Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | The Present and Future Role of Biomarkers in Clinical Development A Partnership.

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. |

The Present and Future Role ofBiomarkers in Clinical DevelopmentA Partnership Journey towards Precision Medicine

Presented by

Sponsored by

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. |Oracle Confidential – Internal/Restricted/Highly Restricted 2

Welcome & IntroductionsModerators

• Robert A. Lindberg, PhD, RAC Senior Director, Technology Transfer and Entrepreneur Programs

• MaryAnne Rizk, PhD Global VP, CRO Business Partnerships & Alliances, Oracle Health Sciences

Speakers

• Jeffrey Shuster, PhD - General Manager at the Biomarker Factory

• Thomas Turi, PhD - Vice President of Science & Technology for Covance Central Laboratory Services

• Thomas Povsic, M.D., PhD - Associate Professor of Medicine at Duke University Medical Center

• James Streeter – Global Vice President, Life Science Strategy


The Present and Future Role ofBiomarkers in Clinical Development

• Importance of Biomarkers in Clinical Trials and Precision Medicine– Cost to Develop New Pharmaceutical Drug Now Exceeds $2.5B– Fit-for-Purpose: How Biomarkers Can Be Leveraged to Improve Return on Investment

(ROI) in Drug Development

• Getting Precise on Precision Medicine– Patient Stratification

• The Collaboration & Partnership Journey– Innovation Solutions to accelerate Drug Development– Leveraging CROs and Sponsor Engagement Strategies


Cost of drug development has increased in recent years

According to PhRMA1:

• –In 1970, the average cost to develop a drug (including failures) was $140M

• –In late 1990s, the cost was $800M

• –In early 2000s, cost was $1.2B • 10-15 years from discovery to the marketplace

According to a 2013 article in FORBES2:

• –The cost to develop a drug is as high as $5B

1 http://www.phrma.org/sites/default/files/pdf/PhRMA%20Profile%202013.pdf

2 http://www.forbes.com/sites/matthewherper/2013/08/11/how-the-staggering-cost-of-inventing-new-drugs-is-shaping-the-future-of-medicine/


Why is the cost of drug development going up? High failure rate – 5,000 to 10,000 compounds enter the pipeline for every 1 FDA-approved medicine1 – Even medicines that reach clinical trials have only a 16% chance of being approved. 2

Clinical trials are becoming more complex, less likely to succeed.

• Personalized medicine and accompanying diagnostics development

• more procedures, more data, more numerous and complex eligibility criteria for enrollment, longer study duration. 3

Difficulty recruiting volunteers extends the original timeline of phase 2 to 4 trials by nearly double on average across all therapeutic areas.4– 1 http://www.phrma.org/sites/default/files/pdf/PhRMA%20Profile%202013.pdf

– 2 Tufts Center for the Study of Drug Development. “Large Pharma Success Rate for Drugs Entering Clinical Trials in 1993–2004: 16%.”

– Impact Report 2009; 11(4

– 3 K.A. Getz, R.A. Campo, and K.I. Kaitin. “Variability in Protocol Design Complexity by Phase and Therapeutic Area.” Drug Information Journal 2011; 45(4): 413–420.

– 4 Tufts Center for the Study of Drug Development. “89% of Trials Meet Enrollment, but Timelines Slip, Half of Sites Under-Enroll.” Impact Report 2013; 15(1).


Reduced profits after approval

• Fierce competition reduces revenue after approval

• After FDA approval, the average effective patent life of a brand name medicine is about 12 years

• Only 2 of every 10 brand name medicines earn sufficient revenues to recoup average R&D costs

1 H.G. Grabowski, et al. “Evolving Brand-name and Generic Drug Competition may Warrant a Revision of the Hatch-Waxman Act.” Health Affairs 2011; 30(11): 2157–2166. 2 J.A. Vernon, J.H. Golec, and J.A. DiMasi. “Drug Development Costs When Financial Risk is Measured Using the Fama-French Three-factor Model.” Health Economics 2009; 19(8): 1002–1005.


How can use of biomarkers increase ROI?

• “Biomarker” = a laboratory measurement that reflects the activity of a disease process1

• Quantitatively correlates with disease progression.

