AIMC Topic: CHO Cells
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Accelerating biopharmaceutical cell line selection with label-free multimodal nonlinear optical microscopy and machine learning.
Communications biology
Feb 3, 2025
The selection of high-performing cell lines is crucial for biopharmaceutical production but is often time-consuming and labor-intensive. We investigated label-free multimodal nonlinear optical microscopy for non-perturbative profiling of biopharmaceu...
Machine Learning-Powered Optimization of a CHO Cell Cultivation Process.
Biotechnology and bioengineering
Jan 31, 2025
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...
Linsitinib inhibits proliferation and induces apoptosis of both IGF-1R and TSH-R expressing cells.
Frontiers in immunology
Dec 11, 2024
BACKGROUND: The insulin-like growth factor 1 receptor (IGF-1R) and the thyrotropin receptor (TSH-R) are expressed on orbital cells and thyrocytes. These receptors are targeted in autoimmune-induced thyroid eye disease (TED). Effective therapeutic tre...
Novel active Trp- and Arg-rich antimicrobial peptides with high solubility and low red blood cell toxicity designed using machine learning tools.
International journal of antimicrobial agents
Dec 5, 2024
BACKGROUND: Given the rising number of multidrug-resistant (MDR) bacteria, there is a need to design synthetic antimicrobial peptides (AMPs) that are highly active, non-hemolytic, and highly soluble. Machine learning tools allow the straightforward i...
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
Nov 19, 2024
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...
Rapid total sialic acid monitoring during cell culture process using a machine learning model based soft sensor.
Biotechnology progress
Jul 2, 2024
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...
Optimizing recombinant antibody fragment production: A comparison of artificial intelligence and statistical modeling.
Biotechnology and applied biochemistry
May 19, 2024
Maximizing the recombinant protein yield necessitates optimizing the production medium. This can be done using a variety of methods, including the conventional "one-factor-at-a-time" approach and more recent statistical and mathematical methods such ...
Insights into the transformation of natural organic matter during UV/peroxydisulfate treatment by FT-ICR MS and machine learning: Non-negligible formation of organosulfates.
Water research
Apr 1, 2024
Natural organic matter (NOM) is a major sink of radicals in advanced oxidation processes (AOPs) and understanding the transformation of NOM is important in water treatment. By using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR ...
Leveraging machine learning to dissect role of combinations of amino acids in modulating the effect of zinc on mammalian cell growth.
Biotechnology progress
Feb 15, 2024
Although the contributions of individual components of cell culture media are largely known, their combinatorial effects are far less understood. Experiments varying one component at a time cannot identify combinatorial effects, and analysis of the l...
Data-driven prediction models for forecasting multistep ahead profiles of mammalian cell culture toward bioprocess digital twins.
Biotechnology and bioengineering
Apr 20, 2023
Recently, the advancement in process analytical technology and artificial intelligence (AI) has enabled the generation of enormous culture data sets from biomanufacturing processes that produce various recombinant therapeutic proteins (RTPs), such as...
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