AIMC Topic: Chemistry, Pharmaceutical
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Enhancing YOLOv8n with Mamba-like linear attention for defect detection and coating thickness analysis of irregular film tablet.
International journal of pharmaceutics
Jun 10, 2025
This study presents a real-time system that integrates deep learning and machine vision for defect detection and coating thickness measurement of irregularly shaped film-coated tablets. To overcome the accuracy and speed limitations of the traditiona...
Predicting the solubility of drugs in supercritical carbon dioxide using machine learning and atomic contribution.
European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
Jun 1, 2025
The pharmaceutical sector is aware of supercritical CO (SC-CO) as a possible replacement for problematic organic solvents. Using a novel artificial intelligence (AI) strategy to predict drug solubility using the SC-CO system mathematically has been d...
Advancing Pharmaceutical Science with Artificial Neural Networks: A Review on Optimizing Drug Delivery Systems Formulation.
Current pharmaceutical design
Jan 1, 2025
Drug Delivery Systems (DDS) have been developed to address the challenges associated with traditional drug delivery methods. These DDS aim to improve drug administration, enhance patient compliance, reduce side effects, and optimize target therapy. T...
In-line monitoring and endpoint determination of percolation process of herbal medicine using ultraviolet spectroscopy combined with convolutional neural network.
The Journal of pharmacy and pharmacology
Oct 7, 2021
OBJECTIVES: As a common step in the herbal medicine production process, percolation usually lacks effective process monitoring methods and is often conducted with fixed process parameters. In this study, an in-line ultraviolet (UV) spectroscopy was u...
Machine Learning and Perturbation Theory Machine Learning (PTML) in Medicinal Chemistry, Biotechnology, and Nanotechnology.
Current topics in medicinal chemistry
Jan 1, 2021
Recently, different authors have reported Perturbation Theory (PT) methods combined with machine learning (ML) to obtain PTML (PT + ML) models. They have applied PTML models to the study of different biological systems. Here we present one state-of-a...
Assessing the impact of generative AI on medicinal chemistry.
Nature biotechnology
Feb 1, 2020
PTML Multi-Label Algorithms: Models, Software, and Applications.
Current topics in medicinal chemistry
Jan 1, 2020
By combining Machine Learning (ML) methods with Perturbation Theory (PT), it is possible to develop predictive models for a variety of response targets. Such combination often known as Perturbation Theory Machine Learning (PTML) modeling comprises a ...
Artificial Neural Networks in Computer-Aided Drug Design: An Overview of Recent Advances.
Advances in experimental medicine and biology
Jan 1, 2020
Computer-aided drug design (CADD) is the framework in which the huge amount of data accumulated by high-throughput experimental methods used in drug design is quantitatively studied. Its objectives include pattern recognition, biomarker identificatio...
Development and application of a comprehensive machine learning program for predicting molecular biochemical and pharmacological properties.
Physical chemistry chemical physics : PCCP
Feb 27, 2019
We establish a comprehensive quantitative structure-activity relationship (QSAR) model termed AlphaQ through the machine learning algorithm to associate the fully quantum mechanical molecular descriptors with various biochemical and pharmacological p...
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