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Pharmaceutical Preparations

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Deep learning large-scale drug discovery and repurposing.

Nature computational science
Large-scale drug discovery and repurposing is challenging. Identifying the mechanism of action (MOA) is crucial, yet current approaches are costly and low-throughput. Here we present an approach for MOA identification by profiling changes in mitochon...

Perspectives on the use of machine learning for ADME prediction at AstraZeneca.

Xenobiotica; the fate of foreign compounds in biological systems
A drug's pharmacokinetic (PK) profile will determine its dose and the frequency of administration as well as the likelihood of observing any adverse drug reactions.It is important to understand these PK properties as early as possible in the drug dis...

MGNDTI: A Drug-Target Interaction Prediction Framework Based on Multimodal Representation Learning and the Gating Mechanism.

Journal of chemical information and modeling
Drug-Target Interaction (DTI) prediction facilitates acceleration of drug discovery and promotes drug repositioning. Most existing deep learning-based DTI prediction methods can better extract discriminative features for drugs and proteins, but they ...

Actionable Predictions of Human Pharmacokinetics at the Drug Design Stage.

Molecular pharmaceutics
We present a novel computational approach for predicting human pharmacokinetics (PK) that addresses the challenges of early stage drug design. Our study introduces and describes a large-scale data set of 11 clinical PK end points, encompassing over 2...

Predicting Drug-Target Interactions Via Dual-Stream Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
Drug target interaction prediction is a crucial stage in drug discovery. However, brute-force search over a compound database is financially infeasible. We have witnessed the increasing measured drug-target interactions records in recent years, and t...

GCGACNN: A Graph Neural Network and Random Forest for Predicting Microbe-Drug Associations.

Biomolecules
The interaction between microbes and drugs encompasses the sourcing of pharmaceutical compounds, microbial drug degradation, the development of , and the impact of on host drug metabolism and immune modulation. These interactions significantly impac...

Navigating the frontier of drug-like chemical space with cutting-edge generative AI models.

Drug discovery today
Deep generative models (GMs) have transformed the exploration of drug-like chemical space (CS) by generating novel molecules through complex, nontransparent processes, bypassing direct structural similarity. This review examines five key architecture...

Deep-Learning-Guided Electrochemical Impedance Spectroscopy for Calibration-Free Pharmaceutical Moisture Content Monitoring.

ACS sensors
The moisture content of pharmaceutical powders can significantly impact the physical and chemical properties of drug formulations, solubility, flowability, and stability. However, current technologies for measuring moisture content in pharmaceutical ...

Would robots really bother with a bloody uprising?

Science robotics
In the amusing 1982 novel , robots punish their human overlords by raising prices on longevity drugs and organ transplants.

3D printed dosage forms, where are we headed?

Expert opinion on drug delivery
INTRODUCTION: 3D Printing (3DP) is an innovative fabrication technology that has gained enormous popularity through its paradigm shifts in manufacturing in several disciplines, including healthcare. In this past decade, we have witnessed the impact o...