• Examples include: – Blood pressure – Cholesterol – Fasting glucose – Positron emission tomography (PET)

• –Magnetic resonance imaging (MRI)

1 Russell Katz, Biomarkers and Surrogate Markers: An FDA Perspective, NeuroRx, Apr 2004; 1(2): 189–195. doi: 10.1602/neurorx.1.2.189

Importance of Biomarkers in Clinical Trials and Precision Medicine

Jeffrey Shuster, [email protected]

Bringing Biomarkers to Clinical Practice

Translational Medicine in Diagnostics

A diagnostic is of use if it changes clinical practice.

Biomarkers in Clinical PracticeUtilities of Biomarkers

Disease diagnosis Prognosis, for selection of treatment Predictive, for optimizing therapy Companion diagnostics

Specimen obtainment and assay technology must be suitable for use in clinical practice

Studies must identify and validate

biomarkers in clinical materials

Areas of Interest for Biomarkers

Chronic disease

Cardiovascular Diabetes Mental health Cancer Arthritis Autoimmune diseases

Acute illness Cardiovascular events Infectious disease Cancer Toxicology Trauma

Health Nutrition Aging Microbiomes Immune system

functions Performance training

Translational Medicine in Diagnostics

Biomarker Study Components

1. Clinical need

What is the medical need for a new test over and above current clinical practice?

2. Patient population to be tested

What patient criteria will a physician use to order the test?

3. Actionable in clinical practice

Based on the test result, what will the physician do differently than he/she does today?

4. Number of patients

How many patients are estimated to be tested and how often?

Four Questions


A diagnostic is of use if it changes clinical practice.

A focus on the utility of the biomarker Diagnostic, prognostic, predictive, or companion Screening in the general population Screening in at risk populations Diagnosis in symptomatic patients

One biomarker may have more than one utility and can be used in multiple tests and

product lines.

Patient stratification to prescribe drug treatment Drug efficacy Drug side effects/toxicity

Example - Focus on the utility of the biomarkerProstate-Specific Antigen (PSA) Biomarker for Prostate Cancer

1979: Discovery of PSA (Wang et al., Invest. Urol. 17:159-63)

1980: PSA levels in serum as a biomarker of prostate cancer (Kuriyama et al., Cancer Res. 40:4658-62)

1986: FDA approval for PSA test as a monitoring test for patients already diagnosed with prostate cancer

1994: FDA approval for PSA test (with DRE) as a screening test for prostate cancer in asymptomatic men

Experimental Design

Have the right specimens, and have enough of them

Pre-define the target patient population

Do not settle for samples of convenience

o You cannot make a good test with bad specimens

In translational work, very careful attention to detail is necessary in

sourcing specimens

Make sure you understand all possible confounding variables

Understand the possible limitations of retrospective studies

Quality assurance for all samples in experimental design

Understand potential regulatory affairs issues up front

Example - Experimental Design

Biomarkers for Early Detection of Ovarian Cancer

Study 1 100.0 95.0

Study 2 86.5 93.0

Study 3 95.3 99.4

Study 4 74.0 97.0

Reported Reported SensitivitySpecificity

Discovery Experimental Design, Case-control,Cancer vs. non-cancer*

Attention to detail is necessary in sourcing specimens

Test Utility for Early Detection,≤ 12 months before Diagnosis**

CA125 64.6 95.0

Panel A 32.8 95.0

Panel B 64.6 95.0

Panel C 25.4 95.0

Panel D 52.3 95.0

at 95%Specificity

Sensitivity

**ref. Cancer Prev Res 2011;4 (3)*1. Petricoin et al., Lancet. 2002, 359(9306):572-7 2. Gorelik et al., Cancer Epidemiol Biomarkers Prev. 2005, 14(4):981-7 3. Visintin et al., Clin Cancer Res. 2008, 14(4):1065-72 4. Zhang et al. Cancer Res. 2004, 64(16):5882-90

Consider Design Options Early

Enlist biostatisticians throughout the discovery phase

Plan biomarker discovery as close to clinical specimens as possible

If the test will need clinical parameters

Include the clinical parameters in the discovery phase Does the new test out-perform current state of care

Sensitivity, specificity, PPV, NPV

ROC analysis, area under the curve

Calibration, reclassification

Costs of false positive and false negative results

Test Performance

Test performance requirements are based on the medical need.

