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 learning for biologics: opportunities for protein engineering, developability, and formulation
Successful biologics must satisfy multiple properties including activity and particular
physicochemical features that are globally defined as developability. These multiple …
physicochemical features that are globally defined as developability. These multiple …
Design of protein-binding proteins from the target structure alone
The design of proteins that bind to a specific site on the surface of a target protein using no
information other than the three-dimensional structure of the target remains a challenge …
information other than the three-dimensional structure of the target remains a challenge …
Therapeutics data commons: Machine learning datasets and tasks for drug discovery and development
Therapeutics machine learning is an emerging field with incredible opportunities for
innovatiaon and impact. However, advancement in this field requires formulation of …
innovatiaon and impact. However, advancement in this field requires formulation of …
Biophysical properties of the clinical-stage antibody landscape
T Jain, T Sun, S Durand, A Hall… - Proceedings of the …, 2017 - National Acad Sciences
Antibodies are a highly successful class of biological drugs, with over 50 such molecules
approved for therapeutic use and hundreds more currently in clinical development …
approved for therapeutic use and hundreds more currently in clinical development …
Language models generalize beyond natural proteins
Learning the design patterns of proteins from sequences across evolution may have
promise toward generative protein design. However it is unknown whether language …
promise toward generative protein design. However it is unknown whether language …
Five computational developability guidelines for therapeutic antibody profiling
MIJ Raybould, C Marks, K Krawczyk… - Proceedings of the …, 2019 - National Acad Sciences
Therapeutic mAbs must not only bind to their target but must also be free from
“developability issues” such as poor stability or high levels of aggregation. While small …
“developability issues” such as poor stability or high levels of aggregation. While small …
Protein aggregation–mechanisms, detection, and control
W Wang, CJ Roberts - International journal of pharmaceutics, 2018 - Elsevier
Protein aggregation has been recognized as one of the major challenges in the
development and commercialization of successful protein-based drug products because of …
development and commercialization of successful protein-based drug products because of …
Computational approaches to therapeutic antibody design: established methods and emerging trends
Antibodies are proteins that recognize the molecular surfaces of potentially noxious
molecules to mount an adaptive immune response or, in the case of autoimmune diseases …
molecules to mount an adaptive immune response or, in the case of autoimmune diseases …
Predicting antibody developability profiles through early stage discovery screening
M Bailly, C Mieczkowski, V Juan, E Metwally… - MAbs, 2020 - Taylor & Francis
Monoclonal antibodies play an increasingly important role for the development of new drugs
across multiple therapy areas. The term 'developability'encompasses the feasibility of …
across multiple therapy areas. The term 'developability'encompasses the feasibility of …