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Forbes TP, Gillen JG, Feeney W, Ho J. Quality by Design Considerations for Drop-on-Demand Point-of-Care Pharmaceutical Manufacturing of Precision Medicine. Mol Pharm 2024. [PMID: 38661480 DOI: 10.1021/acs.molpharmaceut.4c00032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Distributed and point-of-care (POC) manufacturing facilities enable an agile pharmaceutical production paradigm that can respond to localized needs, providing personalized and precision medicine. These capabilities are critical for narrow therapeutic index drugs and pediatric or geriatric dosing, among other specialized needs. Advanced additive manufacturing, three-dimensional (3D) printing, and drop-on-demand (DoD) dispensing technologies have begun to expand into pharmaceutical production. We employed a quality by design (QbD) approach to identify critical quality attributes (CQAs), critical material attributes (CMAs), and critical process parameters (CPPs) of a POC pharmaceutical manufacturing paradigm. This theoretical framework encompasses the production of active pharmaceutical ingredient (API) "inks" at a centralized facility, which are distributed to POC sites for DoD dispensing into/onto delivery vehicles (e.g., orodispersible films, capsules, single liquid dose vials). Focusing on the POC dispensing/dosing processes, QbD considerations and cause-and-effect analyses identified the dispensed API quantity and solid-state form (CQAs), as well as the nozzle diameter, system pressure channel, and number of drops dispensed (CPPs) for detailed investigation. Final assay quantification and content uniformity CQAs were measured from demonstrative levothyroxine sodium single-dose liquid vials of glycerin/water, meeting the standard acceptance values. Each POC facility is unlikely to maintain full quality control laboratory capabilities, requiring the development of appropriate atline or inline methods to ensure quality control. We developed control strategies, including atline ultraviolet-visible (UV-vis) verification of the API ink prior to dispensing, inline drop counting during dispensing, intermediate atline-dispensed volume checks, and offline batch confirmation by liquid chromatography-tandem mass spectrometry (LC-MS/MS) following production.
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Affiliation(s)
- Thomas P Forbes
- Materials Measurement Science Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States
| | - John Greg Gillen
- Materials Measurement Science Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States
| | - William Feeney
- Materials Measurement Science Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States
| | - Johnny Ho
- Materials Measurement Science Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States
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Shi H, Zhang M, Mujumdar AS. 3D/4D printed super reconstructed foods: Characteristics, research progress, and prospects. Compr Rev Food Sci Food Saf 2024; 23:e13310. [PMID: 38369929 DOI: 10.1111/1541-4337.13310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/17/2024] [Accepted: 01/24/2024] [Indexed: 02/20/2024]
Abstract
Super reconstructed foods (SRFs) have characteristics beyond those of real system in terms of nutrition, texture, appearance, and other properties. As 3D/4D food printing technology continues to be improved in recent years, this layered manufacturing/additive manufacturing preparation technology based on food reconstruction has made it possible to continuously develop large-scale manufacture of SRFs. Compared with the traditional reconstructed foods, SRFs prepared using 3D/4D printing technologies are discussed comprehensively in this review. To meet the requirements of customers in terms of nutrition or other characteristics, multi-processing technologies are being combined with 3D/4D printing. Aspects of printing inks, product quality parameters, and recent progress in SRFs based on 3D/4D printing are assessed systematically and discussed critically. The potential for 3D/4D printed SRFs and the need for further research and developments in this area are presented and discussed critically. In addition to the natural materials which were initially suitable for 3D/4D printing, other derivative components have already been applied, which include hydrogels, polysaccharide-based materials, protein-based materials, and smart materials with distinctive characteristics. SRFs based on 3D/4D printing can retain the characteristics of deconstruction and reconstruction while also exhibiting quality parameters beyond those of the original material systems, such as variable rheological properties, on-demand texture, essential printability, improved microstructure, improved nutrition, and more appealing appearance. SRFs with 3D/4D printing are already widely used in foods such as simulated foods, staple foods, fermented foods, foods for people with special dietary needs, and foods made from food processingbyproducts.
