Drug discovery methods

• US 8,793,073 B2
• Filed: 08/01/2003
• Issued: 07/29/2014
• Est. Priority Date: 02/04/2002
• Status: Active Grant

• Current Assignee: Qiagen Redwood City, Inc. (Qiagen NV)
• Original Assignee: Ingenuity Systems, Inc. (Qiagen NV)
• Inventors: Chen, Richard O., Cho, Raymond J., Felciano, Ramon M., Holley, Brett, Patel, Viresh, Richards, Daniel R., Selvarajan, Sushma, Steward, Keith, Schneider, Sara Tanenbaum
• Primary Examiner(s): Clow, Lori A
• Application Number:
  US10/632,099
• Publication Number:
  US 20070178473A1
• Time in Patent Office: 4,015 Days
• US Class Current: 702/19
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 25/10 Gene or protein expression profiling; Expression-ratio estimation or normalisation
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 35/00 ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides
• CPC Class Codes: G16B 35/20 Screening of libraries
• CPC Class Codes: G16B 5/00 ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
• CPC Class Codes: G16B 5/30 Dynamic-time models
• CPC Class Codes: G16C 20/60 In silico combinatorial chemistry
• CPC Class Codes: G16C 20/64 Screening of libraries

Abstract

Methods for identifying disease-related pathways that can be used to identify drug discovery targets, to identify new uses for known drugs, to identify markers for drug response, and related purposes.

Claims

1. A computer system for identifying one or more drug discovery targets, the system comprising:

a knowledge representation system comprising an ontology, and a knowledge base of scientific findings;

wherein;

(a) the knowledge base comprises genomics information, and findings derived from natural language, wherein the genomics information comprises information relating to genes, their DNA sequences, their mRNA, proteins expressed from said genes and the biological effects of the expressed proteins;

(b) the ontology is organized so that;

(i) each gene, mRNA, protein expressed from said gene, and biological effect is given an identifier which is related to synonyms for the identifier;

(ii) each gene, mRNA, protein expressed from said gene, and biological effect is categorized by class; and

(iii) the relationship of each gene, mRNA, protein expressed from said gene and disease state is defined by slots and facets; and

(c) the computer system is configured to;

(i) receive a profile definition criterion from a user identifying a subset of biological objects and processes that act on biological systems in a disease-related pathway;

(ii) generate a profile using the knowledge base, wherein the profile comprises a subset of genomics information contained in the knowledge base comprising information relating to genes, their DNA sequences, their mRNA, proteins expressed from said genes and the biological effects of the expressed proteins;

(iii) perform computational analysis of biological relationships among the subset of genomics information in the profile based upon the profile definition criterion; and

(iv) identify additional biological objects and processes that act on those objects associated with the disease-related pathway using the analysis of biological relationship;

whereby each identified object or process is a drug discovery target,

wherein the computer system is a stand alone computer, a multicomponent computer, or a networked computer, and wherein the computer system farther comprises hardware for electronically searching the knowledge base.

2. The computer system of claim 1 wherein said genomics information comprises data extracted from multiple public sources.

3. The computer system of claim 1 wherein said genomics information comprises proprietary data.

4. The computer system of claim 1 wherein said genomics information comprises data extracted from a combination of proprietary and public data sources.

5. The computer system of claim 1 wherein drug discovery targets in the disease-related pathway are prioritized based on factors that include function and complexity.

6. The computer system of claim 1 wherein drug discovery targets are prioritized based on markers for side effects and patient responsiveness.

7. The computer system of claim 1 wherein the genomics information comprises information relating to genotype and the disease-related pathway comprises a gene, mRNA or protein expressed from said gene associated with a particular genotype.

8. The computer system of claim 1, wherein the genomics information comprises a name of each gene, mRNA or protein expressed from said gene, and their biological effects, and the computer identifies relationships between genes and/or proteins expressed from said genes that are at least two steps removed from each other in a disease-related pathway.

9. The computer system of claim 1, further comprising a second knowledge base of scientific findings.

10. The computer system of claim 9, wherein the knowledge base is a frame-based knowledge base.

11. The computer system of claim 1, wherein the system is further configured to compare disease-related pathways with data obtained from gene expression studies or a manually entered gene list.

12. The computer system of claim 11, wherein the gene expression studies comprise differential gene expression studies or microarray studies.

13. The computer system of claim 11, wherein the comparison of the disease-related pathways with user-defined data is made using a statistical model.

14. The computer system of claim 13, wherein the statistical model calculates the probability that overlaps between the disease-related pathways and user-defined data is a random event.

15. The computer system of claim 1, wherein the identification step further comprises storing the identified biological objects and processes according to the ontology.

16. The computer system of claim 1, wherein performance of computational analysis of biological relationships comprises generating one or more subsets of genomics information.

17. The computer system of claim 16, wherein the one or more subsets of genomics information are pre-generated from the knowledge base.

18. The computer system of claim 16, wherein the one or more subsets of genomics information are generated by one of a data-driven and model-driven approach.

19. The computer system of claim 16, wherein the one or more subsets of genomics information are generated based upon information contained in the knowledge base and user supplied genomics information.

20. The computer system of claim 16, further comprising the step of providing a user-supplied set of gene expression data for identifying a particular subset of genomics information, wherein the gene expression data are selected based on one or more of expression levels derived from inicroarray experiments, a prior analysis algorithm, and a user'"'"'s preferred gene set.

21. The computer system of claim 16, wherein the one or more subsets of genomics information are gene-centric being derived about a central gene for all genes in the knowledge base.

22. The computer system of claim 16, wherein the generation of one or more subsets of genomics information further comprises deriving one or more subsets of genomics information of related user-selected genes.

23. The computer system of claim 22, wherein the one or more subsets of genomics information are generated so as to be non-overlapping by ensuring that user-selected genes do not appear in more than a predetermined maximum threshold number of subset of genomics information.

24. The computer system of claim 22, wherein the one or more subsets of genomics information are generated so as to be based on connections between a first known drug target gene and a second drug target gene of interest.

25. A networked computer system for identifying one or more drug discovery targets comprising:

a communication network; and

a computer system coupled to the communication network comprising a database for storing and accessing genomics information, wherein the genomics information comprises information relating to genes, their DNA sequences, their mRNA, proteins expressed from said genes and the biological effects of the expressed proteins;

wherein the computer system is configured to;

(i) receive a profile definition criterion from a user identifying a subset of biological objects and processes that act on biological sytems in a disease-related pathway;

(ii) generate a profile using the knowledge base, wherein the profile comprises a subset of the information contained in the database comprising information relating to genes, their DNA sequences, their mRNA, proteins expressed from said genes and the biological effects of the expressed proteins;

(iii) perform computational analysis of biological relationships among the subset of genomics information in the profile based upon the profile definition criterion; and

(iv) identify additional biological objects and processes that act on those objects associated with the disease-related pathways using the analysis of biological relationships;

whereby each identified object or process is a drug discovery target,

wherein the computer system comprises hardware for electronically searching the database.