System and method for predictive candidate compound discovery

A computer-implemented method candidate compound discovery, comprising executing on a processor the steps of:

• receiving a type of standardized data from at least a database, wherein the standardized data is for compounds, metals, molecules, atoms, sub-atomic particles or any combination thereof, and wherein the standardized data types comprise numerical data sets, images, graphs, text, or any combination thereof;
• receiving a user query, wherein the user query comprises a request for a desired attribute for the candidate compound;
• processing each of the standardized data types with one or more trained machine learning models, wherein the one or more machine learning models are configured to recommend at least one of a plurality of the candidate molecules to be bonded with the candidate compound based on the user query;
• generating an interactive environment comprising graphical representation of the candidate molecule and candidate compound based on the user query;
• based on a received a signal from a user, altering a configuration of the candidate compound to allow the user, using virtual reality (VR), augmented reality (AR) or both, to interact with the candidate compound and the plurality of candidate molecules, wherein based on a received additional signal from the user, further alter the candidate compound with another of the plurality of molecules;
• and
• generating clinical characteristics of the candidate compound based on the further alteration by the user.

A non-transitory computer-readable medium having stored thereon program instructions that, upon execution by a computing device, cause the computing device to perform operations comprising:

• receive a type of standardized data from at least a database, wherein the standardized data is for compounds, metals, molecules, atoms, sub-atomic particles or any combination thereof, and wherein the standardized data types comprise numerical data sets, images, graphs, text, or any combination thereof;
• receive a user query, wherein the user query comprises a request for a desired attribute for the candidate compound;
• process each of the standardized data types with one or more trained machine learning models, wherein the one or more machine learning models are configured to recommend at least one of a plurality of the candidate molecules to be bonded with the candidate compound based on the user query;
• generate an interactive environment comprising graphical representation of the candidate molecule and candidate compound based on the user query;
• based on a received a signal from a user, alter a configuration of the candidate compound to allow the user, using virtual reality (VR), augmented reality (AR) or both, to interact with the candidate compound and the plurality of candidate molecules, wherein based on a received additional signal from the user, further alter the candidate compound with another of the plurality of molecules;
• and
• generate clinical characteristics of the candidate compound based on the further alteration by the user.