What is the consequence of a false positive test ? Of a false negative?

Positive NegativeGold Standard

Nega

tive

Pos

itive

Test

Res

ult TP

FN

FP

TN

Sensitivity = TP / (TP+FN)

Specificity = TN / (TN+FP)

PPV = TP / (TP+FP)

NPV = TN / (TN+FN)

Rule In test [high specificity]

Rule Out test [high sensitivity]

Sensitivity, Specificity, andPositive and Negative Predictive Values

If the test has

95% sensitivity

95% specificity

it looks like this:

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

0% 5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

100%

Prevalence

PPV -NPV

PPV NPV

Positive Predictive Value

= 0.70

Diabetes screening in patients > 20 years of age

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1.10

1.20

0.00

01

0.00

10

0.01

00

PPV NPV

or like this:

Positive Predictive Value

= 0.004

Ovarian cancer screening in asymtomatic women age 50

Biomarkers in Clinical Trials

A Few Preliminary Questions on theUse of Biomarkers in Clinical Trials

At what stage of your clinical trial would you use a biomarker? Would you use a non-validated biomarker in a clinical trial? Would you not use a validated biomarker in a clinical trial?

Clinical Trials with Biomarkers

Year first received Trials with "biomarker" TrialsPercent with "biomarker"

2015 (to June 30, 2015) 1035 11598 8.9%2014 2100 23270 9.0%2013 1835 20444 9.0%2012 1685 19639 8.6%2011 1616 18228 8.9%2010 1625 17736 9.2%2009 1618 17156 9.4%2008 1341 17020 7.9%2007 1092 13397 8.2%2006 860 10932 7.9%2005 795 12907 6.2%2004 178 1797 9.9%2003 124 1664 7.5%2002 115 1589 7.2%2001 96 1349 7.1%2000 91 1986 4.6%

In 2005, the International Committee of Medical Journal Editors (ICMJE) began to require trial registration as a condition of publication.

Some metrics

(data from clinicaltrials.gov, 08/07/2015)

Biomarkers in Clinical TrialsIntegral, Integrated, or Exploratory

Integral: Required for trial to proceedPatient inclusion/exclusion criteria

Assignment to specific trial arm

Continue/discontinue treatment

IntegratedValidation of biomarker to be used in future trials

Experimental design and statistical analysis pre-specified

ExploratoryBiomarker discovery/ mechanistic studies/ hypothesis generation

Which Biomarker Technology?

Gene-by-gene Genome sequencingGene panels

Film image Digital image analysisDigital imaging

Western blot Mass SpectrometryELISA

Microarray RNA-seqRT-qPCR

IHCH&E FISH

Provides Best and Economic Use and

Suitable with Regulatory Requirements

and...

Biomarkers in Clinical TrialsUse of Analytically Validated

AssaysAccuracy and Precision

Sample obtainment and processing

Defined and obtainable standards

Qualified reagents

Analytical sensitivity

Analytical specificity

Stability

Example: Biomarkers in Clinical Trials

Use of Analytically Validated AssaysValidation of a multiplex assay for simultaneous

quantification of amyloid-β peptide species in human plasma with utility for measurements in studies of Alzheimer's disease therapeuticsLachno et al., J Alzheimers Dis. 2012;32(4):905-18Abstract. The aim of this study was to validate the INNO-BIA plasma amyloid-β (Aβ) forms assay for quantification of Aβ1-40 and Aβ1-42 according to regulatory guidance for bioanalysis and demonstrate its fitness for clinical trial applications. Validation parameters were evaluated by repeated testing of human

EDTA-plasma pools. In 6 separate estimates, intra-assay coefficients of variation (CV) for repeated testing of 5 plasma pools were≤9% and relative error (RE) varied between –35% and +22%.

