AIMC Topic: Antineoplastic Agents

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Prediction of survival rate and effect of drugs on cancer patients with somatic mutations of genes: An AI-based approach.

Chemical biology & drug design
The causal role of somatic mutation and its interrelationship with gene expression profile during tumor development has already been observed, which plays a major role to decide the cancer grades and overall survival. Accurate and robust prediction o...

[Synergistic drug combination prediction in multi-input neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Synergistic effects of drug combinations are very important in improving drug efficacy or reducing drug toxicity. However, due to the complex mechanism of action between drugs, it is expensive to screen new drug combinations through trials. It is wel...

Enzyme-powered Janus platelet cell robots for active and targeted drug delivery.

Science robotics
Transforming natural cells into functional biocompatible robots capable of active movement is expected to enhance the functions of the cells and revolutionize the development of synthetic micromotors. However, present cell-based micromotor systems co...

Multifunctional surface microrollers for targeted cargo delivery in physiological blood flow.

Science robotics
Mobile microrobots offer great promise for minimally invasive targeted medical theranostic applications at hard-to-access regions inside the human body. The circulatory system represents the ideal route for navigation; however, blood flow impairs pro...

Ensembled machine learning framework for drug sensitivity prediction.

IET systems biology
Drug sensitivity prediction is one of the critical tasks involved in drug designing and discovery. Recently several online databases and consortiums have contributed to providing open access to pharmacogenomic data. These databases have helped in dev...

Adaptive back-stepping cancer control using Legendre polynomials.

IET systems biology
Here, a model-free controller for cancer treatment is presented. The treatment objective is to find a proper drug dosage that can reduce the population of tumour cells. Recently, some solutions have been proposed according to the control theory. In t...

Current Advances and Limitations of Deep Learning in Anticancer Drug Sensitivity Prediction.

Current topics in medicinal chemistry
Anticancer drug screening can accelerate drug discovery to save the lives of cancer patients, but cancer heterogeneity makes this screening challenging. The prediction of anticancer drug sensitivity is useful for anticancer drug development and the i...

Evolution of Machine Learning Algorithms in the Prediction and Design of Anticancer Peptides.

Current protein & peptide science
Peptides act as promising anticancer agents due to their ease of synthesis and modifications, enhanced tumor penetration, and less systemic toxicity. However, only limited success has been achieved so far, as experimental design and synthesis of anti...