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Watson Genomic Analytics

Watson Genomic Analytics. Select Watson solutions address a wide range of clinical and research needs in oncology Patient InsightsEvidence-based InsightsResearch

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Watson Genomic Analytics

Select Watson solutions address a wide range of clinical and research needs in oncology

Electronic Medical Record Advisor

Watson Discovery Advisor(Insights from vast Medical and Research literature)

Watson Genomics Advisor(Insights into Tumor DNA Sequencing)

Watson for Oncology (Lung, Breast, Colon/Rectal

Treatment Plans)

Watson Clinical Trial Matching (Identify all eligible trials for a patient)

Analysis of Medical Images (MRI, Mammogram, etc)

Available today Research Phase2

Currently in Development/Testing

© 2014 International Business Machines Corporation

© 2014 IBM Corporation

Path Toward Personalized Medicine

Prominent personalized medicine treatments & diagnostics available 2

Green, ED et al (2011). Charting a course for genomic medicine from base pairs to bedside. Nature 470: 204-213

13in 2006

113in 2014

1 Tufts Center for the Study of Drug Development, 2010; 2 Personalized Medicine Coalition, 2014

Change in personalized healthcare investment from 2005 to 2010 1

75%

Biopharmaceutical companies investing in personalized healthcare research in 2010 1

94%

© 2014 IBM Corporation

Decreasing Cost of Genome Sequencing

© 2014 IBM Corporation

Cancer Workflow: Research and Patient-Care

MutationDysfunction

Hyperplasia

DysfunctionSymptom/Finding

Mass

Radiology

Physical Exam & Review of Systems

Histology/Cytology

Molecular Analysis

Tumor Markers

Radiation

Chemotherapy Surgery

Biologics

Family Hx

Primary Care

Basic Science

Medical Hx

Biopsy• Diagnosis• Sub-type Analysis

• Personalize Therapy• Apply Treatment

Guidelines

© 2014 IBM Corporation

Diving Deeper on Gene to Protein Relationship

© 2014 IBM Corporation

Survival Benefit of Targeted Treatment

Kris M, et al. Lung Cancer Mutation Consortium Survival by Group 2014, American Medical Association.

© 2014 IBM Corporation

How are These System Being Developed?

Learn

Test

Ingest

Clinical trialsClinical trials

Pharmaceutical Reports

Pharmaceutical Reports

Chemical Chemical

PatentsPatents

MedlineMedline

Reference GenomesReference Genomes

MutationMutation

Protein Pathways

Protein Pathways

Patient ReportsPatient Reports

Dysfunctional Proteins &Targeted Treatments

© 2014 IBM Corporation

Protein Pathways: Consensus

© 2014 IBM Corporation

…doxorubicin results in extracellular signal-regulated kinase (ERK)2 activation, which in turn phosphorylates p53 on a previously

uncharacterized site, Thr55…

Extracts Preposition Recognizes preposition location on Thr55

Extracts EntitiesERK2 = Protein, P53 = Protein, Thr55 = Amino Acid

Extracts Verb Maps to domain of Post Translational Modification Recognizes subject / object relationships

Extracts EntitiesERK2 = Protein, P53 = Protein, Thr55 = Amino Acid

Extracts EntitiesERK2 = Protein, P53 = Protein, Thr55 = Amino Acid

ERK2

phosphorylates

p53

on

Thr55

Protein Pathways: ExploratoryNatural Language Processing (Annotators) Identify and Provide Structure to Concepts

Learn

Test

Ingest

© 2014 IBM Corporation

Aspirin

GI Pain

Valium

Depression

Annotator Logic

Apply Annotators to TextWatson Creates

Knowledge Graph

• Aspirin is an antiplatelet indicated to reduce the risk of myocardial infarction

• Known side effects include Gastrointestinal (GI) pain, GI upset, ulcers, GI bleeding, and nausea

• Valium or Diazepam is a benzodiazepine derivative, indicated for the treatment of anxiety, muscle spasms

• Valium may cause depression, suicidal ideation, hyperactivity, agitation, aggression, hostility…

• Drug = entity

• Side effect = entity association cause

• Cause = relating verb

• Rule = 1 drug to 1 side effect

Learn

Test

Ingest

Protein Pathways: ExploratoryConcepts are Classified and Relationships Defined

© 2014 IBM Corporation

• Quantity

• Proximity

• Relationship

• Domain Truths/ Business Rules

What genes contribute to developing

colon cancer?

Search CorpusExtract

EvidenceScore & WeighQuestion

• Side Effects

• Lab Notes

• Genes

• Publications

• Drugs

• Animal Models

• Clinical Trial Data

Learn

Test

Ingest

Protein Pathways: ExploratoryKnowledge is Reviewed and Statistics Added

© 2014 IBM Corporation

© 2014 IBM Corporation

Step 2: Organization

Domain Entities

Ontologies(e.g. organism, cell, protein,

amino acid)

Step 3: Relationships

Step 4: Prediction

Known Pathways Predicted Effects

Step 1: Exploring for Entities

Unstructured

FUNCTION

FORM

Jak2

Jak3 Jak1

TCF7

ATM

SER1TCF5

P53

Gene A Gene Bor

Protein Pathways: ExploratoryOverall

© 2014 IBM Corporation

Exploring Scientific Literature

© 2014 IBM Corporation

Exploring Scientific Literature

© 2014 IBM Corporation

Watson Genomic Analytics

© 2014 IBM Corporation

What Genomic Data is Being Leveraged?Sample Collection Sequencing

Variation Detection Data Presentation

© 2014 IBM Corporation

Watson Genomic Analytics: Process

Molecular Profile Analysis

Input: (Patient Specific)1) Somatic Mutation (VCF or MAF file)2) Copy Number Variation (log2 format)

These patient specific abnormalities are compared against known mutations and reference genomes to determine likely “drivers” of the patients cancer

-Databases are gathered from consensus community leading

Output: (Clinically Focused)1) List of Dysfunctional Proteins2) IBM Developed Driver Score3) Targeted Therapies

© 2014 IBM Corporation

Watson Genomic Analytics: Process (continued)

Pathway Analysis

Collections of consensus pathways (known) and NLP based augmented pathway (unknown) is used for our pathway traversal algorithm

Drug Recommendation

Proteins directly or closely related mutated proteins are identified and correlated with approved or investigational drug therapies

© 2014 IBM Corporation

Connecting Mutations to Treatable Targets

© 2014 IBM Corporation

As sequencing becomes less resource intensive genomic data is becoming more and more prevalent.

Genomic Data is being integrated with scientific literature and patient data to advance clinical care. This integration is allowing personalized medicine to take shape.

In response to the continued growth in the amount and complexity of medical knowledge industry leaders are leveraging process and machine-learning algorithms to scale expertise within and across the various basic science and clinical domains.

Summary

© 2014 IBM Corporation