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1. WO2020118158 - DRUG DISCOVERY AND EARLY DISEASE IDENTIFICATION PLATFORM USING ELECTRONIC HEALTH RECORDS, GENETICS AND STEM CELLS

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[ EN ]

CLAIM'

1. A method for identifying an agent that corrects a phenotype associated with a condition, comprising:

receiving, at a processor, a set of structured health data comprising electronic health records of a set of patients each comprising at least one diagnostic code associated with the condition;

processing, by the processor, the set of structured health data using a first algorithm to output a group of phenotypic clusters wherein each of the phenotypic clusters comprises a sub-set of the set of patients;

receiving, at the processor, genetic data for the set of patients;

processing, by the processor, the genetic data for a first phenotypic cluster of the group of phenotypic clusters using a second algorithm to output a set of phenotypic-genomic sub-clusters, wherein each of the phenotypic-genetic sub-cluster represents a subset of the patients of the first phenotypic cluster;

isolating cells from each of the patients in a first phenotypic-genomic sub-cluster of the set of phenotypic-genomic sub-clusters;

differentiating the cells into one or more disease-affected cell types;

assaying the disease-affected cells to identify a first disease phenotype associated with the condition;

contacting the disease-affected cells with a candidate agent;

assaying the disease-affected cells for the first disease phenotype after contacting the disease-affected cells with the candidate agent to determine whether the candidate agent corrected the phenotype; and

identifying the candidate agent as a treatment for the first phenotypic-genomic sub cluster if the candidate agent corrected the phenotype.

2. The method of claim 1, wherein the st<

differentiating the cells into all three germ lines simultaneously or individually using directed differentiating techniques.

3. The method of claim 2 or any other preceding claim, wherein the first disease phenotype is in germ layers differentiated into non-neural tissue and wherein the poly-genetic condition is a neuropsychiatric disorder.

4. The method of claim 1 or any other preceding claim, wherein the set of structured health data comprises diagnostic codes from electronic medical records.

5. The method of claim 4 or any other preceding claim, wherein the first algorithm comprises aggregating the diagnostic codes into a set of categories using data from the phenotype-side association study (PheWAS).

6. The method of claim 5 or any other preceding claim, further comprising processing the diagnostic codes into dimensional vectors describing the counts of the most common diagnostic codes in specific time windows for the patients.

7. The method of claim 5 or any other preceding claim, wherein the first algorithm comprises hierarchical clustering.

8. The method of claim 7 or any other preceding claim, wherein hierarchical clustering is performed using Euclidean distance and Ward’s method.

9. The method of claim 1 or any other preceding claim, wherein assaying the cells comprises using at least one of the following assays: image-based assays examining cell properties comprising proliferation, differentiation or migration, cell death markers or oxidative stress dyes, RNA sequencing (bulk or single cell), or electrophysiology testing.

10. The method of claim 5 or any other preceding claim, wherein the step of differentiating the cells comprises differentiating the cells into tissue types related to the set of categories.

11. The method of claim 1 or any other preceding claim, wherein the genetic data comprises mutations related to the condition.

12. The method of claim 1 or any other prece

comprises a clustering algorithm.

13. A method for identifying an agent that corrects a phenotype associated with a condition, comprising:

receiving, a set of phenotypic-genomic sub-clusters that were output from a processor that had performed the following steps:

receiving, at the processor, a set of structured health data comprising electronic health records of a set of patients each comprising at least one diagnostic code associated with the condition;

processing, by the processor, the set of structured health data using a first algorithm to output a group of phenotypic clusters wherein each of the phenotypic clusters comprises a sub-set of the set of patients;

receiving, at the processor, genetic data for the set of patients;

processing, by the processor, the genetic data for a first phenotypic cluster of the group of phenotypic clusters using a second algorithm to output a set of phenotypic-genomic sub-clusters, wherein each of the phenotypic-genetic sub-cluster represents a subset of the patients of the first phenotypic cluster; and

isolating cells from each of the patients in a first phenotypic-genomic sub-cluster of the set of phenotypic-genomic sub-clusters;

differentiating the cells into one or more disease-affected cell types;

assaying the disease-affected cells to identify a first disease phenotype associated with the condition;

contacting the disease-affected cells with a candidate agent;

assaying the disease-affected cells for the first disease phenotype after contacting the disease-affected cells with the candidate agent to determine whether the candidate agent corrected the phenotype; and

identifying the candidate agent as a treatrr

cluster if the candidate agent corrected the phenotype.

14. A method of identifying whether a medical record of a patient indicates a patient is likely to develop a genetic disease, the method comprising:

receiving, at a processor, a set of structured health data comprising an electronic health record of a patient comprising at least one diagnostic code associated with the genetic condition, a set of additional diagnostic codes, and genetic data;

processing, at the processor, the set of structured health data to determine whether the patient is a match for a phenotypic-genetic sub-cluster; and

flagging, by the process, the patient record to indicate the patient is likely to develop the disease within a certain time window.

15. The method of claim 14, wherein the processor re-determines whether the patient is a match for a phenotypic-genetic sub-cluster each time the patient’s electronic health record receives a new diagnostic code.

16. The method of claim 14, further comprising treating the patient with a drug associated with the phenotypic-genetic sub-cluster as treatment.

17. The method of claim 14, wherein the disease is a CNS disorder.

18. The method of claim 14, wherein the disease is Spinal Muscular Atrophy.

19. The method of claim 14, wherein the step of determining whether the patient is a match for a phenotypic-genetic sub-cluster further comprises:

isolating cells from the patient;

differentiating the cells into one or more disease-affected cell types;

assaying the disease-affected cells to identify a first disease phenotype associated with the condition; and

determining whether the patient is a match for the phenotypic-genetic sub-cluster based on the assays.

20. A method of preventing the onset of a dii

comprising:

receiving, at a processor, a set of structured health data comprising an electronic health record of a patient comprising at least one diagnostic code associated with the genetic condition, a set of additional diagnostic codes, and genetic data;

processing, at the processor, the set of structured health data to determine whether the patient is a match for a phenotypic-genetic sub-cluster;

flagging, by the process, the patient record to indicate the patient is likely to develop the disease within a certain time window;

isolating cells from the patient;

differentiating the cells into one or more disease-affected cell types;

assaying the disease-affected cells to identify a first disease phenotype associated with the condition;

contacting the disease-affected cells with a candidate agent;

assaying the disease-affected cells for the first disease phenotype after contacting the disease-affected cells with the candidate agent to determine whether the candidate agent corrected the phenotype;

identifying the candidate agent as a treatment for the first phenotypic-genomic sub cluster if the candidate agent corrected the phenotype; and

administering the candidate agent to the subject.

21. The method of claim 20, wherein the patient does not exhibit a common symptom of the disease or disorder prior to administration.

22. The method of claim 20 or any other preceding claim, wherein administration treats the disease or disorder.

23. The method of claim 20 or any other preceding claim, wherein administration treats the first disease phenotype associated with the disease or disorder.

24. The method of claim 22 or 23, wherein tre

second symptom associated with the disease or disorder.

25. The method of any one of the preceding claims, wherein the cells from the patient are stem cells.

26. The method of claim 25, wherein the stem cells are selected from embryonic stem cells, adult stem cells, or cord blood stem cells.

27. The method of any one of the preceding claims, wherein the cells from the patient are somatic cells.

28. The method of claim 27, wherein the somatic cells are fibroblasts.

29. The method of claim 27 or 28, wherein the method further comprises reprogramming the cells into induced pluripotent stem (iPS) cells, and then differentiating the iPS cells into the one or more disease-affected cell types.