AI Medical Compendium Topic:
Drug Design

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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...

Artificial Intelligence in The Management of Neurodegenerative Disorders.

CNS & neurological disorders drug targets
Neurodegenerative disorders are characterized by a gradual but irreversible loss of neurological function. The ability to detect and treat these conditions successfully is crucial for ensuring the best possible quality of life for people who suffer f...

Artificial Intelligence in ADME Property Prediction.

Methods in molecular biology (Clifton, N.J.)
Absorption, distribution, metabolism, excretion (ADME) are key properties of a small molecule that govern pharmacokinetic profiles and impact its efficacy and safety. Computational methods such as machine learning and artificial intelligence have gai...

Recent Deep Learning Applications to Structure-Based Drug Design.

Methods in molecular biology (Clifton, N.J.)
Identification and optimization of small molecules that bind to and modulate protein function is a crucial step in the early stages of drug development. For decades, this process has benefitted greatly from the use of computational models that can pr...

DrugGen: a database of de novo-generated molecular binders for specified target proteins.

Database : the journal of biological databases and curation
De novo molecular generation is a promising approach to drug discovery, building novel molecules from the scratch that can bind the target proteins specifically. With the increasing availability of machine learning algorithms and computational power,...

FormulationAI: a novel web-based platform for drug formulation design driven by artificial intelligence.

Briefings in bioinformatics
Today, pharmaceutical industry faces great pressure to employ more efficient and systematic ways in drug discovery and development process. However, conventional formulation studies still strongly rely on personal experiences by trial-and-error exper...

Combining machine learning and molecular simulations to predict the stability of amorphous drugs.

The Journal of chemical physics
Amorphous drugs represent an intriguing option to bypass the low solubility of many crystalline formulations of pharmaceuticals. The physical stability of the amorphous phase with respect to the crystal is crucial to bring amorphous formulations into...

A Review on Artificial Intelligence Approaches and Rational Approaches in Drug Discovery.

Current pharmaceutical design
Artificial intelligence (AI) speeds up the drug development process and reduces its time, as well as the cost which is of enormous importance in outbreaks such as COVID-19. It uses a set of machine learning algorithms that collects the available data...