AIMC Topic: Antibodies, Monoclonal
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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...
Predicting purification process fit of monoclonal antibodies using machine learning.
mAbs
Jan 9, 2025
In early-stage development of therapeutic monoclonal antibodies, assessment of the viability and ease of their purification typically requires extensive experimentation. However, the work required for upstream protein expression and downstream purifi...
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...
Machine Learning Models for Predicting Monoclonal Antibody Biophysical Properties from Molecular Dynamics Simulations and Deep Learning-Based Surface Descriptors.
Molecular pharmaceutics
Nov 28, 2024
Monoclonal antibodies (mAbs) have found extensive applications and development in treating various diseases. From the pharmaceutical industry's perspective, the journey from the design and development of mAbs to clinical testing and large-scale produ...
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...
Crowdsourcing Adverse Events Associated With Monoclonal Antibodies Targeting Calcitonin Gene-Related Peptide Signaling for Migraine Prevention: Natural Language Processing Analysis of Social Media.
JMIR formative research
Nov 8, 2024
BACKGROUND: Clinical trials demonstrate the efficacy and tolerability of medications targeting calcitonin gene-related peptide (CGRP) signaling for migraine prevention. However, these trials may not accurately reflect the real-world experiences of mo...
Particle formation in response to different protein formulations and containers: Insights from machine learning analysis of particle images.
Journal of pharmaceutical sciences
Oct 9, 2024
Subvisible particle count is a biotherapeutics stability indicator widely used by pharmaceutical industries. A variety of stresses that biotherapeutics are exposed to during development can impact particle morphology. By classifying particle morpholo...
Predicting Peptide Ionization Efficiencies for Electrospray Ionization Mass Spectrometry Using Machine Learning.
Journal of the American Society for Mass Spectrometry
Sep 9, 2024
Mass spectrometry (MS) is inherently an information-rich technique. In this era of big data, label-free MS quantification for nontargeted studies has gained increasing popularity, especially for complex systems. One of the cornerstones of successful ...
A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.
JAMA health forum
Sep 6, 2024
IMPORTANCE: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (...
Male
Middle Aged
Severity of Illness Index
Adolescent
Antibodies, Viral
Health Policy
Aged
Young Adult
Adult
Female
SARS-CoV-2
Hospitalization
COVID-19
COVID-19 Drug Treatment
Retrospective Studies
Humans
Health Care Rationing
Electronic Health Records
Machine Learning
Antibodies, Monoclonal
Emergency Use Authorization
Random Forest
United States Food and Drug Administration
Accurate prediction of CDR-H3 loop structures of antibodies with deep learning.
eLife
Jun 26, 2024
Accurate prediction of the structurally diverse complementarity determining region heavy chain 3 (CDR-H3) loop structure remains a primary and long-standing challenge for antibody modeling. Here, we present the H3-OPT toolkit for predicting the 3D st...
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