AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Drug Compounding

Showing 51 to 60 of 134 articles

Clear Filters

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 ...

Testing Precision Limits of Neural Network-Based Quality Control Metrics in High-Throughput Digital Microscopy.

Pharmaceutical research
OBJECTIVE: Digital microscopy is used to monitor particulates such as protein aggregates within biopharmaceutical products. The images that result encode a wealth of information that is underutilized in pharmaceutical process monitoring. For example,...

Application of machine learning to a material library for modeling of relationships between material properties and tablet properties.

International journal of pharmaceutics
This study investigates the usefulness of machine learning for modeling complex relationships in a material library. We tested 81 types of active pharmaceutical ingredients (APIs) and their tablets to construct the library, which included the followi...

In silico formulation prediction of drug/cyclodextrin/polymer ternary complexes by machine learning and molecular modeling techniques.

Carbohydrate polymers
Ternary cyclodextrin (CD) complexes (drug/CD/polymer) can effectively improve the solubility of water-insoluble drugs with large size than binary CD formulations. However, ternary formulations are screened by a trial-and-error approach, which is labo...

Use of machine learning in prediction of granule particle size distribution and tablet tensile strength in commercial pharmaceutical manufacturing.

International journal of pharmaceutics
In the manufacturing of pharmaceutical Oral Solid Dosage (OSD) forms, Particle Size Distribution (PSD) and Tensile Strength (TS) are common in-process tests that are controlled in order to achieve the quality targets of the end-product. The Quality b...

Design of Biopharmaceutical Formulations Accelerated by Machine Learning.

Molecular pharmaceutics
In addition to activity, successful biological drugs must exhibit a series of suitable developability properties, which depend on both protein sequence and buffer composition. In the context of this high-dimensional optimization problem, advanced alg...