Inter-assay CV (n = 36) ranged from 5% to 17% and RE varied from –17% to +8%. Dilutional linearity was not demonstrated for either analyte using diluent buffer, but dilution with immuno-

depleted plasma by 1.67-fold gave results within 20% of target. Analyte stability was

demonstrated in plasma at 2–8◦C for up to 6 h. Stability during frozen storage up to 12 months and through 3 freeze-thaw cycles at ≤–70◦C was also demonstrated in 5 of 6 individuals but deteriorated thereafter. Neither semagacestat nor LY2811376 interfered with the assay but solanezumab

at 500 mg/L reduced recovery of Aβ1-42 by 53%. Specimens from a Phase I human volunteer study of the β-secretase inhibitor LY2811376 were tested at baseline and at intervals up to 12 h after single oral doses, demonstrating a clear treatment effect. During 1,041 clinical assay runs from semagacestat

studies over 10 months, the CV for plasma quality control pools at three levels were≤15% and RE were <10%. In conclusion, the INNO-BIA plasma assay was successfully validated and qualified for use in clinical research.

Abstract. The aim of this study was to validate the INNO-BIA plasma amyloid-β (Aβ) forms assay for quantification of Aβ1-40 and Aβ1-42 according to regulatory guidance for bioanalysis and demonstrate its fitness for clinical trial applications. Validation parameters were evaluated by repeated testing of human EDTA-plasma pools. In 6 separate estimates, intra-assay coefficients of variation (CV) for repeated testing of 5 plasma pools were≤9% and relative error (RE) varied between –35% and +22%. Inter-assay CV (n = 36) ranged from 5% to 17% and RE varied from –17% to +8%. Dilutional linearity was not demonstrated for either analyte using diluent buffer, but dilution with immuno-depleted plasma by 1.67-fold gave results within 20% of target. Analyte stability was demonstrated in plasma at 2–8◦C for up to 6 h. Stability during frozen storage up to 12 months and through 3 freeze-thaw cycles at ≤–70◦C was also demonstrated in 5 of 6 individuals but deteriorated thereafter. Neither semagacestat nor LY2811376 interfered with the assay but solanezumab at 500 mg/L reduced recovery of Aβ1-42 by 53%. Specimens from a Phase I human volunteer study of the β-secretase inhibitor LY2811376 were tested at baseline and at intervals up to 12 h after single oral doses, demonstrating a clear treatment effect. During 1,041 clinical assay runs from semagacestat studies over 10 months, the CV for plasma quality control pools at three levels were≤15% and RE were <10%. In conclusion, the INNO-BIA plasma assay was successfully validated and qualified for use in clinical research.

BRAF V600E mutation in melanoma Vemurafinib and Dabrafenib

Example: Integral Biomarkers in Oncology

Clinical Trials

Example: Integral Biomarkers in Oncology Clinical Trials

Phase 1 - NCT00405587, Solid TumorsPaired melanoma biopsies must have a V600E+ BRAF mutation

Phase 2 - NCT00949702, MelanomaBRAF V600E positive mutation (by Roche CoDx BRAF mutation assay)

Phase 3 - NCT01006980, Melanomapositive for BRAF V600E mutation

Phase 4 - NCT01307397: MelanomaBRAF V600 mutation determined by Cobas 4800 BRAF Mutation Test

Vemurafenib Dabrafenib

Phase 1 - NCT01262963, Solid TumorsBRAF mutation-positive tumor (V600 E/K mutation) as determined via relevant genetic testing

Phase 2 - NCT01153763, MelanomaBRAF mutation-positive (V600 E/K) as determined via central testing with a BRAF mutation assay

Phase 2 -NCT01336634, Lung Cancer.BRAF V600E mutation confirmed in a CLIA-certified laboratory (or equivalent)

Phase 3 - NCT01584648, MelanomaBRAF V600E/K mutation-positive using the bioMerieux (bMx) investigational use only (IUO) THxID BRAF Assay (IDE: G120011).

A Few Additional Questions

If a biomarker result is required for use of a drug and

If biomarker positive patients respond to a drug, and

If biomarker negative patients are harmed by a drug

What is the consequence of a false positive test ? Of a false negative?

