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Pharmaceutical Preparations

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Comprehensive Survey of Recent Drug Discovery Using Deep Learning.

International journal of molecular sciences
Drug discovery based on artificial intelligence has been in the spotlight recently as it significantly reduces the time and cost required for developing novel drugs. With the advancement of deep learning (DL) technology and the growth of drug-related...

SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures.

BMC bioinformatics
BACKGROUND: One of the major challenges in precision medicine is accurate prediction of individual patient's response to drugs. A great number of computational methods have been developed to predict compounds activity using genomic profiles or chemic...

Biodegradable Small-Scale Swimmers for Biomedical Applications.

Advanced materials (Deerfield Beach, Fla.)
Most forms of biomatter are ephemeral, which means they transform or deteriorate after a certain time. From this perspective, implantable healthcare devices designed for temporary treatments should exhibit the ability to degrade and either blend in w...

CBDPS 1.0: A Python GUI Application for Machine Learning Models to Predict Bitter-Tasting Children's Oral Medicines.

Chemical & pharmaceutical bulletin
Bitter tastes are innately aversive and are thought to help protect animals from consuming poisons. Children are extremely sensitive to drug tastes, and their compliance is especially poor with bitter medicine. Therefore, judging whether a drug is bi...

AttentionDDI: Siamese attention-based deep learning method for drug-drug interaction predictions.

BMC bioinformatics
BACKGROUND: Drug-drug interactions (DDIs) refer to processes triggered by the administration of two or more drugs leading to side effects beyond those observed when drugs are administered by themselves. Due to the massive number of possible drug pair...

Computational pharmaceutics - A new paradigm of drug delivery.

Journal of controlled release : official journal of the Controlled Release Society
In recent decades pharmaceutics and drug delivery have become increasingly critical in the pharmaceutical industry due to longer time, higher cost, and less productivity of new molecular entities (NMEs). However, current formulation development still...

KenDTI: An Ensemble Model for Predicting Drug-Target Interaction by Integrating Multi-Source Information.

IEEE/ACM transactions on computational biology and bioinformatics
The identification of drug-target interactions (DTIs) is an essential step in the process of drug discovery. As experimental validation suffers from high cost and low success rate, various computational models have been exploited to infer potential D...

A Convolutional Neural Network System to Discriminate Drug-Target Interactions.

IEEE/ACM transactions on computational biology and bioinformatics
Biological targets are most commonly proteins such as enzymes, ion channels, and receptors. They are anything within a living organism to bind with some other entities (like an endogenous ligand or a drug), resulting in change in their behaviors or f...

Patentability challenges associated with emerging pharmaceutical technologies.

Pharmaceutical patent analyst
According to the recent patent filing trends, it has been observed that certain pharmaceutical technologies are more popular than others and are commonly referred to as emerging technologies. The emerging technologies in the pharmaceutical sector inc...

Disrupting 3D printing of medicines with machine learning.

Trends in pharmacological sciences
3D printing (3DP) is a progressive technology capable of transforming pharmaceutical development. However, despite its promising advantages, its transition into clinical settings remains slow. To make the vital leap to mainstream clinical practice an...