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Drug Development

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SynthMol: A Drug Safety Prediction Framework Integrating Graph Attention and Molecular Descriptors into Pre-Trained Geometric Models.

Journal of chemical information and modeling
Drug safety is affected by multiple molecular properties and safety assessment is critical for clinical application. Evaluating a drug candidate's therapeutic potential is facilitated by machine learning models trained on extensive compound bioactivi...

Elevating Research and Careers in the Development of Safer Drugs through Artificial Intelligence.

Chemical research in toxicology
The session "Elevating Research and Careers in the Development of Safer Drugs through Artificial Intelligence," held at the American Chemical Society meeting, showcased innovative methodologies that AI brings to drug development, from predictive mode...

Advances of deep Neural Networks (DNNs) in the development of peptide drugs.

Future medicinal chemistry
Peptides are able to bind to difficult disease targets with high potency and specificity, providing great opportunities to meet unmet medical requirements. Nevertheless, the unique features of peptides, such as their small size, high structural flexi...

Evaluating the synergistic use of advanced liver models and AI for the prediction of drug-induced liver injury.

Expert opinion on drug metabolism & toxicology
INTRODUCTION: Drug-induced liver injury (DILI) is a leading cause of acute liver failure. Hepatotoxicity typically occurs only in a subset of individuals after prolonged exposure and constitutes a major risk factor for the termination of drug develop...

The reality of modeling irritable bowel syndrome: progress and challenges.

Expert opinion on drug discovery
INTRODUCTION: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is often therapeutically challenging. While research has advanced our understanding of IBS pathophysiology, developing precise models to predict drug response and...

Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models.

Molecular informatics
The blood brain barrier (BBB) is an endothelial-derived structure which restricts the movement of certain molecules between the general somatic circulatory system to the central nervous system (CNS). While the BBB maintains homeostasis by regulating ...

Embracing the changes and challenges with modern early drug discovery.

Expert opinion on drug discovery
INTRODUCTION: The landscape of early drug discovery is rapidly evolving, fueled by significant advancements in artificial intelligence (AI) and machine learning (ML), which are transforming the way drugs are discovered. As traditional drug discovery ...

Enhancing clinical trial outcome prediction with artificial intelligence: a systematic review.

Drug discovery today
Clinical trials are pivotal in drug development yet fraught with uncertainties and resource-intensive demands. The application of AI models to forecast trial outcomes could mitigate failures and expedite the drug discovery process. This review discus...

A Tutorial and Use Case Example of the eXtreme Gradient Boosting (XGBoost) Artificial Intelligence Algorithm for Drug Development Applications.

Clinical and translational science
Approaches to artificial intelligence and machine learning (AI/ML) continue to advance in the field of drug development. A sound understanding of the underlying concepts and guiding principles of AI/ML implementation is a prerequisite to identifying ...

Applications of Artificial Intelligence in Drug Repurposing.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Drug repurposing identifies new therapeutic uses for the existing drugs originally developed for different indications, aiming at capitalizing on the established safety and efficacy profiles of known drugs. Thus, it is beneficial to bypass of early s...