Drug Discoveryin the

Age of Genomics

www.genomenon.com | hello@genomenon.com | @genomenon

Mark Kiel, MD PhDFounder and Chief Science Officer, GenomenonMolecular Genetic PathologyUniversity of Michigan, Ann Arbor

Alex Joyner, PhD Senior Field Application Scientist, GenomenonBiomedical Sciences & BioinformaticsUniversity of California, San Diego

1. WHY use Genomics?• Core Benefits and Applications of Genomics

2. HOW should we go about it?• Practical Considerations for Use of Genomic Data

3. WHAT are some Examples?• Representative Case Studies

Outline

3

DRUG DISCOVERY IN THE AGE OF GENOMICS

4

Core Benefits and Applications of Genomics

“[G]enetically supported targets could double the success rate in

clinical development”

5 Nat Genet. 2015 Aug;47(8):856-60.

GENOMICS EMPOWERS PHARMA TO:

•Optimize Pre-Clinical Therapeutic Targets

• Reduce R&D Costs

•Maximize Success of Clinical Trials

• Expedite FDA Approval

• Decrease Time To Market

6

• Understand the biomolecular basis of disease

• Identify new pathways in complex disease

• Provide a molecular starting point for targeted therapy

• Discover biomarkers in disease populations• Disease-Causing• Response-Modifying• Response-Monitoring

OPTIMIZE PRE-CLINICAL TARGETS

7

1950 - 1970 Phenotypic Screening

1970 - 1990 Putative Protein Target

1990 - 2003 EST Studies

2003 - 2013 GWAS Studies

2013 - now NGS Studies

8 Nat Rev Drug Discovery 2018 March; 17(3):183-196

• Focus on High-Yield Candidates

• Decrease Failure Rate

• Save on Opportunity Costs

REDUCE R&D COSTS

9

“The cost to develop new therapeutics has increased significantly over the past 30-40

years, while the success rate has remained unchanged.”

“Many therapeutic failures occur after large investment.”

10 J Transl Med. 2016; 14:105.

• Use Genomic Markers as Inclusion/Exclusion Criteria

• Ensure a More Homogenous Patient Cohort

• Establish a Molecular Companion Diagnostic

• Increase Drug Response Rate

• Add Statistical Power to the Study

MAXIMIZE SUCCESS OF CLINICAL TRIALS

11

12 https://www.q2labsolutions.com/companion-diagnostics

• Provide Supporting Data for Biomarker Candidacy

• Establish Objectivity with Genetic Evidence

• Support Understanding of Pharmacogenomics

• Proactively Strengthen Initial Submission

EXPEDITE FDA APPROVAL

13

14 The future of the drug approval process Linda Honaker; figure Rebecca Clements.

• More Efficient Product Development

• More Innovative Clinical Trial Design

• e.g. n-of-1 trials

• Out-Compete Competitors

DECREASE TIME TO MARKET

15

16

Practical Considerations for Use of Genomic Data

SELECTING THE RIGHT OMIC DATA

1. Single Nucleotide Variants and Indels

2. Structural Alterations – Copy Number Variants

3. Structural Alterations – Fusion Genes

4. Transcriptome – Gene Expression

5. Epigenetic Change – Methylation Marks

A GENETIC WORKFLOW MODEL

1. Determine Study Parameters

2. Design Cohort Composition and Inclusion Criteria

3. Perform Sequencing/Array Experiment

4. Analyze NGS Data

PRIMARY & SECONDARY ANALYSIS

DNA to Data

chr GeneATGCBAMFASTQ VCF

TERTIARY ANALYSIS

Variant Interpretation - The Evidence Triad (ACMG/AMP)

PUBLISHED LITERATURE

PREDICTIVEMODELS

POPULATIONDATA

TERTIARY ANALYSIS

External Curated Data Sources

QUATERNARY ANALYSIS

Cohort Analysis - Putting it all together at the population level

AGGREGATE ANNOTATE ASSESS

COHORT ANALYSIS

• Phenotypic and genotypic homogeneity is beneficial

• Presence/absence of a disease-causing mutation as

inclusion/exclusion criteria in a clinical trial

• Population-level sequencing identifies large, homogeneous

cohorts for specific diseases for clinical trials

• UK Biobank, Finngen, deCode, Genomics Medicine Ireland

24

Representative Example Studies

GAIN OF FUNCTION: V600E

Tiacci et al. NEJM 2011 Jun 16; 364:2305-15.

BRAF mutations in Hairy Cell Leukemia

25

GAIN OF FUNCTION: NOTCH2

Kiel et al.J Exp Med2012 Aug 27;209(9):1553-65. 26

GAIN OF FUNCTION: JAK-STAT

Kiel et al. Blood.2014 Aug 28;124(9):1460-72. 27

LOSS OF FUNCTION: SEZARY SYNDROME

Kiel et al. Nat Comm 2015 Sep 29;6:8470. 28

29

Complex and heterogeneous diseases –examples of strongly activating mutations

Conditions with genetic heterogeneity –pathway homogeneity uncovered by genomics

Across multiple related disease types –convergence of treatment strategies

THE PROMISE OF GENOMICS IN DRUG DISCOVERY

Nat Rev Drug Discovery 2018 March; 17(3):183-196

A Comprehensive Index of the Genomic Literature, Annotated for Clinical and Functional Variants

30

MASTERMIND GENOMIC DATABASE

30MTITLES/ABSTRACTS

SCANNED

6.7MFULL-TEXT GENOMIC ARTICLES INDEXED

10K DISEASES 25K GENES 4.9M VARIANTS

31

hello@genomenon.com | www.genomenon.com |1-734-794-3075

Thank You

Sign Up for Mastermind Basic Editionand get 14 days of Mastermind Pro

bit.ly/mm-pharma