Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies
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 …
are tremendous, the design and discovery of new candidates remain a time and cost …
Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery
W Wilman, S Wróbel, W Bielska… - Briefings in …, 2022 - academic.oup.com
Antibodies are versatile molecular binders with an established and growing role as
therapeutics. Computational approaches to developing and designing these molecules are …
therapeutics. Computational approaches to developing and designing these molecules are …
In silico proof of principle of machine learning-based antibody design at unconstrained scale
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 …
computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to …
Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics
Therapeutic monoclonal antibodies and their derivatives are key components of clinical
pipelines in the global biopharmaceutical industry. The availability of large datasets of …
pipelines in the global biopharmaceutical industry. The availability of large datasets of …
Unconstrained generation of synthetic antibody–antigen structures to guide machine learning methodology for antibody specificity prediction
Abstract Machine learning (ML) is a key technology for accurate prediction of antibody–
antigen binding. Two orthogonal problems hinder the application of ML to antibody …
antigen binding. Two orthogonal problems hinder the application of ML to antibody …
Phenotypic determinism and stochasticity in antibody repertoires of clonally expanded plasma cells
D Neumeier, A Yermanos, A Agrafiotis… - Proceedings of the …, 2022 - National Acad Sciences
The capacity of humoral B cell-mediated immunity to effectively respond to and protect
against pathogenic infections is largely driven by the presence of a diverse repertoire of …
against pathogenic infections is largely driven by the presence of a diverse repertoire of …
[HTML][HTML] SARS-CoV-2 reactive and neutralizing antibodies discovered by single-cell sequencing of plasma cells and mammalian display
Characterization of COVID-19 antibodies has largely focused on memory B cells; however, it
is the antibody-secreting plasma cells that are directly responsible for the production of …
is the antibody-secreting plasma cells that are directly responsible for the production of …
Reference-based comparison of adaptive immune receptor repertoires
B and T cell receptor (immune) repertoires can represent an individual's immune history.
While current repertoire analysis methods aim to discriminate between health and disease …
While current repertoire analysis methods aim to discriminate between health and disease …
Disease diagnostics using machine learning of immune receptors
Clinical diagnoses rely on a wide variety of laboratory tests and imaging studies, interpreted
alongside physical examination findings and the patient's history and symptoms. Currently …
alongside physical examination findings and the patient's history and symptoms. Currently …
Deep Learning in Therapeutic Antibody Development
JM Shaver, J Smith, T Amimeur - Artificial Intelligence in Drug Design, 2022 - Springer
Deep learning applied to antibody development is in its adolescence. Low data volumes
and biological platform differences make it challenging to develop supervised models that …
and biological platform differences make it challenging to develop supervised models that …