AIMC Topic: Antineoplastic Agents

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Construction of a predictive model for the risk of moderate-to-severe cancer-related fatigue in colorectal cancer chemotherapy patients: an interpretable machine learning approach.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aimed to analyze the influencing factors of moderate-to-severe cancer-related fatigue (CRF) in colorectal cancer (CRC) chemotherapy patients and to develop a predictive risk stratification model.

Prediction of high-performing spleen-targeted lipid nanoparticles using a deep learning model for robust anticancer immunotherapy.

Journal of materials chemistry. B
Messenger RNA (mRNA) therapeutics hold significant potential across a wide range of medical applications. LNPs are the most clinically advanced mRNA delivery vehicles, but challenges such as off-target effects and liver accumulation limit their broad...

Recent Advances in Diagnostic Strategies and Nanotechnology-Based Therapies for Ovarian Cancer Treatment.

ACS applied bio materials
Ovarian cancer is a global silent killer in women and is the second most common cause of gynecologic cancer-related deaths. Despite significant research and advances in treatment, ovarian cancer treatment remains a challenge, as it is diagnosed in an...

DeepExpDR: Drug Response Prediction through Molecular Topological Grouping and Substructure-Aware Expert.

Journal of chemical information and modeling
Cancer remains a major threat to human health. Tumor heterogeneity often leads to differences in tumor growth rate, invasion capacity, drug sensitivity, and prognosis, which complicates treatment strategies. Currently, drug responses are often verifi...

Discovery of Novel 4,5-Dihydropyrrolo[3,4-]pyrazol-6()-one-Based Tubulin Inhibitors Targeting Colchicine Binding Site with Potent Anti-Ovarian Cancer Activity.

Journal of medicinal chemistry
To address the toxicity of current microtubule inhibitors, we employed the GeminiMol deep learning model to screen the Zinc20 database, identifying a novel 4,5-dihydropyrrolo[3,4-]pyrazol-6(2)-one scaffold () targeting the colchicine binding site. Su...

Structural stability-guided scaffold hopping and computational modeling of tankyrase inhibitors targeting colorectal cancer.

PloS one
Colorectal cancer is one of the leading causes of cancer-related deaths worldwide, mainly due to aberrant Wnt/β-catenin signaling resulting from APC mutations. Tankyrase is a key regulator of this pathway and plays a crucial role in stabilizing AXIN,...

PyaiVS unifies AI workflows to accelerate ligand discovery and yields ABCG2 inhibitors.

European journal of medicinal chemistry
Developing optimized AI models for virtual screening requires coordinated selection of algorithms, molecular representations, and data splitting strategies, yet lacks integrated tools. We present PyaiVS, a Python package that integrates nine machine ...

DGSS: A Dynamic Interaction Graph Neural Network with Specific Substructure Awareness for Drug Synergy Prediction.

Journal of chemical information and modeling
Combination therapy presents a transformative approach to treating complex diseases such as cancer by mitigating toxicity and resistance challenges inherent to monotherapy. A critical gap in current computational methods, however, lies in their inabi...

TuNa-AI: A Hybrid Kernel Machine To Design Tunable Nanoparticles for Drug Delivery.

ACS nano
Artificial intelligence (AI) has the potential to transform nanoparticle development for drug delivery; however, existing strategies typically optimize either material selection or component ratios in isolation. To enable simultaneous optimization of...