Machine learning driven acceleration of biopharmaceutical formulation development using Excipient Prediction Software (ExPreSo).

ABSTRACT: Formulation development of protein biopharmaceuticals has become increasingly challenging due to new modalities and higher target drug substance concentrations. The limited amount of drug substance available during development, coupled with extensive analytical requirements, restrict the number of excipients that can be empirically screened. There is a strong need for in silico tools to optimize excipient pre-selection before wet lab experiments. Here, we introduce Excipient Prediction Software (ExPreSo), a supervised machine learning algorithm that suggests excipients based on the properties of the protein drug substance and target product profile. ExPreSo was trained on a dataset comprising 335 regulatory-approved peptide and protein drug products. Predictive features included pro

SUBMITTER: Vidal-Henriquez E 

PROVIDER: S-EPMC12597001 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature