Prescriptions

Developing a Knowledge Graph for Pharmacokinetic Natural Product-Drug Interactions.

BACKGROUND: Pharmacokinetic natural product-drug interactions (NPDIs) occur when botanical or other natural products are co-consumed with pharmaceutical drugs. With the growing use of natural products, the risk for potential NPDIs and consequent adverse events has increased. Understanding mechanisms of NPDIs is key to preventing or minimizing adverse events. Although biomedical knowledge graphs (K...

Deep Learning Model for Efficient Protein-Ligand Docking with Implicit Side-Chain Flexibility.

Protein-ligand docking is an essential tool in structure-based drug design with applications ranging from virtual high-throughput screening to pose prediction for lead optimization. Most docking programs for pose prediction are optimized for redocking to an existing cocrystallized protein structure, ignoring protein flexibility. In real-world drug design applications, however, protein flexibility ...

Priority-based replenishment policy for robotic dispensing in central fill pharmacy systems: a simulation-based study.

In recent years, companies that operate pharmacy store chains have adopted centralized and automated fulfillment systems, which are called Central Fil...

AlphaFold, allosteric, and orthosteric drug discovery: Ways forward.

Drug discovery is arguably a highly challenging and significant interdisciplinary aim. The stunning success of the artificial intelligence-powered Alp...

PLA-GNN: Computational inference of protein subcellular location alterations under drug treatments with deep graph neural networks.

The aberrant protein sorting has been observed in many conditions, including complex diseases, drug treatments, and environmental stresses. It is impo...

How can machine learning and multiscale modeling benefit ocular drug development?

The eyes possess sophisticated physiological structures, diverse disease targets, limited drug delivery space, distinctive barriers, and complicated b...

A Fine-Grained Recognition Neural Network with High-Order Feature Maps via Graph-Based Embedding for Natural Bird Diversity Conservation.

The conservation of avian diversity plays a critical role in maintaining ecological balance and ecosystem function, as well as having a profound impac...

The curse and blessing of abundance-the evolution of drug interaction databases and their impact on drug network analysis.

BACKGROUND: Widespread bioinformatics applications such as drug repositioning or drug-drug interaction prediction rely on the recent advances in machi...

Prescribing patterns of SGLT-2 inhibitors for patients with heart failure: A two-center analysis.

BACKGROUND: Sodium glucose co-transporter 2 inhibitors (SGLT2i) have been proven to reduce the combined risk of cardiovascular death and hospitalizati...

The promise and peril of interactive embodied agents for studying non-verbal communication: a machine learning perspective.

In face-to-face interactions, parties rapidly react and adapt to each other's words, movements and expressions. Any science of face-to-face interactio...

Applications and prospects of cryo-EM in drug discovery.

Drug discovery is a crucial part of human healthcare and has dramatically benefited human lifespan and life quality in recent centuries, however, it i...

BCM-DTI: A fragment-oriented method for drug-target interaction prediction using deep learning.

The identification of drug-target interaction (DTI) is significant in drug discovery and development, which is usually of high cost in time and money ...

Analyzing the Relationship among Social Capital, Dynamic Capability, and Farmers' Cooperative Performance Using Lightweight Deep Learning Model: A Case Study of Liaoning Province.

The purpose of this study is to understand the relationship between social capital and the performance of Farmers' Cooperatives (Cooperatives) and exp...

MSEDDI: Multi-Scale Embedding for Predicting Drug-Drug Interaction Events.

A norm in modern medicine is to prescribe polypharmacy to treat disease. The core concern with the co-administration of drugs is that it may produce a...

Strategy toward Kinase-Selective Drug Discovery.

Kinase drug selectivity is the ground challenge in cancer research. Due to the structurally similar kinase drug pockets, off-target inhibitor toxicity...

A Machine Learning-Combined Flexible Sensor for Tactile Detection and Voice Recognition.

Intelligent sensors have attracted substantial attention for various applications, including wearable electronics, artificial intelligence, healthcare...

Gene-environment interaction analysis via deep learning.

Gene-environment (G-E) interaction analysis plays an important role in studying complex diseases. Extensive methodological research has been conducted...

MecDDI: Clarified Drug-Drug Interaction Mechanism Facilitating Rational Drug Use and Potential Drug-Drug Interaction Prediction.

Drug-drug interactions (DDIs) are a major concern in clinical practice and have been recognized as one of the key threats to public health. To address...

Geometric Interaction Graph Neural Network for Predicting Protein-Ligand Binding Affinities from 3D Structures (GIGN).

Predicting protein-ligand binding affinities (PLAs) is a core problem in drug discovery. Recent advances have shown great potential in applying machin...

Investigations into the use of machine learning to predict drug dosage form design to obtain desired release profiles for 3D printed oral medicines.

Three-dimensional (3D) printing, digitalization, and artificial intelligence (AI) are gaining increasing interest in modern medicine. All three aspect...