AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cell Culture Techniques

Showing 1 to 10 of 54 articles

Clear Filters

Robotic cell processing facility for clinical research of retinal cell therapy.

SLAS technology
The consistent production of high-quality cells in cell therapy highlights the potential of automated manufacturing. Humanoid robots are a useful option for transferring technology to automate human cell cultures. This study evaluated a robotic cell-...

Challenges in developing cell culture media using machine learning.

Biotechnology advances
Microbial and mammalian cells are widely used in the food, pharmaceutical, and medical industries. Developing or optimizing culture media is essential to improve cell culture performance as a critical technology in cell culture engineering. Methodolo...

Prediction of Spheroid Cell Death Using Fluorescence Staining and Convolutional Neural Networks.

Chemical research in toxicology
Three-dimensional (3D) cell culture is emerging for drug design and drug screening. Skin toxicity is one of the most important assays for determining the toxicity of a compound before being used in skin application. Much work has been done to find an...

Angio-Net: deep learning-based label-free detection and morphometric analysis of angiogenesis.

Lab on a chip
Despite significant advancements in three-dimensional (3D) cell culture technology and the acquisition of extensive data, there is an ongoing need for more effective and dependable data analysis methods. These concerns arise from the continued relian...

Development of a robotic cluster for automated and scalable cell therapy manufacturing.

Cytotherapy
BACKGROUND AIMS: The production of commercial autologous cell therapies such as chimeric antigen receptor T cells requires complex manual manufacturing processes. Skilled labor costs and challenges in manufacturing scale-out have contributed to high ...

An innovative hybrid modeling approach for simultaneous prediction of cell culture process dynamics and product quality.

Biotechnology journal
The use of hybrid models is extensively described in the literature to predict the process evolution in cell cultures. These models combine mechanistic and machine learning methods, allowing the prediction of complex process behavior, in the presence...

Reinforcement learning-guided control strategies for CAR T-cell activation and expansion.

Biotechnology and bioengineering
Reinforcement learning (RL), a subset of machine learning (ML), could optimize and control biomanufacturing processes, such as improved production of therapeutic cells. Here, the process of CAR T-cell activation by antigen-presenting beads and their ...

Rapid total sialic acid monitoring during cell culture process using a machine learning model based soft sensor.

Biotechnology progress
Total sialic acid content (TSA) in biotherapeutic proteins is often a critical quality attribute as it impacts the drug efficacy. Traditional wet chemical assays to quantify TSA in biotherapeutic proteins during cell culture typically takes several h...

Recent advances in culture medium design for enhanced production of monoclonal antibodies in CHO cells: A comparative study of machine learning and systems biology approaches.

Biotechnology advances
The production of monoclonal antibodies (mAbs) using Chinese Hamster Ovary (CHO) cells has revolutionized the treatment of numerous diseases, solidifying their position as a cornerstone of the biopharmaceutical industry. However, achieving maximum mA...

Machine Learning-Powered Optimization of a CHO Cell Cultivation Process.

Biotechnology and bioengineering
Chinese Hamster Ovary (CHO) cells are the most widely used cell lines to produce recombinant therapeutic proteins such as monoclonal antibodies (mAbs). However, the optimization of the CHO cell culture process is very complex and influenced by variou...