| CPC G16C 20/30 (2019.02) [G16C 20/50 (2019.02); G16C 20/70 (2019.02)] | 21 Claims |
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1. A method of predicting a property of potential protein formulations, the method comprising:
classifying, by one or more processors of a computing system, a set of formulation descriptors as belonging to a specific group of a plurality of predetermined groups that each correspond to a different value range for a protein formulation property, wherein classifying the set of formulation descriptors includes applying at least a first portion of the set of formulation descriptors as inputs to a first machine learning model;
selecting, by the one or more processors and based on the specific group, a second machine learning model from among a plurality of machine learning models that each correspond to a different one of the plurality of predetermined groups;
predicting, by the one or more processors, a value of the protein formulation property by applying at least a second portion of the set of formulation descriptors as inputs to the second machine learning model; and
causing, by the one or more processors, the value of the protein formulation property to be one or both of (i) displayed to a user, and (ii) stored in a memory.
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