Biomarker based pgx strategies
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Biomarker Based PGx Strategies. Rick Hockett, MD Chief Medical Officer Affymetrix. Why Are Biomarkers So Important?. “Providing meaningful improved health outcomes for patients by delivering the right drug at the right dose at the right time.”.

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Biomarker based pgx strategies

Biomarker Based PGx Strategies

Rick Hockett, MD

Chief Medical Officer

Affymetrix


Why are biomarkers so important

Why Are Biomarkers So Important?

“Providing meaningful improved health outcomes for patients by delivering the right drug at the right dose at the right time.”

Goal:Improve individual patient outcomes and health outcome predictability through tailoring drug, dose, timing of treatment, and relevant information

Targeted Therapy

One size fits all

Tailoring

(e.g. oncology productscomprising drug and companion diagnostic)

assess spectrum of patient response to therapy;

stratify patient populations; optimize benefit/risk.

Measure something in a patient to learn how to prescribe medicine

Tailoring is Broader Than Pharmacogenomics


Biomarker based pgx strategies

Increased Benefit:Risk Scenarios

“Providing meaningful improved health outcomes for patients by improving diagnosis, prognosis, or therapy choice.”

Diagnosing patients with particular traits

  • Identifying “Patient”

    • Diagnosis

    • Prognosis

    • Therapy

Identifying responders for targeted therapies (essentially highly tailored therapies)

Identifying who have an alternate prognosis (perhaps needing additional therapy)

Optimize dosing regimen for patient subpopulation(s) to achieve optimal benefit/risk

  • Tailoring “Dose”

Identify time to intervene during disease progression, time to complete therapy, or time to alter treatment regimen

  • Tailoring “Time”

Accommodate info for patient diversity, questions specific to payors or providers, or provide tools to meet needs of customers

  • Tailoring “Information/Tools”

Can apply one or more scenarios to each Lilly compound.

Scenarios can often be interdependent.


Why do we think genetics will play

Why do we think genetics will play?


Biomarker based pgx strategies

DNA

----ACGTGGGCAGTAGACTCAT----

----TGCACCCGTCATCTGAGTA----

RNA

Protein

----ACGUGGGCAGUAGACUCAU----

----Thr Trp Ala Val Asp Ser ----

Pinpoint the ‘right’ biomarker

Large Scale Fishing

DNA – 100K to 2x106 SNPs

Chip Based

Electrophoresis

RNA – 30K+

Chip Based -oligos

Slide Based - cDNAs

Protein – 1K upward

Mass Spec

Med. Scale Confirm.

DNA–2K to 30K

Chip Based

Electrophoresis

PCR Based

RNA– 30 to 1K

Chip Based -oligos

Slide Based – cDNAs

RT-PCR Based

Protein– 50 to 500

Mass Spec

Luminex Type

Small Scale Valid.

DNA– 1 to 25

PCR Based

Electrophoresis

RNA – 1 to 25

RT-PCR Based

Protein – 1 to 30

ImmunoAssay

Large Scale

‘Fishing’

Whole Genome

Scan

Medium Scale

‘Confirmation’

Many Different

Groups

Small Scale

‘Validated’

Clinical Trial

Support


Shrinking clinical pgx funnel

Interesting Genetic Associations

Genetic Polymorph

With Good

Sens. & Spec

Genetic Polymorph

With Rel. Risk

Y

Response

Y

Response

N

N

Genetic

Variant

Freq

N

Y

N

Y

Variation

Variation

Prospective

Clinical Proof

Shrinking Clinical PGx Funnel

Needs

Examples

Disease vs.

Response

Predictive

≥ 3

Apo E, CETP

5 - LO

vs.

Variants in Growth Genes

Situation Specific

Onc vs. Neuroscience

DMET

OncotypeDx

Clinically Utilized

PGx Tests

UGT1A1

Hercept Test

CYP2C9/VKORC1

c-kit

Tissue of Origin

HLA

EGFr

TPMT

Philly Chromosome


Hurdles to applying omics to medicine

X

??

