Healthcare analysis stream management

• US 10,055,546 B2
• Filed: 06/13/2016
• Issued: 08/21/2018
• Est. Priority Date: 07/06/2012
• Status: Active Grant

• Current Assignee: Nant Holdings IP, LLC (NantWorks, LLC)
• Original Assignee: Nant Holdings IP, LLC (NantWorks, LLC)
• Inventors: Soon-Shiong, Patrick
• Primary Examiner(s): Negin, Russell S
• Application Number:
  US15/181,301
• Publication Number:
  US 20160306920A1
• Time in Patent Office: 799 Days
• Field of Search: None
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 20/40 Population genetics; Linkage disequilibrium
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 30/10 Sequence alignment; Homology search
• CPC Class Codes: G16B 30/20 Sequence assembly
• CPC Class Codes: G16B 50/00 ICT programming tools or database systems specially adapted for bioinformatics
• CPC Class Codes: G16B 50/10 Ontologies; Annotations
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/00 ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
• CPC Class Codes: G16H 70/00 ICT specially adapted for the handling or processing of medical references
• CPC Class Codes: H04L 67/01 Protocols
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/306 User profiles

Abstract

Apparatus, systems and methods for pre-processing, analyzing, and storing genomic data through a scalable, distributed analysis system across a network is presented.

Claims

1. A genomic data analysis network comprising:

a sequence data interface configurable to acquire pre-processed differential genomic sequence data including annotations, the annotations comprising alignment data between sequence data and a pre-existing genome database, wherein the pre-processed differential genomic sequence data is associated with a patient and represents a difference between the patient'"'"'s genome and a reference genome; and

a plurality of genomic analysis computing nodes coupled with the sequence data interface and that are interconnected via a computer network, wherein at least one of the plurality of genomic analysis computing nodes operates as a manager node that is configurable to;

arrange at least some of the analysis computing nodes into a patient-specific analysis computing topology where each node of the at least some of the plurality of genomic analysis computing nodes analyzes different portions of the pre-processed differential genomic sequence data; and

route the pre-processed differential genomic sequence data from the sequence data interface and among nodes of the patient-specific analysis computing topology as a function of the annotations.

2. The network of claim 1, wherein each of the nodes of the patient-specific analysis computing topology is configured to execute a different analysis regime on the pre-processed differential genomic sequence data.

3. The network of claim 2, wherein the analysis regimen includes at least one of the following:

DNA sequence analysis, RNA sequence analysis, gene expression profiling, genome comparison analysis, pattern searching, alignment analysis, DNA motif analysis, DNA promoter analysis, DNA copy number variation analysis, DNA methylation, microRNA analysis, mRNA expression profiling, splice variant analysis, protein sequence analysis, mutation rate analysis, evolutionary distance analysis, and phylogenic tree assembly.

4. The network of claim 1, wherein the patient-specific analysis computing topology is configured to correlate the pre-processed differential genomic sequence data with clinical protocols.

5. The network of claim 4, wherein the clinical protocols represent different cancer types.

6. The network of claim 1, wherein the patient-specific analysis computing topology comprises a genomic storage facility.

7. The network of claim 6, wherein nodes of the patient-specific analysis topology are configured to store respective portions of the pre-processed differential genomic sequence data.

8. The network of claim 7, wherein nodes of the patient-specific analysis computing topology are further configured to index respective portions of the pre-processed differential genomic sequence data as a function of at least one of the following identifiers:

a patient identifier, a population identifier, a demographic identifier, a disease identifier, a diagnosis identifier, a gender identifier, an age identifier, a location identifier, an occupation identifier, a risk factor identifier, a sequence identifier, a gene identifier, a pathway identifier, an allele identifier, and a prognosis identifier.

9. The network of claim 1, wherein nodes of the patient-specific analysis computing topology comprise at least one of the following computing devices:

a GPU modeling engine, a server, high performance computer, and a network switch.

10. The network of claim 1, wherein nodes of the patient-specific analysis computing topology are each configured to a dedicated specific genomic analysis task.

11. The network of claim 10, wherein the dedicated specific genomic analysis task is selected from the group consisting of:

routing, processing, sequencing, data-cleansing, and mapping.

12. The network of claim 1, wherein the patient-specific analysis computing topology comprises a patient-specific data processing route among the nodes of the patient-specific analysis computing topology.

