AIMC Topic: Trastuzumab
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Tuning antibody stability and function by rational designs of framework mutations.
mAbs
Jul 13, 2025
Artificial intelligence and machine learning models have been developed to engineer antibodies for specific recognition of antigens. These approaches, however, often focus on the antibody complementarity-determining region (CDR) whilst ignoring the i...
A new strategy to HER2-specific antibody discovery through artificial intelligence-powered phage display screening based on the Trastuzumab framework.
Biochimica et biophysica acta. Molecular basis of disease
Mar 7, 2025
Human epidermal growth factor receptor 2 (HER2) is a recognized drug target, and it serves as a critical target for various cancer treatments, necessitating the discovery of more antibodies for therapeutic and detection purposes. Here, we have develo...
Artificial Intelligence-Powered Human Epidermal Growth Factor Receptor 2 and Tumor Microenvironment Analysis in Human Epidermal Growth Factor Receptor 2-Amplified Metastatic Colorectal Cancer: Exploratory Analysis of Phase II TRIUMPH Trial.
JCO precision oncology
Jan 17, 2025
PURPOSE: Human epidermal growth factor receptor 2 (HER2)-targeted therapies have shown promise in treating -amplified metastatic colorectal cancer (mCRC). Identifying optimal biomarkers for treatment decisions remains challenging. This study explores...
Deep learning-based prediction of HER2 status and trastuzumab treatment efficacy of gastric adenocarcinoma based on morphological features.
Journal of translational medicine
Jan 6, 2025
BACKGROUND: First-line treatment for advanced gastric adenocarcinoma (GAC) with human epidermal growth factor receptor 2 (HER2) is trastuzumab combined with chemotherapy. In clinical practice, HER2 positivity is identified through immunohistochemistr...
Exploring an novel diagnostic gene of trastuzumab-induced cardiotoxicity based on bioinformatics and machine learning.
Scientific reports
Dec 3, 2024
Trastuzumab (Tra)-induced cardiotoxicity (TIC) is a serious side effect of cancer chemotherapy, which can seriously harm the health of cancer patients. However, there is currently a lack of effective and reliable biomarkers for the early diagnosis of...
Artificial Intelligence-Enhanced Risk Stratification of Cancer Therapeutics-Related Cardiac Dysfunction Using Electrocardiographic Images.
Circulation. Cardiovascular quality and outcomes
Sep 2, 2024
BACKGROUND: Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intelligence (AI) to...
Cardiotoxicity
Anthracyclines
Electrocardiography
Predictive Value of Tests
Ventricular Dysfunction, Left
Trastuzumab
Antineoplastic Agents
Time Factors
United States
Female
Risk Factors
Aged
Male
Ventricular Function, Left
Stroke Volume
Middle Aged
Humans
Risk Assessment
Artificial Intelligence
Retrospective Studies
A high hydrophobic moment arginine-rich peptide screened by a machine learning algorithm enhanced ADC antitumor activity.
Journal of peptide science : an official publication of the European Peptide Society
Jul 1, 2024
Cell-penetrating peptides (CPPs) with better biomolecule delivery properties will expand their clinical applications. Using the MLCPP2.0 machine algorithm, we screened multiple candidate sequences with potential cellular uptake ability from the nucle...
Deep learning-assisted monitoring of trastuzumab efficacy in HER2-Overexpressing breast cancer via SERS immunoassays of tumor-derived urinary exosomal biomarkers.
Biosensors & bioelectronics
May 1, 2024
Monitoring drug efficacy is significant in the current concept of companion diagnostics in metastatic breast cancer. Trastuzumab, a drug targeting human epidermal growth factor receptor 2 (HER2), is an effective treatment for metastatic breast cancer...
Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model.
European radiology
Feb 8, 2024
OBJECTIVES: Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer. New measures are needed for a precise risk stratification to guide (de-)escalation of anti-HER2 strategy.
Aggregate Formation and Antibody Stability in Infusion Bags: The Impact of Manual and Robotic Compounding of Monoclonal Antibodies.
Journal of pharmaceutical sciences
Oct 13, 2023
Monoclonal antibodies (mAbs) can be damaged during the aseptic compounding process, with aggregation being the most prevalent form of degradation. Protein aggregates represent one of several risk factors for undesired immunogenicity of mAbs, which ca...
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