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Affiliation(s)
- Hao Shi
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu, China
- Jiangsu Province International Joint Laboratory on Fresh Food Smart Processing and Quality Monitoring, Jiangnan University, Wuxi, Jiangsu, China
| | - Min Zhang
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu, China
- China General Chamber of Commerce Key Laboratory on Fresh Food Processing & Preservation, Jiangnan University, Wuxi, Jiangsu, China
| | - Arun S Mujumdar
- Department of Bioresource Engineering, Macdonald Campus, McGill University, Quebec, Canada
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Carou-Senra P, Rodríguez-Pombo L, Monteagudo-Vilavedra E, Awad A, Alvarez-Lorenzo C, Basit AW, Goyanes A, Couce ML. 3D Printing of Dietary Products for the Management of Inborn Errors of Intermediary Metabolism in Pediatric Populations. Nutrients 2023; 16:61. [PMID: 38201891 PMCID: PMC10780524 DOI: 10.3390/nu16010061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024] Open
Abstract
The incidence of Inborn Error of Intermediary Metabolism (IEiM) diseases may be low, yet collectively, they impact approximately 6-10% of the global population, primarily affecting children. Precise treatment doses and strict adherence to prescribed diet and pharmacological treatment regimens are imperative to avert metabolic disturbances in patients. However, the existing dietary and pharmacological products suffer from poor palatability, posing challenges to patient adherence. Furthermore, frequent dose adjustments contingent on age and drug blood levels further complicate treatment. Semi-solid extrusion (SSE) 3D printing technology is currently under assessment as a pioneering method for crafting customized chewable dosage forms, surmounting the primary limitations prevalent in present therapies. This method offers a spectrum of advantages, including the flexibility to tailor patient-specific doses, excipients, and organoleptic properties. These elements are pivotal in ensuring the treatment's efficacy, safety, and adherence. This comprehensive review presents the current landscape of available dietary products, diagnostic methods, therapeutic monitoring, and the latest advancements in SSE technology. It highlights the rationale underpinning their adoption while addressing regulatory aspects imperative for their seamless integration into clinical practice.
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Affiliation(s)
- Paola Carou-Senra
- Departamento de Farmacología, Farmacia y Tecnología Farmacéutica, I+D Farma (GI-1645), Facultad de Farmacia, Materials Institute (iMATUS) and Health Research Institute of Santiago de Compostela (IDIS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain; (P.C.-S.); (L.R.-P.); (C.A.-L.)
| | - Lucía Rodríguez-Pombo
- Departamento de Farmacología, Farmacia y Tecnología Farmacéutica, I+D Farma (GI-1645), Facultad de Farmacia, Materials Institute (iMATUS) and Health Research Institute of Santiago de Compostela (IDIS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain; (P.C.-S.); (L.R.-P.); (C.A.-L.)
| | - Einés Monteagudo-Vilavedra
- Servicio de Neonatología, Unidad de Diagnóstico y Tratamiento de Enfermedades Metabólicas Congénitas, Health Research Institute of Santiago de Compostela (IDIS), Hospital Clínico Universitario de Santiago de Compostela, Universidad de Santiago de Compostela, RICORS, CIBERER, MetabERN, 15706 Santiago de Compostela, Spain;
| | - Atheer Awad
- Department of Clinical, Pharmaceutical and Biological Sciences, University of Hertfordshire, College Lane, Hatfield AL10 9AB, UK;
| | - Carmen Alvarez-Lorenzo
- Departamento de Farmacología, Farmacia y Tecnología Farmacéutica, I+D Farma (GI-1645), Facultad de Farmacia, Materials Institute (iMATUS) and Health Research Institute of Santiago de Compostela (IDIS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain; (P.C.-S.); (L.R.-P.); (C.A.-L.)
| | - Abdul W. Basit
- Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK;
- FABRX Ltd., Henwood House, Henwood, Ashford, Kent TN24 8DH, UK
- FABRX Artificial Intelligence, 27543 O Saviñao, Spain
| | - Alvaro Goyanes
- Departamento de Farmacología, Farmacia y Tecnología Farmacéutica, I+D Farma (GI-1645), Facultad de Farmacia, Materials Institute (iMATUS) and Health Research Institute of Santiago de Compostela (IDIS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain; (P.C.-S.); (L.R.-P.); (C.A.-L.)
- Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK;
- FABRX Ltd., Henwood House, Henwood, Ashford, Kent TN24 8DH, UK
- FABRX Artificial Intelligence, 27543 O Saviñao, Spain
| | - María L. Couce
- Servicio de Neonatología, Unidad de Diagnóstico y Tratamiento de Enfermedades Metabólicas Congénitas, Health Research Institute of Santiago de Compostela (IDIS), Hospital Clínico Universitario de Santiago de Compostela, Universidad de Santiago de Compostela, RICORS, CIBERER, MetabERN, 15706 Santiago de Compostela, Spain;
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Sun S, Alkahtani ME, Gaisford S, Basit AW, Elbadawi M, Orlu M. Virtually Possible: Enhancing Quality Control of 3D-Printed Medicines with Machine Vision Trained on Photorealistic Images. Pharmaceutics 2023; 15:2630. [PMID: 38004607 PMCID: PMC10674815 DOI: 10.3390/pharmaceutics15112630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 11/01/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023] Open
Abstract
Three-dimensional (3D) printing is an advanced pharmaceutical manufacturing technology, and concerted efforts are underway to establish its applicability to various industries. However, for any technology to achieve widespread adoption, robustness and reliability are critical factors. Machine vision (MV), a subset of artificial intelligence (AI), has emerged as a powerful tool to replace human inspection with unprecedented speed and accuracy. Previous studies have demonstrated the potential of MV in pharmaceutical processes. However, training models using real images proves to be both costly and time consuming. In this study, we present an alternative approach, where synthetic images were used to train models to classify the quality of dosage forms. We generated 200 photorealistic virtual images that replicated 3D-printed dosage forms, where seven machine learning techniques (MLTs) were used to perform image classification. By exploring various MV pipelines, including image resizing and transformation, we achieved remarkable classification accuracies of 80.8%, 74.3%, and 75.5% for capsules, tablets, and films, respectively, for classifying stereolithography (SLA)-printed dosage forms. Additionally, we subjected the MLTs to rigorous stress tests, evaluating their scalability to classify over 3000 images and their ability to handle irrelevant images, where accuracies of 66.5% (capsules), 72.0% (tablets), and 70.9% (films) were obtained. Moreover, model confidence was also measured, and Brier scores ranged from 0.20 to 0.40. Our results demonstrate promising proof of concept that virtual images exhibit great potential for image classification of SLA-printed dosage forms. By using photorealistic virtual images, which are faster and cheaper to generate, we pave the way for accelerated, reliable, and sustainable AI model development to enhance the quality control of 3D-printed medicines.
