AIMC Topic: Antibodies, Monoclonal
Clear Filters Showing 61 to 70 of 81 articles
AI-designed antibody candidates hit a crucial target.
Science (New York, N.Y.)
May 15, 2025
Companies find enticing drug leads that bind to tricky cell membrane proteins.
Bioconjugates of photon-upconversion nanoparticles with antibodies for the detection of prostate-specific antigen and p53 in heterogeneous and homogeneous immunoassays.
Nanoscale
May 9, 2025
Sensitive immunoassays for the detection of tumor biomarkers play an important role in the early diagnosis and therapy of cancer. Using luminescent nanomaterials as labels can significantly improve immunoassay performance, especially in terms of sens...
An evolving machine-learning-based algorithm to early predict response to anti-CGRP monoclonal antibodies in patients with migraine.
Cephalalgia : an international journal of headache
Dec 1, 2024
BACKGROUND: The present study aimed to determine whether machine-learning (ML)-based models can predict 3-, 6, and 12-month responses to the monoclonal antibodies (mAbs) against the calcitonin gene-related peptide (CGRP) or its receptor (anti-CGRPmAb...
Deep learning framework for peak detection at the intact level of therapeutic proteins.
Journal of separation science
Jun 1, 2024
While automated peak detection functionalities are available in commercially accessible software, achieving optimal true positive rates frequently necessitates visual inspection and manual adjustments. In the initial phase of this study, hetero-varia...
Explainable deep learning enhances robust and reliable real-time monitoring of a chromatographic protein A capture step.
Biotechnology journal
Jan 1, 2024
The application of model-based real-time monitoring in biopharmaceutical production is a major step toward quality-by-design and the fundament for model predictive control. Data-driven models have proven to be a viable option to model bioprocesses. I...
Prediction of HIV sensitivity to monoclonal antibodies using aminoacid sequences and deep learning.
Bioinformatics (Oxford, England)
Sep 15, 2022
MOTIVATION: Knowing the sensitivity of a viral strain versus a monoclonal antibody is of interest for HIV vaccine development and therapy. The HIV strains vary in their resistance to antibodies, and the accurate prediction of virus-antibody sensitivi...
In silico proof of principle of machine learning-based antibody design at unconstrained scale.
mAbs
Jan 1, 2022
Generative machine learning (ML) has been postulated to become a major driver in the computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to confirm this hypothesis have been hindered by the infeasibility of testing ...
Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies.
mAbs
Jan 1, 2022
Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs) are tremendous, the design and discovery of new candidates remain a time and cost-intensive endeavor. In this regard, progress in the generation of data describi...
Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics.
mAbs
Jan 1, 2022
Machine learning has been recently used to predict therapeutic antibody aggregation rates and viscosity at high concentrations (150 mg/ml). These works focused on commercially available antibodies, which may have been optimized for stability. In this...
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