuous manufacturing are indisputable. The quality by design framework provides the cornerstone for better process understanding and ultimately higher product quality for patients. New modes of manufacturing of drugs require a substantial amount of research from the pharmaceutical industry, academia, and various research institutions. This Special Issue: “Continuous Pharmaceutical Manufacturing” is intended to cover the whole spectrum of all relevant aspects of continuous manufacturing. Starting from the fundamental science of detailed phenomenon in continuous manufacturing and ending in how applied science can put continuous manufacturing into practice.

Dr. Ossi Korhonen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceutics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • continuous manufacturing of pharmaceuticals
  • Quality by Design
  • risk assessment in continuous manufacturing
  • Design of Experiment in continuous manufacturing
  • Design Space
  • Process Analytical Techniques (PAT) in continuous manufacturing
  • real-time process monitoring
  • data analysis of process data
  • process simulations
  • process control and automation

Published Papers (7 papers)

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Editorial

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2 pages, 141 KiB  
Editorial
Continuous Pharmaceutical Manufacturing
by Ossi Korhonen
Pharmaceutics 2020, 12(10), 910; https://doi.org/10.3390/pharmaceutics12100910 - 23 Sep 2020
Cited by 1 | Viewed by 1927
Abstract
[...] Full article
(This article belongs to the Special Issue Continuous Pharmaceutical Manufacturing)

