Special Issue "Empowering Pharma4.0: Continuous Monitoring and Optimization of Pharmaceutical Processes"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Pharmaceutical Processes".

Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 1004

Special Issue Editors

Dr. Dana Copot
E-Mail Website
Guest Editor
Research group on Dynamical Systems and Control (DYSC), Department of Electromechanical, Systems and Metal Engineering, Ghent University, B-9052 Ghent, Belgium
Interests: modelling and control, identification, anesthesia control, objective pain assessment, process control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Elena Torfs
E-Mail Website
Guest Editor
Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium
Interests: mathematical modelling; hybrid models; process control; potable water; water distribution networks; wastewater treatment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Despite manufacturing innovations and the technologies on the rise, solid oral dosage in the pharmaceutical industry is still in mass production. Although this is efficient and cost-effective, it is typically based on a “one-size-fts-all” product concept and lacks the flexibility and agility required to fully meet the needs of the individual patient. At present, the pharmaceutical industry is experiencing a paradigm shift from batch to continuous manufacturing. This will lead to increased flexibility to target diverse populations as well as more consistent product quality to ensure best efficacy. Continuous processing integrated with online/inline monitoring tools coupled with an efficient automatic feedback control system is highly desired by the pharmaceutical industry. To facilitate the transition from the batch-wise production to continuous manufacturing in the pharma industry, engineering tools are needed. Hence, the aim of this paper is to enhance the advantages of modeling and control techniques in the field of pharmaceutical applications. Transition to a continuous manufacturing process in the pharma industry has only recently, in 2020, been shown to add great economic benefits and faster time to market for increased end-user availability of products.

Dr. Dana Copot
Prof. Dr. Elena Torfs
Guest Editors

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. Processes 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 2000 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
  • process control
  • advanced manufacturing
  • personalized medicine
  • pharma 4.0
  • process analytical technology
  • mathematical model
  • dynamic simulation
  • process simulations

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Flexible Augmented Reality-Based Health Solution for Medication Weight Establishment
Processes 2022, 10(2), 219; https://doi.org/10.3390/pr10020219 - 24 Jan 2022
Cited by 1 | Viewed by 521
Abstract
The trend of personalized medicine and the increasing flexibility of drug dosage relevant goals of the 21st century represent the foundation for the current research. To obtain doses smaller than the smallest available, physicians frequently write prescriptions for children and adults, without preserving [...] Read more.
The trend of personalized medicine and the increasing flexibility of drug dosage relevant goals of the 21st century represent the foundation for the current research. To obtain doses smaller than the smallest available, physicians frequently write prescriptions for children and adults, without preserving the integrity of the pill. Moreover, patients purchase large amounts of medication for cost-saving reasons. To support the correct administration of the remedies and the partial alignment to the personalized treatment trend, this paper proposes a flexible and user-friendly solution for determining the medication quantity given to patients, using augmented reality and optical character recognition algorithm capabilities. Via the MATLAB development environment and a Logitech HD Pro C920 webcam, the results were 80% correct in identifying the cutting position of the pill, by means of the Hough transform, and 30% correct in weight recognition exploitation using an optical character recognition (OCR) algorithm. In future work, a higher resolution camera and a more powerful computer can be used to increase the percentages mentioned above. In addition, a 3D scan of the pill fragmentation, combined with the weight recognition functionality, could increase the accuracy of the splitting procedure, conducted by the patient or the patient caretaker. Full article
Show Figures

Figure 1

Back to TopTop