AIMC Topic: Doxorubicin

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Microfluidics-based fabrication and targeted motion control of multimodal therapeutic hydrogel capsule microrobots.

Journal of materials chemistry. B
In cancer combination therapy, micro-robot systems that integrate multiple therapeutic functions have emerged as a key direction for overcoming the limitations of traditional treatments. This study proposes a magnetic thermosensitive hydrogel capsule...

Machine Learning-Guided microfluidic optimization of clinically inspired liposomes for nanomedicine applications.

International journal of pharmaceutics
Liposomes have transformed drug delivery by enhancing the solubility, stability, and bioavailability of therapeutic agents, driving widespread clinical adoption and contributing to a rapidly expanding multi-billion-dollar market. However, despite the...

Predicted peptide scaffolds for drug screening in endometrial cancer organoids.

Scientific reports
AlphaFold, a deep learning-based platform widely used to predict protein and peptide structures, was employed in this study to model the self-assembling peptide RFC, which demonstrated a stable α-helical structure with high confidence. This structura...

Label-free classification of nanoscale drug delivery systems using hyperspectral imaging and convolutional neural networks.

International journal of pharmaceutics
Label-free characterization of nanoscale drug delivery systems remains a critical challenge in pharmaceutical research. Traditional analytical methods, such as cryo-electron microscopy, are labor-intensive, low-throughput, and often require labeling,...

Enhancing the Predictive Performance of Molecularly Imprinted Polymer-Based Electrochemical Sensors Using a Stacking Regressor Ensemble of Machine Learning Models.

ACS sensors
The performance of electrochemical sensors is influenced by various factors. To enhance the effectiveness of these sensors, it is crucial to find the right balance among these factors. Researchers and engineers continually explore innovative approach...

Learning Chemotherapy Drug Action via Universal Physics-Informed Neural Networks.

Pharmaceutical research
OBJECTIVE: Quantitative systems pharmacology (QSP) is widely used to assess drug effects and toxicity before the drug goes to clinical trial. However, significant manual distillation of the literature is needed in order to construct a QSP model. Para...

Single-Cell Array Enhanced Cell Damage Recognition Using Artificial Intelligence for Anticancer Drug Discovery.

Analytical chemistry
This work developed a cell damage recognition method based on single-cell arrays using an artificial intelligence tool. The method uses micropatterns (single-cell micropatches and microwells) to isolate each cell in an ordered array to minimize cell ...

Predicting doxorubicin-induced cardiotoxicity in breast cancer: leveraging machine learning with synthetic data.

Medical & biological engineering & computing
Doxorubicin (DOXO) is a primary treatment for breast cancer but can cause cardiotoxicity in over 25% of patients within the first year post-chemotherapy. Recognizing at-risk patients before DOXO initiation offers pathways for alternative treatments o...

AlgaeSperm: Microalgae-Based Soft Magnetic Microrobots for Targeted Tumor Treatment.

Small (Weinheim an der Bergstrasse, Germany)
Magnetic microrobots are significant platforms for targeted drug delivery, among which sperm-inspired types have attracted much attention due to their flexible undulation. However, mass production of sperm-like soft magnetic microrobots with high-spe...

Toward Resolving Heterogeneous Mixtures of Nanocarriers in Drug Delivery Systems through Light Scattering and Machine Learning.

ACS nano
Nanocarriers (NCs) have emerged as a revolutionary approach in targeted drug delivery, promising to enhance drug efficacy and reduce toxicity through precise targeting and controlled release mechanisms. Despite their potential, the clinical adoption ...