13. The network of claim 12, wherein the manager node is further configurable to establish the patient-specific data processing route among the nodes of the patient-specific analysis computing topology as a function of at least one of the following analysis parameters:

an expected diagnosis, a prognosis, an urgency, a sequence annotation, a traffic load, an analysis load, a computational bandwidth, a memory constraint, an alert status, a status of an analysis, a user-defined input, a type of genomic analysis, a number of analysis iterations, and a confidence level.

14. The network of claim 1, wherein the pre-processed differential genomic sequence data comprises an annotated genomic data stream object.

15. The network of claim 1, wherein the pre-processed differential genomic sequence data comprises patient-specific proteomic data.

16. The network of claim 1, wherein the pre-processed differential genomic sequence data comprises patient-specific mutation data.

17. The network of claim 1, wherein the difference between the patient'"'"'s genome and the reference genome is between the patient'"'"'s normal genome and a patient'"'"'s tumor genome.

18. The network of claim 1, wherein the difference is between the patient'"'"'s genome and the reference genome is based on one of the following factors:

a sample time, a tissue, a person, a gender, a family, a community, a demographic, a normalized sequence, a disease, a diet, an environment, and an age.

19. The network of claim 1, wherein the pre-processed differential genomic sequence data is acquired based on at least one of the following formats:

BAMBAM, BAM, BED, SAM, WIG, Axt, MAF, and microarray.

20. The network of claim 1, wherein the annotations includes at least one of the following:

patient data, sequence data, processing parameter data, node ownership data, data ownership data, raw input data, pre-analyzed data, patient-specific data, disease data, diagnosis data, putative sequence locations, and an urgency.

21. A genomic data analysis network comprising:

a sequence data interface configurable to acquire pre-processed differential genomic sequence data including annotations, wherein the pre-processed differential genomic sequence data is associated with a patient and represents a difference between the patient'"'"'s genome and a reference genome; and

a plurality of genomic analysis computing nodes coupled with the sequence data interface and that are interconnected via a computer network, wherein at least one of the plurality of genomic analysis computing nodes operates as a manager node that is configurable to;

arrange at least some of the analysis computing nodes into a patient-specific analysis computing topology where each node of the at least some of the plurality of genomic analysis computing nodes analyzes different portions of the pre-processed differential genomic sequence data, the different portions of the pre-processed differential genomic sequence data comprising different portions of a single patient'"'"'s differential genomic sequence data; and

route the pre-processed differential genomic sequence data from the sequence data interface and among nodes of the patient-specific analysis computing topology as a function of the annotations.

22. A genomic data analysis network comprising:

a sequence data interface configurable to acquire pre-processed differential genomic sequence data including annotations, the annotations comprising alignment data between the sequence data and a pre-existing genome database, wherein the pre-processed differential genomic sequence data is associated with a patient and represents a difference between the patient'"'"'s genome and a reference genome; and

a plurality of genomic analysis computing nodes coupled with the sequence data interface and that are interconnected via a computer network, wherein at least one of the plurality of genomic analysis computing nodes operates as a manager node that is configurable to;

arrange at least some of the analysis computing nodes into a patient-specific analysis computing topology where each node of the at least some of the plurality of genomic analysis computing nodes analyzes different portions of the pre-processed differential genomic sequence data, the different portions of the pre-processed differential genomic sequence data comprising different portions of a single patient'"'"'s differential genomic sequence data; and

route the pre-processed differential genomic sequence data from the sequence data interface and among nodes of the patient-specific analysis computing topology as a function of the annotations.

23. A genomic data analysis network comprising:

a sequence data interface configurable to acquire pre-processed differential genomic sequence data including annotations, the annotations comprising alignment data between the sequence data and a pre-existing genome database, wherein the pre-processed differential genomic sequence data is associated with a patient and represents a difference between the patient'"'"'s genome and a reference genome; and

a plurality of genomic analysis computing nodes coupled with the sequence data interface and that are interconnected via a computer network, wherein at least one of the plurality of genomic analysis computing nodes operates as a manager node that is configurable to;

arrange at least some of the analysis computing nodes into a patient-specific analysis computing network topology where each node of the at least some of the plurality of genomic analysis computing nodes analyzes different portions of the pre-processed differential genomic sequence data; and

route the pre-processed differential genomic sequence data from the sequence data interface and among nodes of the patient-specific analysis computing network topology as a function of the annotations.