Systems and methods for prediction of protein formulation properties

A computing system comprising:

• one or more processors;
• and
• one or more memories storing instructions that, when executed by the one or more processors, cause the computing system to
• classify 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,
• select, 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,
• predict 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
• cause the value of the protein formulation property to be one or both of (i) displayed to a user, and (ii) stored in a memory.

A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing system, cause the computing system to:

• classify 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;
• select, 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;
• predict 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
• cause the value of the protein formulation property to be one or both of (i) displayed to a user, and (ii) stored in a memory.