AIMC Topic: Drug Compounding

Clear Filters Showing 21 to 30 of 167 articles

Economic evaluation of a robotic chemotherapy compounding system and its service expansion to network hospital in Thailand.

BMC health services research
BACKGROUND: Robotic systems for chemotherapy preparation offer improved accuracy and staff safety but require substantial capital investment. This study assessed the economic performance of a domestically developed robotic chemotherapy compounding sy...

Machine Learning Predicts Drug Release Profiles and Kinetic Parameters Based on Tablets' Formulations.

The AAPS journal
Direct compression (DC) remains a popular manufacturing technology for producing solid dosage forms. However, the formulation optimisation is a laborious process, costly and time-consuming. The aim of this study was to determine whether machine learn...

Explainable artificial neural network as a soft sensor to predict the moisture content in a continuous granulation line.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
The application of artificial neural networks (ANNs) has the potential to fundamentally change the pharmaceutical industry, making manufacturing more agile, robust, efficient and reliable. Although ANNs' application as data-driven soft sensors has a ...

Advancing Direct Tablet Compression with AI: A multi-task framework for quality control, batch acceptance, and causal analysis.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Pharmaceutical manufacturing has surged in drug development with the rise of Pharma 4.0, leveraging artificial intelligence (AI) to improve efficiency, optimize resource use, and reduce production times. Direct Tablet Compression (DTC), a key manufac...

Recent advances in dry powder inhalation formulations prepared by co-spray drying technology: a comprehensive review.

International journal of pharmaceutics
Co-spray drying technology represents an increasingly important approach in preparing dry powder inhalation (DPI) formulations. Compared to conventional spray drying, co-spray drying typically yields particles characterized by improved aerosol perfor...

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
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...

PLGA-based long-acting injectable (LAI) formulations.

Journal of controlled release : official journal of the Controlled Release Society
Long-acting injectable (LAI) formulations, which deliver drugs over weeks or months, have been in use for more than three decades. Most clinically approved LAI products are formulated using poly(lactide-co-glycolide) (PLGA) polymers. Historically, th...

Predicting Powder Blend Flowability from Individual Constituent Properties Using Machine Learning.

Pharmaceutical research
PURPOSE: Predicting powder blend flowability is necessary for pharmaceutical manufacturing but challenging and resource-intensive. The purpose was to develop machine learning (ML) models to help predict flowability across multiple flow categories, id...

Combining High-Throughput Screening and Machine Learning to Predict the Formation of Both Binary and Ternary Amorphous Solid Dispersion Formulations for Early Drug Discovery and Development.

Pharmaceutical research
OBJECTIVE: Amorphous solid dispersion (ASD) is widely utilized to enhance the solubility and bioavailability of water-insoluble drugs. However, conventional experimental approaches for ASD development are often resource-intensive and time-consuming. ...

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
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...