The ability to predict formulation behaviour at production scale during formulation design can reduce the time to market and decrease product development costs. However, it is challenging to extrapolate compaction settings for direct compression formulations between tablet press models during scale-up and transfer from R&D to commercial production. The aim of this study was to develop statistical process models to predict tablet tensile strength, porosity and disintegration time from compaction parameters (pre-compression and main compression force, and press speed), for three formulations, with differing deformation characteristics (plastic, brittle and elastic), on three tablet press models (one pilot-scale tablet press (KG RoTab) and two production-scale presses (Fette 1200i and GEA Modul P)). The deformation characteristics of yield pressure and elastic recovery were determined for the model placebo formulations investigated. To facilitate comparison of dwell time settings between tablet press models, the design of experiments (DoE) approach was 9 individual 16-run response surface DoEs (3 formulation × 3 press models), whose results were combined to create a polynomial regression model for each tablet property. These models predicted tablet tensile strength, porosity and disintegration time and enabled the construction of design spaces to produce tablets with specified target properties, for each formulation on each press. The models were successfully validated. This modelling approach provides an understanding of the compaction behaviour of formulations with varying deformation behaviour on development and commercial tablet press models. This understanding can be applied to inform achievable production rates at a commercial scale, during the formulation development.
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http://dx.doi.org/10.3390/pharmaceutics14040695 | DOI Listing |
Mol Med
December 2024
Disease Prevention and Health Management Center, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, 310006, Zhejiang, China.
Background: Nonalcoholic fatty liver disease (NAFLD) has developed as a leading public wellness challenge as a result of changes in dietary patterns. Unfortunately, there is still a lack of effective pharmacotherapy methods for NAFLD. Wang's empirical formula (WSF) has demonstrated considerable clinical efficacy in treating metabolic disorders for years.
View Article and Find Full Text PDFPsychopharmacology (Berl)
December 2024
Department of Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN, 47904, USA.
Rationale: The rise in overdose deaths from synthetic opioids, especially fentanyl, necessitates the development of preclinical models to study fentanyl use disorder (FUD). While there has been progress with rodent models, additional translationally relevant models are needed to examine excessive fentanyl intake and withdrawal signs.
Objective: The current study aimed to develop a translationally relevant preclinical mouse model of FUD by employing chronic intravenous fentanyl self-administration (IVSA).
Sci Rep
December 2024
College of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130012, China.
In the context of rapid urbanization, the proliferation of high-density residential zones and intricate infrastructure networks markedly amplifies a city's susceptibility to natural calamities, notably seismic events. Thus, a precise evaluation of a city's emergency capability for seismic events is imperative. This research proposes a novel and all-encompassing evaluation framework for indicators, grounded in crisis management theory, covering the entire spectrum of disaster mitigation, preparedness, response, and recovery.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Laboratory Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China.
Endometrial cancer is the most prevalent form of gynecologic malignancy, with a significant surge in incidence among youngsters. Although the advent of the immunotherapy era has profoundly improved patient outcomes, not all patients benefit from immunotherapy; some patients experience hyperprogression while on immunotherapy. Hence, there is a pressing need to further delineate the distinct immune response profiles in patients with endometrial cancer to enhance prognosis prediction and facilitate the prediction of immunotherapeutic responses.
View Article and Find Full Text PDFJ Pers Med
December 2024
Department of Clinical Research, University of Southern Denmark, 5230 Odense, Denmark.
Artificial intelligence (AI) is becoming increasingly influential in ophthalmology, particularly through advancements in machine learning, deep learning, robotics, neural networks, and natural language processing (NLP). Among these, NLP-based chatbots are the most readily accessible and are driven by AI-based large language models (LLMs). These chatbots have facilitated new research avenues and have gained traction in both clinical and surgical applications in ophthalmology.
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