| Abstract | Biotherapeutics have emerged as a major class of pharmaceuticals, encompassing monoclonal antibodies, recombinant human proteins and enzymes, fusion proteins, antibody drug conjugates, multi-specific formats, peptides, and vaccines. These modalities serve a wide range of therapeutic areas, including immune-oncology, inflammation, cardiovascular, metabolic, infectious, and rare diseases (DeFrancesco, 2019; Kang and Jung, 2020; Lu et al., 2020; Kaplon et al., 2023). Recent advancements in structure determination, structure prediction, bioanalytical characterization, and machine learning have established in silico approaches as a key toolbox employed in the biologic drug discovery and development pipelines (Fischman and Ofran, 2018; Norman et al., 2020; Fernandez-Quintero et al., 2023). Additionally, physics-based molecular modeling and simulation methods, along with empirical linear models, have matured to routine implementation during biotherapeutic drug candidate selection and optimization. However, the accuracy of these predictions can be improved. Further refinements will be welcomed, particularly towards binding affinity predictions and developability assessments. |
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