AIMC Topic: Antineoplastic Agents
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Deep learning-driven drug response prediction and mechanistic insights in cancer genomics.
Scientific reports
Jul 1, 2025
In the field of cancer therapy, the diversity and heterogeneity of cancer genomes in clinical patients complicate and challenge the effective use of non-targeted drugs, as these drugs often fail to address specific genetic events. Recent advancements...
A genotype-to-drug diffusion model for generation of tailored anti-cancer small molecules.
Nature communications
Jul 1, 2025
Despite advances in precision oncology, developing effective cancer therapeutics remains a significant challenge due to tumor heterogeneity and the limited availability of well-defined drug targets. Recent progress in generative artificial intelligen...
Predicting cisplatin response in cholangiocarcinoma patients using chromosome pattern and related gene expression.
Scientific reports
Jul 1, 2025
Cholangiocarcinoma (CCA) is a prevalent bile duct cancer with limited treatment options. Cisplatin-based chemotherapy is a common approach, but response rates vary. Recently, chromosome aberrations have emerged as predictors of chemotherapy response ...
Unveiling the mechanisms and promising molecular targets of curcumin in pancreatic cancer through multi-dimensional data.
Scientific reports
Jul 1, 2025
Pancreatic cancer (PC) is a highly aggressive and fatal malignancy, primarily affecting older males. Curcumin, a potential anti-cancer agent, has been shown to regulate key molecules in cancer progression, but its specific mechanisms in PC remain unc...
Self-Driving and Detachable Lab-Microrobots Tailor Drug Delivery for Closed-Loop Stimulation of the Antitumor Immune Cycle.
ACS nano
Jun 16, 2025
Hypoxia arises in most solid tumors with insufficient blood flow, which hinders the delivery and efficacy of therapeutic agents to tumors. In this work, utilizing anaerobic bacteria capable of seeking out hypoxic areas for flourishing, we constructed...
Next-generation cancer therapeutics: unveiling the potential of liposome-based nanoparticles through bioinformatics.
Mikrochimica acta
Jun 16, 2025
Cancer remains one of the most deadly diseases in the world, requiring constant growth and improvements in therapeutic strategies. Traditional cancer treatments, such as chemotherapy, radiotherapy, and surgery, have limitations like off-target releas...
Role of artificial intelligence in cancer drug discovery and development.
Cancer letters
May 23, 2025
The role of artificial intelligence (AI) in cancer drug discovery and development has garnered significant attention due to its potential to transform the traditionally time-consuming and expensive processes involved in bringing new therapies to mark...
Interpretable prediction of drug synergy for breast cancer by random forest with features from Boolean modeling of signaling pathways.
Scientific reports
May 22, 2025
Breast cancer is a complex and challenging disease to treat, and despite progress in combating it, drug resistance remains a significant hindrance. Drug combinations have shown promising results in improving therapeutic outcomes, and many machine lea...
Microbial vitamin biosynthesis links gut microbiota dynamics to chemotherapy toxicity.
mBio
May 20, 2025
Dose-limiting toxicities pose a major barrier to cancer treatment. While preclinical studies show that the gut microbiota influences and is influenced by anticancer drugs, data from patients paired with careful side effect monitoring remains limited....
Enhancing ERα-targeted compound efficacy in breast cancer threapy with ExplainableAI and GeneticAlgorithm.
PloS one
May 20, 2025
Breast cancer remains a major cause of mortality among women globally, driving the need for advanced therapeutic solutions. This study presents a novel, comprehensive methodology integrating explainable artificial intelligence (AI), machine learning ...
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