IP Library Patent Application 18298371
Patent Application
App. No. 18/298,371

DATA BASED CANCER RESEARCH AND TREATMENT SYSTEMS AND METHODS

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Quick Facts
Patent No.
US None
App. No.
18/298,371
Filed
Apr 11, 2023
Art Unit
1686
USPC
702/19
Abstract

A method for data intake and consumption includes the steps of: storing a plurality of micro-service programs, operational user application programs, and analytical user application programs in at least one computer system, storing system data received from a plurality of different sources in a database, the system data includes clinical records data in original forms, the clinical records data including cancer state information, treatment types, and treatment efficacy information, consuming, by each of the micro-service programs, defined subsets of the system data to generate a new data product, storing the new data product in a second database, and consuming the new data product by others of the micro-service programs or the operational or analytical user application programs.

Claims (56)

1 . A method for data intake and consumption, the method comprising the steps of:

storing a plurality of micro-service programs, operational user application programs, and analytical user application programs in at least one computer system;

storing system data received from a plurality of different sources in a database, the system data includes clinical records data in original forms, the clinical records data including cancer state information, treatment types, and treatment efficacy information;

consuming, by each of the micro-service programs, defined subsets of the system data to generate a new data product;

storing the new data product in a second database; and

consuming the new data product by others of the micro-service programs or the operational or analytical user application programs.

2 . The method of claim 1 , wherein the subsets of the system data are defined according to a data consume definition associated with each respective micro-service program.

3 . The method of claim 1 , where at least one of the defined subsets of the system data;

comprises data to which optical character recognition and natural language processing techniques have already been applied;

is defined according to metadata associated with the data; or

is defined according to a data type of the data.

4 . (canceled)

5 . (canceled)

6 . The method of claim 1 , wherein the new data product comprises a data model optimized for a particular user application.

7 . The method of claim 1 , further comprising:

shaping the system data and storing the shaped data in a third database, wherein the defined subsets of the system data comprise shaped data retrieved from the third database.

8 . The method of claim 7 , wherein shaping the system data comprises applying at least one of optical character recognition or natural language processing techniques to the system data.

9 . The method of claim 7 , wherein shaping the system data comprises applying an extract, transform, and load process to the system data.

10 . The method of claim 7 , wherein shaping the system data comprises identifying metadata associated with the system data and storing the identified metadata in the third database.

11 . The method of claim 10 , wherein the identified metadata is stored in a separate catalog within the third database.

12 . The method of claim 7 , wherein the shaped system data is optimized for searching; and

wherein the data being optimized for searching comprises the shaped system data being stored in a first data structure, the first data structure different than a second, different data structure in which the shaped system data can be stored, the second data structure being configured to support one or more of the user application programs; or

wherein the system data is stored in a plurality of different formats, and wherein the shaped system data being optimized for searching comprises normalizing the system data into a common format.

13 . (canceled)

14 . (canceled)

15 . (canceled)

16 . (canceled)

17 . The method of claim 1 , further comprising:

generating an alert indicating that the new data product is ready for consumption.

18 . The method of claim 17 , wherein the alert is generated by the micro-service program that generated the respective new data product.

19 . The method of claim 17 further including each micro-service program monitoring the alert and determining if new data is to be consumed by that micro-service program independent of all other micro-service programs.

20 . The method of claim 17 , further comprising:

monitoring, by a micro-service program, for the alert, the micro-service program including a data-consumption definition;

determining whether the new data corresponding to the alert satisfies the data-consumption definition; and

consuming, by the micro-service program, the new data when the alert satisfies the data-consumption definition.

21 . The method of claim 20 wherein at least a subset of the micro-service programs specify the same data-consumption definition.

22 . (canceled)

23 . (canceled)

24 . (canceled)

25 . (canceled)

26 . The method of claim 1 , wherein the system data includes genomic sequencing data for a patient's cancerous cells and normal cells, the genomic sequencing data generated by a next generation genomic sequencer.

27 . The method of claim 1 wherein each cancer state includes a plurality of factors, the method further including the steps of using a processor to automatically perform the steps of analyzing patient genomic sequencing data that is associated with patients having at least a common subset of cancer state factors to identify treatments of genomically similar patients that experience treatment efficacies relative to a threshold level.

28 . The method of claim 1 wherein each cancer state includes a plurality of factors, the method further including the steps of using a processor to automatically identify, for specific cancer types, highly efficacious cancer treatments and, for each highly efficacious cancer treatment, identify at least one genomic sequencing data subset that is different for patients that experienced treatment efficacy above a first threshold level when compared to patients that experienced treatment efficacy below a second threshold level.

29 . A system for data intake and consumption, the system comprising:

at least one computer system including a plurality of stored micro-service programs, operational user application programs, and analytical user application programs in a computer system;

a database storing system data received from a plurality of different sources, the system data includes clinical records data in original forms, the clinical records data including cancer state information, treatment types, and treatment efficacy information; and

a second database,

wherein each of the micro-service programs is configured to consume defined subsets of the system data to generate a new data product,

wherein the new data product is stored in a second database; and

wherein others of the micro-service programs or the operational or analytical user application programs are configured to consume the new data product.

30 . A non-transitory computer-readable storage medium having stored thereon program code instructions that, when executed by a processor, cause the processor to:

store a plurality of micro-service programs, operational user application programs, and analytical user application programs in at least one computer system;

store system data received from a plurality of different sources in a database, the system data includes clinical records data in original forms, the clinical records data including cancer state information, treatment types, and treatment efficacy information;

consume, by each of the micro-service programs, defined subsets of the system data to generate a new data product;

store the new data product in a second database; and

consume the new data product by others of the micro-service programs or the operational or analytical user application programs.

Assignments (5)
RELEASE OF SECURITY INTEREST Recorded May 14, 2026
From: ARES CAPITAL CORPORATION, AS COLLATERAL AGENT
To: TEMPUS AI, INC. (F/K/A TEMPUS LABS, INC.)
Reel/Frame 074653/0745 →
CHANGE OF NAME Recorded Feb 6, 2024
From: TEMPUS LABS, INC.
To: TEMPUS AI, INC.
Reel/Frame 066507/0862 →
SECURITY INTEREST Recorded May 25, 2023
From: TEMPUS LABS, INC.
To: ARES CAPITAL CORPORATION, AS COLLATERAL AGENT
Reel/Frame 063764/0174 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 14, 2023
From: COLLEY, SHANE; SIMPSON, ISAIAH; REUTER, BRIAN; TELL, ROBERT; LEFKOFSKY, HAILEY; LANE, HUNTER; WHITE, KEVIN; BEAUBIER, NIKE; BUSH, STEPHEN; KHAN, ALY; LAU, DENISE; SHAH, KAANAN
To: TEMPUS LABS, INC.
Reel/Frame 063327/0137 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 14, 2023
From: LEFKOFSKY, ERIC
To: TEMPUS LABS, INC.
Reel/Frame 063327/0281 →