Results 1 to 10 of about 16,267,247 (278)

A high-throughput platform for biophysical antibody developability assessment to enable AI/ML model training. [PDF]

open access: yesMAbs
Antibodies must bind their targets with high affinity and specificity to achieve useful therapeutic activity. They must also possess suitable developability properties (e.g.
Arsiwala A   +27 more
europepmc   +3 more sources

Assessing developability early in the discovery process for novel biologics

open access: yesMAbs, 2023
Beyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures.
Guy Georges   +2 more
exaly   +4 more sources

Blueprint for antibody biologics developability

open access: yesMAbs, 2023
Large-molecule antibody biologics have revolutionized medicine owing to their superior target specificity, pharmacokinetic and pharmacodynamic properties, safety and toxicity profiles, and amenability to versatile engineering. In this review, we focus on
Yanling Wang, Xuejin Zhang
exaly   +4 more sources

Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics

open access: yesMAbs, 2022
Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly ...
Kouhei Tsumoto   +2 more
exaly   +3 more sources

Developability considerations for bispecific and multispecific antibodies

open access: yesMAbs
Bispecific antibodies (bsAb) and multispecific antibodies (msAb) encompass a diverse variety of formats that can concurrently bind multiple epitopes, unlocking mechanisms to address previously difficult-to-treat or incurable diseases. Early assessment of
Alaa Amash   +9 more
exaly   +4 more sources

Application of protein language models for antibody developability prediction. [PDF]

open access: yesMAbs
Protein language models (PLMs) provide a powerful framework for learning sequence – property relationships in antibodies. However, their performance and reliability in real-world industrial antibody discovery pipelines remain underexplored.
Amini S   +5 more
europepmc   +3 more sources

Characterising nanobody developability to improve therapeutic design using the Therapeutic Nanobody Profiler. [PDF]

open access: yesCommun Biol
Developability optimisation is an important step for successful biotherapeutic design. For monoclonal antibodies, developability is relatively well characterised. However, progress for novel biotherapeutics such as nanobodies is more limited. Differences
Gordon GL   +3 more
europepmc   +3 more sources

PROPERMAB: an integrative framework for <i>in silico</i> prediction of antibody developability using machine learning. [PDF]

open access: yesMAbs
Selection of lead therapeutic molecules is often driven predominantly by pharmacological efficacy and safety. Candidate developability, such as biophysical properties that affect the formulation of the molecule into a product, is usually evaluated only ...
Li B   +9 more
europepmc   +3 more sources

Computational design of therapeutic antibodies with improved developability: efficient traversal of binder landscapes and rescue of escape mutations. [PDF]

open access: yesMAbs
Developing therapeutic antibodies is a challenging endeavor, often requiring large-scale screening to produce initial binders, that still often require optimization for developability.
Dreyer FA   +19 more
europepmc   +3 more sources

Separating clinical antibodies from repertoire antibodies, a path to in silico developability assessment

open access: yesMAbs, 2022
Approaches for antibody discovery have seen substantial improvement and success in recent years. Yet, advancing antibodies into the clinic remains difficult because therapeutic developability concerns are challenging to predict.
Christopher Negrón
exaly   +4 more sources

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