AIMC Topic: Drug Compounding

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Processability evaluation of multiparticulate units prepared by selective laser sintering using the SeDeM Expert System approach.

International journal of pharmaceutics
3D printing in dosage forms fabrication is in the focus of researchers, however, the attempts in multiparticulate units (MPUs) preparation are scarce. The aim of this study was to fabricate different size MPUs by selective laser sintering (SLS), usin...

Evaluation of a Self-Supervised Machine Learning Method for Screening of Particulate Samples: A Case Study in Liquid Formulations.

Journal of pharmaceutical sciences
Imaging is commonly used as a characterization method in the pharmaceuticals industry, including for quantifying subvisible particles in solid and liquid formulations. Extracting information beyond particle size, such as classifying morphological sub...

Continuous Manufacturing and Molecular Modeling of Pharmaceutical Amorphous Solid Dispersions.

AAPS PharmSciTech
Amorphous solid dispersions enhance solubility and oral bioavailability of poorly water-soluble drugs. The escalating number of drugs with poor aqueous solubility, poor dissolution, and poor oral bioavailability is an unresolved problem that requires...

Contribution of an anticancer drug compounding robot in reducing the risks of manual preparation in a hospital pharmacy unit specialized in oncology.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
INTRODUCTION: In the last few years, pharmaceutical technology has evolved. In the field of oncology pharmacy, robots for the preparation of anti-cancer drugs have appeared to progressively replace manual preparation. The objective of this study is t...

Risk Assessment for a Twin-Screw Granulation Process Using a Supervised Physics-Constrained Auto-encoder and Support Vector Machine Framework.

Pharmaceutical research
Quality risk management is an important task when it pertains to the pharmaceutical industry, as this is directly related to product performance. With the ICH Q9 guidelines, several regulatory bodies have encouraged the pharmaceutical industry to imp...

Machine Learning Analysis Provides Insight into Mechanisms of Protein Particle Formation Inside Containers During Mechanical Agitation.

Journal of pharmaceutical sciences
Container choice can influence particle generation within protein formulations. Incompatibility between proteins and containers can manifest as increased particle concentrations, shifts in particle size distributions and changes in particle morpholog...

Real-time coating thickness measurement and defect recognition of film coated tablets with machine vision and deep learning.

International journal of pharmaceutics
This paper presents a system, where images acquired with a digital camera are coupled with image analysis and deep learning to identify and categorize film coating defects and to measure the film coating thickness of tablets. There were 5 different c...

Pharmacotechnical Evaluation by SeDeM Expert System to Develop Orodispersible Tablets.

AAPS PharmSciTech
Sediment delivery model (SeDeM) system is innovative tool to correlate micromeritic properties of powders with compressibility. It involves computation of indices which facilitate direct compressibility of solids and enable corrective measures throug...

A Strategy for the Effective Optimization of Pharmaceutical Formulations Based on Parameter-Optimized Support Vector Machine Model.

AAPS PharmSciTech
Engineering pharmaceutical formulations is governed by a number of variables, and the finding of the optimal preparation is intricately linked to the exploration of a multiparametric space through a variety of optimization tasks. As a result, making ...