Research

Jump to: Editorial

15 pages, 4686 KiB  
Article
End-Point Prediction of Granule Moisture in a ConsiGmaTM-25 Segmented Fluid Bed Dryer
by Jakob Rehrl, Stephan Sacher, Martin Horn and Johannes Khinast
Pharmaceutics 2020, 12(5), 452; https://doi.org/10.3390/pharmaceutics12050452 - 14 May 2020
Cited by 12 | Viewed by 2707
Abstract
Continuously operated pharmaceutical manufacturing lines often consist of a wet granulation unit operation, followed by a (semi-) continuous dryer. The operating conditions of the dryer are crucial for obtaining a desired final granule moisture. Commercially available dryers lack of a thorough online measurement [...] Read more.
Continuously operated pharmaceutical manufacturing lines often consist of a wet granulation unit operation, followed by a (semi-) continuous dryer. The operating conditions of the dryer are crucial for obtaining a desired final granule moisture. Commercially available dryers lack of a thorough online measurement of granule moisture during the drying process. However, this information could improve the operation of the equipment considerably, yielding a granule moisture close to the desired value (e.g., by drying time and process parameter adjustments in real-time). The paper at hand proposes a process model, which can be parameterized from a very limited number of experiments and then be used as a so-called soft sensor for predicting granule moisture. It utilizes available process measurements for the estimation of the granule moisture. The development of the model as well as parameter identification and validation experiments are provided. The proposed model paves the way for the application of sophisticated observer concepts. Possible future activities on that topic are outlined in the paper. Full article
(This article belongs to the Special Issue Continuous Pharmaceutical Manufacturing)
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19 pages, 2026 KiB  
Article
The Comparison of Two Challenging Low Dose APIs in a Continuous Direct Compression Process
by Tuomas Ervasti, Hannes Niinikoski, Eero Mäki-Lohiluoma, Heidi Leppinen, Jarkko Ketolainen, Ossi Korhonen and Satu Lakio
Pharmaceutics 2020, 12(3), 279; https://doi.org/10.3390/pharmaceutics12030279 - 20 Mar 2020
Cited by 14 | Viewed by 4376
Abstract
Segregation is a common problem in batch-based direct compression (BDC) processes, especially with low-dose tablet products, as is the preparation of a homogenous mixture. The scope of the current work was to explore if a continuous direct compression (CDC) process could serve as [...] Read more.
Segregation is a common problem in batch-based direct compression (BDC) processes, especially with low-dose tablet products, as is the preparation of a homogenous mixture. The scope of the current work was to explore if a continuous direct compression (CDC) process could serve as a solution for these challenges. Furthermore, the principle of a platform formulation was demonstrated for low dose tablets. The combination of filler excipients and the API in the formulation used was suitable for direct compression, but also prone to induce segregation in BDC process. The CDC process was found to be very promising; it was shown that tablets with the desired quality parameters could be manufactured successfully with both of the APIs studied. Powder analysis indicated that the APIs display some fundamental differences in their physical properties, which was also reflected in powder mixture properties and, hence, eventually in processing. However, process parameters, especially mixer impeller speed, were not found to have any significant influence on end product quality. The study suggests that a CDC process can be a viable solution to resolve the challenges described. Moreover, manufacturing by using a universal platform formulation seems to be a feasible way for producing low-dose tablets. Full article
(This article belongs to the Special Issue Continuous Pharmaceutical Manufacturing)
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26 pages, 1409 KiB  
Article
Predicting Pharmaceutical Particle Size Distributions Using Kernel Mean Embedding
by Daan Van Hauwermeiren, Michiel Stock, Thomas De Beer and Ingmar Nopens
Pharmaceutics 2020, 12(3), 271; https://doi.org/10.3390/pharmaceutics12030271 - 16 Mar 2020
Cited by 14 | Viewed by 3792
Abstract
In the pharmaceutical industry, the transition to continuous manufacturing of solid dosage forms is adopted by more and more companies. For these continuous processes, high-quality process models are needed. In pharmaceutical wet granulation, a unit operation in the ConsiGma TM -25 continuous powder-to-tablet [...] Read more.
In the pharmaceutical industry, the transition to continuous manufacturing of solid dosage forms is adopted by more and more companies. For these continuous processes, high-quality process models are needed. In pharmaceutical wet granulation, a unit operation in the ConsiGma TM -25 continuous powder-to-tablet system (GEA Pharma systems, Collette, Wommelgem, Belgium), the product under study presents itself as a collection of particles that differ in shape and size. The measurement of this collection results in a particle size distribution. However, the theoretical basis to describe the physical phenomena leading to changes in this particle size distribution is lacking. It is essential to understand how the particle size distribution changes as a function of the unit operation’s process settings, as it has a profound effect on the behavior of the fluid bed dryer. Therefore, we suggest a data-driven modeling framework that links the machine settings of the wet granulation unit operation and the output distribution of granules. We do this without making any assumptions on the nature of the distributions under study. A simulation of the granule size distribution could act as a soft sensor when in-line measurements are challenging to perform. The method of this work is a two-step procedure: first, the measured distributions are transformed into a high-dimensional feature space, where the relation between the machine settings and the distributions can be learnt. Second, the inverse transformation is performed, allowing an interpretation of the results in the original measurement space. Further, a comparison is made with previous work, which employs a more mechanistic framework for describing the granules. A reliable prediction of the granule size is vital in the assurance of quality in the production line, and is needed in the assessment of upstream (feeding) and downstream (drying, milling, and tableting) issues. Now that a validated data-driven framework for predicting pharmaceutical particle size distributions is available, it can be applied in settings such as model-based experimental design and, due to its fast computation, there is potential in real-time model predictive control. Full article
