Drug Discovery in the Age of Genomics Mark Kiel, MD PhD Alex - - PowerPoint PPT Presentation

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Drug Discovery in the Age of Genomics Mark Kiel, MD PhD Alex - - PowerPoint PPT Presentation

Sep 11, 2023 22 likes •348 views

Drug Discovery in the Age of Genomics Mark Kiel, MD PhD Alex Joyner, PhD Senior Field Application Scientist, Genomenon Founder and Chief Science Officer, Genomenon Biomedical Sciences & Bioinformatics Molecular Genetic Pathology

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Drug Discovery

in the

Age of Genomics

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www.genomenon.com | hello@genomenon.com | @genomenon Mark Kiel, MD PhD

Founder and Chief Science Officer, Genomenon Molecular Genetic Pathology University of Michigan, Ann Arbor

Alex Joyner, PhD

Senior Field Application Scientist, Genomenon Biomedical Sciences & Bioinformatics University of California, San Diego

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  • 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

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DRUG DISCOVERY IN THE AGE OF GENOMICS

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Core Benefits and Applications of Genomics

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

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

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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

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  • 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

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1950 - 1970 Phenotypic Screening 1970 - 1990 Putative Protein Target 1990 - 2003 EST Studies 2003 - 2013 GWAS Studies 2013 - now NGS Studies

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

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  • Focus on High-Yield Candidates
  • Decrease Failure Rate
  • Save on Opportunity Costs

REDUCE R&D COSTS

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“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.”

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J Transl Med. 2016; 14:105.

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  • 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

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

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  • Provide Supporting Data for Biomarker Candidacy
  • Establish Objectivity with Genetic Evidence
  • Support Understanding of Pharmacogenomics
  • Proactively Strengthen Initial Submission

EXPEDITE FDA APPROVAL

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

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  • More Efficient Product Development
  • More Innovative Clinical Trial Design
  • e.g. n-of-1 trials
  • Out-Compete Competitors

DECREASE TIME TO MARKET

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Practical Considerations for Use of Genomic Data

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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
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A GENETIC WORKFLOW MODEL

  • 1. Determine Study Parameters
  • 2. Design Cohort Composition and Inclusion Criteria
  • 3. Perform Sequencing/Array Experiment
  • 4. Analyze NGS Data
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PRIMARY & SECONDARY ANALYSIS

DNA to Data

chr

Gene ATGC

BAM FASTQ VCF

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TERTIARY ANALYSIS

Variant Interpretation - The Evidence Triad (ACMG/AMP)

PUBLISHED LITERATURE PREDICTIVE MODELS POPULATION DATA

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TERTIARY ANALYSIS

External Curated Data Sources

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QUATERNARY ANALYSIS

Cohort Analysis - Putting it all together at the population level

AGGREGATE ANNOTATE ASSESS

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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
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Representative Example Studies

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GAIN OF FUNCTION: V600E

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

BRAF mutations in Hairy Cell Leukemia

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GAIN OF FUNCTION: NOTCH2

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

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GAIN OF FUNCTION: JAK-STAT

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

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LOSS OF FUNCTION: SEZARY SYNDROME

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

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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

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

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MASTERMIND GENOMIC DATABASE

30M

TITLES/ABSTRACTS SCANNED

6.7M

FULL-TEXT GENOMIC ARTICLES INDEXED

10K DISEASES 25K GENES 4.9M VARIANTS

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

Thank You

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