G16C20/80

MECHANISMS AUTHORING TOOL AND DATA COLLECTION SYSTEM
20220157193 · 2022-05-19 ·

A method for authoring and using a chemical mechanism includes a step of authoring a chemical mechanism problem to be solved by a user with an authoring tool. The chemical mechanism problem presents a user with chemical renderings of starting chemical compounds to be rearranged in a predetermined series of steps to form a predetermined final chemical compound. The authoring tool being implemented by an authoring computer device having a processor and a display. The chemical renderings of the starting chemical compounds are intended to be displayed on a user computer device. Therefore, the steps of the chemical problem created by the author recorded to a suitable storage medium. A series of inputs from the user are received on a user tool on the user computer device for moving atoms and or bonds in the chemical rendering of the starting chemical compounds to reproduce a chemical mechanism.

SYSTEMS AND METHODS FOR GENERATING PHASE DIAGRAMS FOR METASTABLE MATERIAL STATES

A system can include one or more processors configured to access at least one parameter of a material, generate a plurality of structures of the material using the at least one parameter, determine a state of each structure of the plurality of structures using the at least one parameter, determine a difference between the state of each structure of the plurality of structures and a ground state value, evaluate a convergence condition responsive to determining the difference between the state of each structure of the plurality of structures and the ground state value, and output at least one structure of the plurality of structures responsive to the convergence condition being satisfied.

SYSTEMS AND METHODS FOR GENERATING PHASE DIAGRAMS FOR METASTABLE MATERIAL STATES

A system can include one or more processors configured to access at least one parameter of a material, generate a plurality of structures of the material using the at least one parameter, determine a state of each structure of the plurality of structures using the at least one parameter, determine a difference between the state of each structure of the plurality of structures and a ground state value, evaluate a convergence condition responsive to determining the difference between the state of each structure of the plurality of structures and the ground state value, and output at least one structure of the plurality of structures responsive to the convergence condition being satisfied.

END OF LIFE DETECTION FOR ANALYTE SENSORS

Systems and methods for processing sensor data and end of life detection are provided. In some embodiments, a method for determining the end of life of a continuous analyte sensor includes evaluating a plurality of risk factors using an end of life function to determine an end of life status of the sensor and providing an output related to the end of life status of the sensor. The plurality of risk factors may be selected from the list including the number of days the sensor has been in use, whether there has been a decrease in signal sensitivity, whether there is a predetermined noise pattern, whether there is a predetermined oxygen concentration pattern, and error between reference BG values and EGV sensor values.

END OF LIFE DETECTION FOR ANALYTE SENSORS

Systems and methods for processing sensor data and end of life detection are provided. In some embodiments, a method for determining the end of life of a continuous analyte sensor includes evaluating a plurality of risk factors using an end of life function to determine an end of life status of the sensor and providing an output related to the end of life status of the sensor. The plurality of risk factors may be selected from the list including the number of days the sensor has been in use, whether there has been a decrease in signal sensitivity, whether there is a predetermined noise pattern, whether there is a predetermined oxygen concentration pattern, and error between reference BG values and EGV sensor values.

DRUG VIRTUAL SCREENING SYSTEM FOR CRYSTAL COMPLEXES, AND METHOD OF USING THE SAME

The present invention provides a drug virtual screening system for crystal complexes, and method of using the same, comprising a visualization subsystem, an evaluation tool box subsystem, an AI model management subsystem, a large-scale sampling subsystem, a virtual screening subsystem, and a data log storage subsystem. Starting with the known crystal complexes, a batch of candidate compounds that meet the requirements are recommended after going through the visualization subsystem, evaluation tool box subsystem, AI model management subsystem, large-scale sampling subsystem, and virtual screening system in turn. Based on this system, the generation of the compound library is organically combined with the subsequent virtual screening. Users only need to describe the action mode of the drug on the protein and the requirements for the drug to generate a batch of compounds that meet the expectations. The automated system reduces user intervention and improves the efficiency of research and development.

Systems and Methods for Predicting the Olfactory Properties of Molecules Using Machine Learning

The present disclosure provides systems and methods for predicting olfactory properties of a molecule. One example method includes obtaining a machine-learned graph neural network trained to predict olfactory properties of molecules based at least in part on chemical structure data associated with the molecules. The method includes obtaining a graph that graphically describes a chemical structure of a selected molecule. The method includes providing the graph as input to the machine-learned graph neural network. The method includes receiving prediction data descriptive of one or more predicted olfactory properties of the selected molecule as an output of the machine-learned graph neural network. The method includes providing the prediction data descriptive of the one or more predicted olfactory properties of the selected molecule as an output.

Systems and Methods for Predicting the Olfactory Properties of Molecules Using Machine Learning

The present disclosure provides systems and methods for predicting olfactory properties of a molecule. One example method includes obtaining a machine-learned graph neural network trained to predict olfactory properties of molecules based at least in part on chemical structure data associated with the molecules. The method includes obtaining a graph that graphically describes a chemical structure of a selected molecule. The method includes providing the graph as input to the machine-learned graph neural network. The method includes receiving prediction data descriptive of one or more predicted olfactory properties of the selected molecule as an output of the machine-learned graph neural network. The method includes providing the prediction data descriptive of the one or more predicted olfactory properties of the selected molecule as an output.

SYSTEM AND METHOD FOR EVALUATING CHEMICAL COMPOUND DATA USING AND APPLYING A VIRTUAL LANDSCAPE
20220027374 · 2022-01-27 ·

The present invention is directed to generating an n-dimensional map using the results of a query for compounds enumerated within a collection of documents describing a particular biological target of interest and a curated set of compounds not enumerated in the collection of documents. Both sets of compounds (document coded and curated coded) are converted into coded forms and placed in the n-dimensional map. One or more processors are configured to evaluate the distance between the curated coded forms and the closest cluster of document coded forms. Based on the distance between a coded form and the document coded forms, the curated coded forms can be ranked regarding the likelihood of interacting with the particular biological target.

SYNTHESIS ROUTE RECOMMENDATION ENGINE FOR INORGANIC MATERIALS
20210350880 · 2021-11-11 ·

A computer system and computational method for determining optimal solid-state methods for synthesis of an inorganic material that results in an output of recommended synthetic methods that can be implemented based on the recommendation. The method involves inputting a target inorganic material, querying structural data and thermodynamic data for the target inorganic material and reactant inorganic materials that can be used for its synthesis, enumerating possible synthetic reactions to construct a synthesis reaction database with a viable subset of the possible synthetic methods. The program generates a nucleation barrier metric and a competition metric that are combined to provide a recommendation of the synthetic procedures to the target inorganic material.