Hurdles to applying -omics to medicine

  • Strategic

    • Gearing the infrastructure

    • Obtaining the talent

  • Technologic

    • Information overload

    • Lack of biologic understanding

    • Platform challenges

  • Regulatory

    • Understand how to apply technology

  • Implementation

    • Clinician education, understanding, and acceptance


Biomarker based pgx strategies

DMET PlusDrugMetabolismEnzymes&TransportersAn Example of Applying New Technologies to the Clinical Marketplace


The genesis of dmet

The Genesis of DMET:

  • March of 2004: Collaboration initiated between Lilly, ParAllele, and Affymetrix

  • The goal for Eli Lilly was to develop a clinical solution for better understanding the genetic components behind metabolism and transport:

    • Better ability to understand PK outliers in early phase trials

    • Build a database for selective recruitment of healthy volunteers with a defined genotype

    • Work with the FDA in an attempt to decrease the number of biopharm (DDI) trials needed for future NDAs

  • June 2006 was the inception of a working assay for clinical trials

  • Dec 2007 first NDA was submitted the FDA


Biomarker based pgx strategies

Pinpoint the ‘right’ biomarker

Using existing Affymetrix technology

Large Scale Fishing

DNA – 100K to 2x106 SNPs

Chip Based

Electrophoresis

RNA – 30K+

Chip Based -oligos

Slide Based - cDNAs

Protein – 1K upward

Mass Spec

Med. Scale Confirm.

DNA–2K to 30K

MIP Based

True Materials

RNA – 30 to 1K

Panomics Expression

Protein – 50 to 500

Mass Spec

Luminex Type

Small Scale Valid.

DNA– 1 to 25

MIP Based

True Materials

RNA – 1 to 25

Panomics Expression

Protein – 1 to 30

ImmunoAssay

Large Scale

‘Fishing’

Whole Genome

Scan

Medium Scale

‘Confirmation’

Many Different

Groups

Small Scale

‘Validated’

Clinical Trial

Support


Setting the stage for adoption of genetic analysis tools for use in personalized medicine

Setting the stage for adoption of genetic analysis tools for use in personalized medicine

Risks associated with taking

popular heart disease medication

Plavix (Clopidogrel)

  • Paper published in New England Journal of Medicine

  • Conclusion: Patients taking Clopidogrel and who were carriers of a certain gene variation had higher rates of heart attack, death and other cardiac-related events

  • Two additional independent studies recently published in NEJM and Lancet show similar PGx associations.


No relationship between genetics and pk pd for prasugrel significant effect for clopidogrel

No Relationship between Genetics and PK/PD for Prasugrel, Significant Effect for Clopidogrel

Pharmacokinetics

Pharmacodynamics

Integrated Genetic Analyses in Healthy Subjects


Biomarker based pgx strategies

PGx associated clinical outcomes of 1459 acute coronary syndrome patients treated with clopidogrel were significant

  • 1477 Patients were randomly assigned Plavix treatment with 98.8% being genotyped

    • CYP2C19 variant allele (1) frequency in treated population was 27.1%.

  • Primary efficacy outcome: composite of death from cardiovascular causes, MI and stroke.

    • 395 variant carrier patients had a 1.5 fold higher risk of death vs non-carriers.

  • 1389 Rx patients had stents implanted with a secondary endpoint of stent thrombosis.

    • 375 2C19 variant patients had a 3 fold increase in risk of thrombosis.

  • Two additional independent studies recently published in NEJM and Lancet show similar PGx associations.


Pharmacogenomics in drug development

Literature

Cell Lines

Tissues

DNA marker

RNA expression level

Protein

Pharmacogenomics in drug development

Development of a biomarker

Biomarker: A physiological response or laboratory test that occurs in

association with a pathological process and that has putative diagnostic

and/or prognostic utility

DNA or

RNA Samples

A.

B.

Identification of

potential biomarker

or drug target

C.

D.

Retrospective

confirmation

on clinical

samples

Use of marker

in prospective

clinical trials

Patient

Stratification

Plasma or

Serum Samples

Patient Samples are the Key


What we must do to enable omics impact

What we Must Do to Enable -omics Impact

  • Align focus on what can be done and where genetics is likely to work

  • Analyze, Integrate and Learn from data

    • Enable the field of Molecular Epidemiology

  • Enhance our biologic understanding of genetic influence of complex traits and produce more examples

  • Develop and validate technologies for clinical use

    • IT Infrastructure

    • Standards & Controls

  • Educate the medical infrastructure

  • Engage patients and third party payers


How do we enable omics uptake

Academics

Labs

FDA

Industry

Diagnostic

Companies

How Do We Enable -omics Uptake?

  • We cannot maintain silos

  • We must enable certain, common functions

    • Sample banking

    • Clinical trials

  • We must look to the regulators for direction

    • Standards

    • Controls

    • Critical Path Initiative


Biomarker based pgx strategies

The Biotech/Genomics

Revolution:

Increase the Benefit:Risk Ratio

Develop clinical aids for:

Diagnosis

Prognosis

Dosing

Therapy Decisions


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