AIMC Topic: Drug Screening Assays, Antitumor

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Ultradense Electrochemical Chip and Machine Learning for High-Throughput, Accurate Anticancer Drug Screening.

ACS sensors Nov 29, 2024
Despite the potentialities of electrochemical sensors, these devices still encounter challenges in devising high-throughput and accurate drug susceptibility testing. The lack of platforms for providing these analyses over the preclinical trials of dr...
Humans Machine Learning Antineoplastic Agents Cell Line, Tumor Doxorubicin High-Throughput Screening Assays Cell Survival Drug Screening Assays, Antitumor Electrochemical Techniques
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Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response.

Genes Nov 12, 2024
Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. The anoikis-related prognostic signature (ANRS) was gene...
Reverse Transcriptase Polymerase Chain Reaction Immunotherapy Enzyme-Linked Immunosorbent Assay Treatment Outcome Gene Expression Profiling Transcriptome Real-Time Polymerase Chain Reaction Blotting, Western Imatinib Mesylate Proportional Hazards Models Anoikis Databases, Genetic Predictive Value of Tests Female Drug Screening Assays, Antitumor Reproducibility of Results Gene Expression Aged Breast Neoplasms Tumor Microenvironment Machine Learning Biomarkers, Tumor Prognosis Middle Aged Antineoplastic Agents
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Wee1 inhibitor optimization through deep-learning-driven decision making.

European journal of medicinal chemistry Sep 29, 2024
Deep learning has gained increasing attention in recent years, yielding promising results in hit screening and molecular optimization. Herein, we employed an efficient strategy based on multiple deep learning techniques to optimize Wee1 inhibitors, w...
Dose-Response Relationship, Drug Protein-Tyrosine Kinases Decision Making Drug Screening Assays, Antitumor Deep Learning Cell Line, Tumor Cell Proliferation Structure-Activity Relationship Molecular Structure Protein Kinase Inhibitors Cell Cycle Proteins Humans Antineoplastic Agents
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Multitask Learning on Graph Convolutional Residual Neural Networks for Screening of Multitarget Anticancer Compounds.

Journal of chemical information and modeling Aug 28, 2024
Recently, various modern experimental screening pipelines and assays have been developed to find promising anticancer drug candidates. However, it is time-consuming and almost infeasible to screen an immense number of compounds for anticancer activit...
Neural Networks, Computer Machine Learning Neoplasms Antineoplastic Agents Drug Screening Assays, Antitumor Drug Evaluation, Preclinical Humans
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From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.

ChemMedChem Jun 20, 2024
Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in oncology, playing a critical role in angiogenesis, tumor growth, and metastasis. FDA-approved VEGFR-2 inhibitors are associated with diverse side effe...
Humans Molecular Structure Molecular Docking Simulation Vascular Endothelial Growth Factor Receptor-2 Drug Discovery Protein Kinase Inhibitors Antineoplastic Agents Dose-Response Relationship, Drug Deep Learning Cell Line, Tumor Drug Screening Assays, Antitumor Cell Proliferation Structure-Activity Relationship
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Deep learning unlocks label-free viability assessment of cancer spheroids in microfluidics.

Lab on a chip Jun 11, 2024
Despite recent advances in cancer treatment, refining therapeutic agents remains a critical task for oncologists. Precise evaluation of drug effectiveness necessitates the use of 3D cell culture instead of traditional 2D monolayers. Microfluidic plat...
Humans Microfluidic Analytical Techniques Cell Survival Drug Screening Assays, Antitumor Antineoplastic Agents Lab-On-A-Chip Devices Deep Learning Spheroids, Cellular Cell Line, Tumor
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SNSynergy: Similarity network-based machine learning framework for synergy prediction towards new cell lines and new anticancer drug combinations.

Computational biology and chemistry Mar 19, 2024
The computational method has been proven to be a promising means for pre-screening large-scale anticancer drug combinations to support precision oncology applications. Pioneering efforts have been made to develop machine learning technology for predi...
Humans Machine Learning Antineoplastic Agents Cell Line, Tumor Antineoplastic Combined Chemotherapy Protocols Drug Screening Assays, Antitumor Drug Synergism
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T6496 targeting EGFR mediated by T790M or C797S mutant: machine learning, virtual screening and bioactivity evaluation study.

Journal of biomolecular structure & dynamics Jan 4, 2024
Acquired resistance to EGFR is a major impediment in lung cancer treatment, highlighting the urgent need to discover novel compounds to overcome EGFR drug resistance. In this study, we utilized in silico methods and bioactivity evaluation for drug di...
Mutation Drug Resistance, Neoplasm ErbB Receptors Protein Kinase Inhibitors Cell Proliferation Drug Discovery Apoptosis Antineoplastic Agents Drug Screening Assays, Antitumor Cell Line, Tumor Humans Protein Binding Machine Learning Molecular Docking Simulation
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Noninvasive Computed Tomography-Based Deep Learning Model Predicts In Vitro Chemosensitivity Assay Results in Pancreatic Cancer.

Pancreas Nov 24, 2023
OBJECTIVES: We aimed to predict in vitro chemosensitivity assay results from computed tomography (CT) images by applying deep learning (DL) to optimize chemotherapy for pancreatic ductal adenocarcinoma (PDAC).
Carcinoma, Pancreatic Ductal Paclitaxel Drug Resistance, Neoplasm Gemcitabine Pancreatic Neoplasms Drug Screening Assays, Antitumor Fluorouracil Humans Deep Learning Tomography
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Wet-dry-wet drug screen leads to the synthesis of TS1, a novel compound reversing lung fibrosis through inhibition of myofibroblast differentiation.

Cell death & disease Dec 17, 2021
Therapies halting the progression of fibrosis are ineffective and limited. Activated myofibroblasts are emerging as important targets in the progression of fibrotic diseases. Previously, we performed a high-throughput screen on lung fibroblasts and s...
Myofibroblasts Drug Discovery Transfection Drug Screening Assays, Antitumor Humans High-Throughput Screening Assays Mice Cell Differentiation Machine Learning Idiopathic Pulmonary Fibrosis Lung Diseases Animals Bleomycin
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