AIMC Topic: Antineoplastic Agents

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Evaluation of Robotic Systems on Cytotoxic Drug Preparation: A Systematic Review and Meta-Analysis.

Medicina (Kaunas, Lithuania)
: With the increased prevalence of patients with cancer, the demand for preparing cytotoxic drugs was increased by health-system pharmacists. To reduce the workload and contamination of work areas in pharmacies, compounding robots preparing cytotoxic...

DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics.

Scientific reports
Modern oncology offers a wide range of treatments and therefore choosing the best option for particular patient is very important for optimal outcome. Multi-omics profiling in combination with AI-based predictive models have great potential for strea...

Deep Learning-Based Artificial Intelligence to Investigate Targeted Nanoparticles' Uptake in TNBC Cells.

International journal of molecular sciences
Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer in women. It has the poorest prognosis along with limited therapeutic options. Smart nano-based carriers are emerging as promising approaches in treating TNBC due to...

Comparing different robots available in the European market for the preparation of injectable chemotherapy and recommendations to users.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
INTRODUCTION: Recent advances in technology have made it possible to develop robots for preparing injectable anticancer drugs. This study aims to compare characteristics between robots available in the European market in 2022 and to help future pharm...

DNN-PNN: A parallel deep neural network model to improve anticancer drug sensitivity.

Methods (San Diego, Calif.)
With the rapid development of deep learning techniques and large-scale genomics database, it is of great potential to apply deep learning to the prediction task of anticancer drug sensitivity, which can effectively improve the identification efficien...

Development of GBRT Model as a Novel and Robust Mathematical Model to Predict and Optimize the Solubility of Decitabine as an Anti-Cancer Drug.

Molecules (Basel, Switzerland)
The efficient production of solid-dosage oral formulations using eco-friendly supercritical solvents is known as a breakthrough technology towards developing cost-effective therapeutic drugs. Drug solubility is a significant parameter which must be m...

Anti-Cancer Drug Solubility Development within a Green Solvent: Design of Novel and Robust Mathematical Models Based on Artificial Intelligence.

Molecules (Basel, Switzerland)
Nowadays, supercritical CO(SC-CO) is known as a promising alternative for challengeable organic solvents in the pharmaceutical industry. The mathematical prediction and validation of drug solubility through SC-CO system using novel artificial intelli...

Contribution of an anticancer drug compounding robot in reducing the risks of manual preparation in a hospital pharmacy unit specialized in oncology.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
INTRODUCTION: In the last few years, pharmaceutical technology has evolved. In the field of oncology pharmacy, robots for the preparation of anti-cancer drugs have appeared to progressively replace manual preparation. The objective of this study is t...

ACPNet: A Deep Learning Network to Identify Anticancer Peptides by Hybrid Sequence Information.

Molecules (Basel, Switzerland)
Cancer is one of the most dangerous threats to human health. One of the issues is drug resistance action, which leads to side effects after drug treatment. Numerous therapies have endeavored to relieve the drug resistance action. Recently, anticancer...