Abstract: In a method for predicting a property of potential protein formulations, a set of formulation descriptors is classified as belonging to a specific one of a plurality of predetermined groups that each correspond to a different value range for a protein formulation property. Classifying the set of descriptors includes applying at least a first portion of the set of descriptors as inputs to a first machine learning model. The method also includes selecting, based on the classification, a second machine learning model from among multiple models corresponding to different groups. The method also includes predicting a value of the protein formulation property that corresponds to the set of descriptors, by applying at least a second portion of the set of formulation descriptors as inputs to the selected model. The method further includes causing the value of the protein formulation property to be displayed to a user and/or stored in a memory.

Abstract: A biologics manufacturing process that connects the drug substance and drug product processes into an integrated, continuous process.

Abstract: The field of the invention relates generally to filling containers with liquid. More specifically, the invention relates to the real-time assessment of the volume filled into containers, particularly in the manufacture of medicaments such as pharmaceuticals. The invention finds specific use in the final stage of drug manufacturing known as fill/finish wherein the drug substance or active pharmaceutical intermediate is prepared as a final drug product in a formulation suitable for administration to patients in need of the same, which is then provided to patients. More particularly, the invention relates to controlling the volume in container via in-line non-destructive monitoring of the fill process.