AIMC Topic: Technology, Pharmaceutical
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Beyond the Hype: The potential and challenges of semi-solid extrusion 3D Printing in pharmaceutical applications through the lens of Portuguese 3D experts.
International journal of pharmaceutics
May 29, 2025
In recent years, the technological landscape has experienced a notable surge in the exploration of 3D Printing technologies (3DPT), particularly as an additive manufacturing method. Among the various 3DPT available, semi-solid extrusion 3DP (SSE-3DP)...
Application of rheology to hot melt extrusion: Theory and practice.
International journal of pharmaceutics
May 29, 2025
Hot melt extrusion (HME) has become a key manufacturing method in the pharmaceutical industry for developing novel drug delivery systems, due to its solvent-free nature, ease of operation, and ability to achieve one-step molding and continuous proces...
Probabilistic design space exploration and optimization via bayesian approach for a fluid bed drying process.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
May 3, 2025
The concept of Design Space (DS), delineated as a region of investigated variables aimed at maintaining product quality, was introduced in the International Conference on Harmonisation (ICH) Q8 as a framework to direct pharmaceutical development. How...
Testing on continuous production of mefenamic acids-Design of experiment through simulation and process optimisation.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Apr 29, 2025
In the pharmaceutical manufacturing industry, continuous production methods have been recognised as providing several benefits compared to traditional batch production. These benefits include increased flexibility, higher product output, enhanced qua...
Recommendations for Artificial Intelligence Application in Continued Process Verification: A Journey Toward the Challenges and Benefits of AI in the Biopharmaceutical Industry.
PDA journal of pharmaceutical science and technology
Mar 3, 2025
This review paper explores the transformative impact of Artificial Intelligence (AI) on Continued Process Verification (CPV) in the biopharmaceutical industry. Originating from the CPV of the Future project, the study investigates the challenges and ...
Scale-independent solid fraction prediction in dry granulation process using a gray-box model integrating machine learning model and Johanson model.
International journal of pharmaceutics
Feb 15, 2025
We propose a novel approach for predicting the solid fraction after roller compaction processes. It is crucial to predict and control the solid fraction, as it has a significant impact on the product quality. The solid fraction can be theoretically p...
Deep learning-based defect detection in film-coated tablets using a convolutional neural network.
International journal of pharmaceutics
Jan 18, 2025
Film-coating is a critical step in pharmaceutical manufacturing. Traditional visual inspections for film-coated tablet defect assessment are subjective, inefficient, and labor-intensive. We propose a novel approach utilizing machine learning and imag...
A deep learning approach to perform defect classification of freeze-dried product.
International journal of pharmaceutics
Jan 3, 2025
Cosmetic inspection of freeze-dried products is an important part of the post-manufacturing quality control process. Traditionally done by human visual inspection, this method poses typical challenges and shortcomings that can be addressed with innov...
Modelling the effect of base component properties and processing conditions on mixture products using probabilistic, knowledge-guided neural networks.
International journal of pharmaceutics
Dec 4, 2024
Development of materials by mixing different base components is a widespread methodology to create materials with improved properties compared to those of its base components. However, efficient determination of the properties of mixture-based materi...
Automated tablet defect detection and the prediction of disintegration time and crushing strength with deep learning based on tablet surface images.
International journal of pharmaceutics
Nov 1, 2024
This paper presents novel measurement methods, where deep learning was used to detect tableting defects and determine the crushing strength and disintegration time of tablets on images captured by machine vision. Five different classes of defects wer...
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