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Affiliation(s)
- Siyuan Sun
- UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; (S.S.); (M.E.A.); (S.G.)
| | - Manal E. Alkahtani
- UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; (S.S.); (M.E.A.); (S.G.)
- Department of Pharmaceutics, College of Pharmacy, Prince Sattam bin Abdulaziz University, Alkharj 11942, Saudi Arabia
| | - Simon Gaisford
- UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; (S.S.); (M.E.A.); (S.G.)
| | - Abdul W. Basit
- UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; (S.S.); (M.E.A.); (S.G.)
| | - Moe Elbadawi
- UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; (S.S.); (M.E.A.); (S.G.)
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4DQ, UK
| | - Mine Orlu
- UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; (S.S.); (M.E.A.); (S.G.)
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Ong JJ, Chow YL, Gaisford S, Cook MT, Swift T, Telford R, Rimmer S, Qin Y, Mai Y, Goyanes A, Basit AW. Supramolecular chemistry enables vat photopolymerization 3D printing of novel water-soluble tablets. Int J Pharm 2023; 643:123286. [PMID: 37532009 DOI: 10.1016/j.ijpharm.2023.123286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 07/25/2023] [Accepted: 07/30/2023] [Indexed: 08/04/2023]
Abstract
Vat photopolymerization has garnered interest from pharmaceutical researchers for the fabrication of personalised medicines, especially for drugs that require high precision dosing or are heat labile. However, the 3D printed structures created thus far have been insoluble, limiting printable dosage forms to sustained-release systems or drug-eluting medical devices which do not require dissolution of the printed matrix. Resins that produce water-soluble structures will enable more versatile drug release profiles and expand potential applications. To achieve this, instead of employing cross-linking chemistry to fabricate matrices, supramolecular chemistry may be used to impart dynamic interaction between polymer chains. In this study, water-soluble drug-loaded printlets (3D printed tablets) are fabricated via digital light processing (DLP) 3DP for the first time. Six formulations with varying ratios of an electrolyte acrylate monomer, [2-(acryloyloxy)ethyl]trimethylammonium chloride (TMAEA), and a co-monomer, 1-vinyl-2-pyrrolidone (NVP), were prepared to produce paracetamol-loaded printlets. 1H NMR spectroscopy analysis confirmed the integration of TMAEA and NVP in the polymer, and residual TMAEA monomers were found to be present only in trace amounts (0.71 - 1.37 %w/w). The apparent molecular mass of the photopolymerised polymer was found to exceed 300,000 Da with hydrodynamic radii of 15 - 20 nm, estimated based on 1H DOSY NMR measurements The loaded paracetamol was completely released from the printlets between 45 minutes to 5 hours. In vivo single-dose acute toxicity studies in rats suggest that the printlets did not cause any tissue damage. The findings reported in this study represent a significant step towards the adoption of vat photopolymerization-based 3DP to produce personalised medicines.
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Affiliation(s)
- Jun Jie Ong
- Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK
| | - Yee Lam Chow
- Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK
| | - Simon Gaisford
- Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK
| | - Michael T Cook
- Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK
| | - Thomas Swift
- School of Chemistry and Biosciences, University of Bradford, Richmond Road, BD7 1DP, UK
| | - Richard Telford
- School of Chemistry and Biosciences, University of Bradford, Richmond Road, BD7 1DP, UK
| | - Stephen Rimmer
- School of Chemistry and Biosciences, University of Bradford, Richmond Road, BD7 1DP, UK
| | - Yujia Qin
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou 510275, China
| | - Yang Mai
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou 510275, China
| | - Alvaro Goyanes
- Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; FabRx Ltd., 3 Romney Road, Ashford, Kent TN24 0RW, UK; Departamento de Farmacología, Farmacia y Tecnología Farmacéutica, I+D Farma (GI-1645), Facultad de Farmacia, Instituto de Materiales (iMATUS) and Health Research Institute of Santiago de Compostela (IDIS), Universidade de Santiago de Compostela, 15782, Spain
| | - Abdul W Basit
- Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; FabRx Ltd., 3 Romney Road, Ashford, Kent TN24 0RW, UK.
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