Methods and systems for predicting stability

A computer system for determining stability of one or more target pharmaceutical materials, comprising:

• a memory storing instructions;
• and
• one or more processors configured to execute the instructions to perform operations including:
• (a) obtaining training characteristic data associated with one or more training pharmaceutical materials at one or more training timepoints, wherein the one or more training timepoints comprise at least a first predetermined timepoint;
• (b) obtaining target characteristic data associated with the one or more target pharmaceutical materials at one or more target timepoints, wherein the one or more target timepoints are earlier than the first predetermined timepoint;
• (c) generating one or more clusters of the one or more training pharmaceutical materials and the one or more target pharmaceutical materials based on the training characteristic data and the target characteristic data;
• (d) selecting a subset of the one or more training pharmaceutical materials based on the one or more clusters;
• (e) training a first computational model using the training characteristic data associated with the subset of the one or more training pharmaceutical materials at the one or more training timepoints;
• and
• (f) determining the stability of the one or more target pharmaceutical materials at the first predetermined timepoint based on the target characteristic data associated with the one or more target pharmaceutical materials using the trained first computational model.

A non-transitory computer-readable medium containing instructions for determining stability of one or more target pharmaceutical materials that, when executed by a processor, cause the processor to perform a method comprising:

• (a) obtaining training characteristic data associated with one or more training pharmaceutical materials at one or more training timepoints, wherein the one or more training timepoints comprise at least a first predetermined timepoint;
• (b) obtaining target characteristic data associated with the one or more target pharmaceutical materials at one or more target timepoints, wherein the one or more target timepoints are earlier than the first predetermined timepoint;
• (c) generating one or more clusters of the one or more training pharmaceutical materials and the one or more target pharmaceutical materials based on the training characteristic data and the target characteristic data;
• (d) selecting a subset of the one or more training pharmaceutical materials based on the one or more clusters;
• (e) training a first computational model using the training characteristic data associated with the subset of the one or more training pharmaceutical materials at the one or more training timepoints;
• and
• (f) determining the stability of the one or more target pharmaceutical materials at the first predetermined timepoint based on the target characteristic data associated with the one or more target pharmaceutical materials using the trained first computational model.