(This article belongs to the Special Issue Continuous Pharmaceutical Manufacturing)
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24 pages, 7752 KiB  
Article
Design Space Identification and Visualization for Continuous Pharmaceutical Manufacturing
by Samir Diab and Dimitrios I. Gerogiorgis
Pharmaceutics 2020, 12(3), 235; https://doi.org/10.3390/pharmaceutics12030235 - 05 Mar 2020
Cited by 15 | Viewed by 4744
Abstract
Progress in continuous flow chemistry over the past two decades has facilitated significant developments in the flow synthesis of a wide variety of Active Pharmaceutical Ingredients (APIs), the foundation of Continuous Pharmaceutical Manufacturing (CPM), which has gained interest for its potential to reduce [...] Read more.
Progress in continuous flow chemistry over the past two decades has facilitated significant developments in the flow synthesis of a wide variety of Active Pharmaceutical Ingredients (APIs), the foundation of Continuous Pharmaceutical Manufacturing (CPM), which has gained interest for its potential to reduce material usage, energy and costs and the ability to access novel processing windows that would be otherwise hazardous if operated via traditional batch techniques. Design space investigation of manufacturing processes is a useful task in elucidating attainable regions of process performance and product quality attributes that can allow insight into process design and optimization prior to costly experimental campaigns and pilot plant studies. This study discusses recent demonstrations from the literature on design space investigation and visualization for continuous API production and highlights attainable regions of recoveries, material efficiencies, flowsheet complexity and cost components for upstream (reaction + separation) via modeling, simulation and nonlinear optimization, providing insight into optimal CPM operation. Full article
(This article belongs to the Special Issue Continuous Pharmaceutical Manufacturing)
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14 pages, 1200 KiB  
Article
Partial Least Squares Regression-Based Robust Forward Control of the Tableting Process
by Yusuke Hattori, Miki Naganuma and Makoto Otsuka
Pharmaceutics 2020, 12(1), 85; https://doi.org/10.3390/pharmaceutics12010085 - 20 Jan 2020
Cited by 4 | Viewed by 3156
Abstract
In this study, we established a robust feed-forward control model for the tableting process by partial least squares regression using the near-infrared (NIR) spectra and physical attributes of the granules to be compressed. The NIR spectra of granules are rich in information about [...] Read more.
In this study, we established a robust feed-forward control model for the tableting process by partial least squares regression using the near-infrared (NIR) spectra and physical attributes of the granules to be compressed. The NIR spectra of granules are rich in information about chemical attributes, such as the compositions of any ingredients and moisture content. Polymorphism and pseudo-polymorphism can also be quantitatively evaluated by NIR spectra. We used the particle size distribution, flowability, and loose and tapped density as the physical attributes of the granules. The tableting process was controlled by the lower punch fill depth and the minimum distance between the upper and lower punches at compression, which were specifically related to the tablet weight and thickness, respectively. The feed-forward control of the process would be expected to provide some advantages for automated and semi-automated continuous pharmaceutical manufacturing. As a result, our model, using a combination of NIR spectra and the physical attributes of granules to control the distance between punches, resulted in respectable agreement between the predicted process parameters and actual settings to produce tablets of the desired thickness. Full article
(This article belongs to the Special Issue Continuous Pharmaceutical Manufacturing)
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11 pages, 1345 KiB  
Article
Predictive Model-Based Process Start-Up in Pharmaceutical Continuous Granulation and Drying
by Victoria Pauli, Peter Kleinebudde and Markus Krumme
Pharmaceutics 2020, 12(1), 67; https://doi.org/10.3390/pharmaceutics12010067 - 15 Jan 2020
Cited by 12 | Viewed by 3906
Abstract
Continuous manufacturing (CM) is a promising strategy to achieve various benefits in the context of quality, flexibility, safety and cost in pharmaceutical production. One of the main technical challenges of CM is that the process needs to handle transient conditions such as the [...] Read more.
Continuous manufacturing (CM) is a promising strategy to achieve various benefits in the context of quality, flexibility, safety and cost in pharmaceutical production. One of the main technical challenges of CM is that the process needs to handle transient conditions such as the start-up phase before state of control operation is reached, which can potentially cause out-of-specification (OOS) material. In this context, the presented paper aims to demonstrate that suitable process control strategies during start-up of a continuous granulation and drying operation can limit or even avoid OOS material production and hence can ensure that the provided benefits of CM are not compromised by poor production yields. In detail, heat-up of the drying chamber prior the start of production can lead to thermal energy being stored inside of the stainless-steel housing, acting as an energy buffer that is known to cause over-dried granules in the first few minutes of the drying process. To compensate this issue, an automatic ramping procedure of dryer rotation speed (and hence drying time) was introduced into the plant’s process control system, which counteracts the excessive drying capacity during start-up. As a result, dry granules exiting the dryer complied with the targeted intermediate critical quality attribute loss-on-drying (LOD) from the very beginning of production. Full article
(This article belongs to the Special Issue Continuous Pharmaceutical Manufacturing)
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