Latest Articles for Pharmaceutical Research

DigiLoCs improves predictions in drug testing, enhancing safety and effectiveness.

GShot generates high-quality graphs from limited training data using meta-learning techniques.

iScore offers a faster method for predicting drug binding to proteins.

New techniques improve drug candidate identification by capturing protein flexibility.

Examining the role of patents in pharmaceutical innovation and research.

Exploring the potential of quantum neural networks in chemical and pharmaceutical research.

ShapeLinker optimizes linker design for better drug efficacy using machine learning.

Research explores using known drugs for new COVID-19 treatment options.

Discover how fractional compartmental models improve drug behavior understanding.

New methods enhance understanding of quantum systems through excited states and complex interactions.

Exploring how enhanced sampling and machine learning improve molecular dynamics simulations.

This article assesses the strengths and weaknesses of pharmacometric models in drug trials.

Research compares NLME model approaches for drug effect estimation.

Research highlights the role of enzymes in producing N-nitroso compounds.

Aurodox shows promise in fighting tough infections caused by resistant bacteria.

Research reveals how antibiotic combinations affect bacterial growth and survival rates.

A new method improves predictions of how drugs interact with targets, saving time and resources.

New methods improve understanding of drug binding and effectiveness.

Examining CTLA-4's role in immune control and its medical applications.

Examining the role of γ-secretase in Alzheimer's disease and its complex interactions.

Research reveals promising quinoxaline compounds for combating malaria resistance.

New methods reveal potential for sustainable terpenoid production.

Research on sparteine shows promise for drug development and agricultural improvements.

Study explores safer primaquine dosing for malaria treatment in G6PD deficient patients.

New approaches in cancer care focus on targeted treatments based on tumor genetics.

Researchers enhance drug screening methods for viral diseases through graph neural fingerprints.

A new model, ADRNet, improves predictions of drug-related side effects.

Using machine learning to classify drugs effectively for better treatment outcomes.

Researchers use genetic insights to improve drug development for complex diseases.

Examining semaglutide's effects on growth and metabolism in malnourished juvenile mice.

Research reveals how bacteria resist the antibiotic daptomycin through lipid changes.

New database and tools improve detection of antibiotic resistance.

GIT-Mol integrates graphs, images, and text for better molecular data handling.

Researchers are improving drug design with innovative techniques for better medication development.

DiffHopp improves drug discovery by generating novel molecule structures for better efficacy.

This article discusses challenges and innovations in drug design using advanced technologies.

A fresh approach enhances prediction accuracy in drug discovery using bioactivity data.

Researchers developed a method to create diverse 3D molecules using existing shapes.

Using AI-generated data to enhance molecule discovery and drug development.

ATM simplifies predicting binding energy for drug discovery.