AIMC Topic: Pharmaceutical Preparations

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Prediction of drug-protein interaction based on dual channel neural networks with attention mechanism.

Briefings in functional genomics
The precise identification of drug-protein inter action (DPI) can significantly speed up the drug discovery process. Bioassay methods are time-consuming and expensive to screen for each pair of drug proteins. Machine-learning-based methods cannot acc...

Machine learning framework to predict pharmacokinetic profile of small molecule drugs based on chemical structure.

Clinical and translational science
Accurate prediction of a new compound's pharmacokinetic (PK) profile is pivotal for the success of drug discovery programs. An initial assessment of PK in preclinical species and humans is typically performed through allometric scaling and mathematic...

Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals.

Studies in health technology and informatics
The health product circuit corresponds to the chain of steps that a medicine goes through in hospital, from prescription to administration. The safety and regulation of all the stages of this circuit are major issues to ensure the safety and protect ...

Evaluating the Performance of Large Language Models for Named Entity Recognition in Ophthalmology Clinical Free-Text Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This study compared large language models (LLMs) and Bidirectional Encoder Representations from Transformers (BERT) models in identifying medication names, routes, and frequencies from publicly available free-text ophthalmology progress notes of 480 ...

Graph Neural Networks with Multi-features for Predicting Cocrystals using APIs and Coformers Interactions.

Current medicinal chemistry
INTRODUCTION: Active pharmaceutical ingredients (APIs) have gained direct pharmaceutical interest, along with their in vitro properties, and thus utilized as auxiliary solid dosage forms upon FDA guidance and approval on pharmaceutical cocrystals whe...

Robotic Pills as Innovative Personalized Medicine Tools: A Mini Review.

Recent advances in drug delivery and formulation
The most common route for drug administration is the oral route due to the various advantages offered by this route, such as ease of administration, controlled and sustained drug delivery, convenience, and non-invasiveness. In spite of this, oral dru...

LSTM-SAGDTA: Predicting Drug-target Binding Affinity with an Attention Graph Neural Network and LSTM Approach.

Current pharmaceutical design
INTRODUCTION: Drug development is a challenging and costly process, yet it plays a crucial role in improving healthcare outcomes. Drug development requires extensive research and testing to meet the demands for economic efficiency, cures, and pain re...

Comprehensive Review on Drug-target Interaction Prediction - Latest Developments and Overview.

Current drug discovery technologies
Drug-target interactions (DTIs) are an important part of the drug development process. When the drug (a chemical molecule) binds to a target (proteins or nucleic acids), it modulates the biological behavior/function of the target, returning it to its...

Graph-DTI: A New Model for Drug-target Interaction Prediction Based on Heterogenous Network Graph Embedding.

Current computer-aided drug design
BACKGROUND: In this study, we aimed to develop a new end-to-end learning model called Graph-Drug-Target Interaction (DTI), which integrates various types of information in the heterogeneous network data, and to explore automatic learning of the topol...