PD-1 Antibodies in Oncology

Example: Integral and Integrated Biomarkers in Immuno-oncology Clinical

Trials

Pembrolizumab and Nivolumab

Example: Integral and Integrated Biomarkers in Immuno-oncology Clinical Trials

*from Garon et al., Pembrolizumab for the treatment of non-small-cell lung cancerN Engl J Med. 2015 May 21;372(21):2018-28.

Biomarker

Response

Pembrolizumab in lung cancer*

Example: Integral and Integrated Biomarkers in Immuno-oncology Clinical Trials

Biomarker / Response

*from Robert et. al., Nivolumab in Previously Untreated Melanoma without BRAF MutationN Engl J Med. 2015 Jan 22;372(4):320-30

Nivolumab in melanoma*

"In the subgroup with positive PD-L1 status,

the objective response rate was 52.7%

(95% CI, 40.8 to 64.3) in the nivolumab group"

"In the subgroup with negative or indeterminate PD-L1 status,

the objective response rate was 33.1%

(95% CI, 25.2 to 41.7) in the nivolumab group"

Immuno-oncologyPD-1 Antibodies

Questions for consideration:

If 40-50% of biomarker positive patients respond to a drug, and

If 10-20% of biomarker negative patients respond to a drug,

How would this test be useful in future clinical trials?

In clinical practice?

What is the consequence of a false positive/negative test ?

Biomarkers in Alzheimer's Disease

Example: Alzheimer's Disease Integral and Integrated Biomarkers

in Clinical Trials

Phase 3 - NCT00905372: Progression of Alzheimer's DiseaseChange from baseline to endpoint in plasma A Beta

Phase 3 - NCT00904683: Progression of Alzheimer's DiseaseChange from Baseline to Week 80 in Plasma Amyloid Beta Levels

Solanezumab

Phase 1 - NCT00397891Total plasma amyloid-beta (x-40) was determined using a validated ELISA method

Phase 3 - NCT00575055Bapineuzumab in Patients With Mild to Moderate Alzheimer's Disease (ApoE4 Carrier)

Phase 3 - NCT00574132Bapineuzumab in Patients With Mild to Moderate Alzheimer's Disease (ApoE4 Non-Carrier)

Bapineuzumab

Importance of Biomarkers in Clinical Trials and Precision MedicineSummary

• Diagnostic, Prognostic, Predictive, and/or Companion

• Drug Efficacy: On Target, Clinical Response

• Drug Side Effects/Toxicity

• Patient Stratification

• Integral, Integrated, or Exploratory

Focus on Biomarker Utility

Some Questions in the Use of Biomarkers in Clinical Trials

1. At what stage of your clinical trial would you use a biomarker?

2. Would you use a non-validated biomarker in a clinical trial?

3. Would you not use a validated biomarker in a clinical trial?

4. If a high percentage of biomarker positive patients respond to a drug, and a low percentage of biomarker negative patients respond to a drug,

How would this test be useful in clinical trials? In clinical practice?

5. What is the consequence of a false positive test ? Of a false negative?

Importance of Biomarkers in Clinical Trials and Precision Medicine

Jeffrey Shuster, [email protected]



Oracle Health Sciences

Strategic Vision for Precision Medicine James StreeterGlobal Vice President Life Sciences StrategyOctober 16th, 2015

@OracleHealthSci#PrecisionMedicine

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 40

Safe Harbor StatementThe following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.


Oracle Health Sciences

Strategic Vision for Precision Medicine James StreeterGlobal Vice President Life Sciences StrategyOctober 16th, 2015

@OracleHealthSci#PrecisionMedicine

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 42

Safe Harbor StatementThe following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.


Industry Trends

More than half of clinical trials already have a molecular biomarker component

Significant reduction in cost of genome sequencing

Increase in real world data

Time

Cost

Patient stratification to identify population subsets most likely to respond to a therapy

70%

Provider

61%

Pharma

54%

Payer

Will you use secondary health data within the next 2 years?

Aggregation and analysis of Big Data

Cloud technologies are enhancing R&D collaboration


Accelerated Drug Discovery Through Biomarkers

Targets ALK protein, mutated in 7% of lung cancers

Crizotinib (Xalkori)

FDA approved from a trial of only 255 patients with the biomarker

3 years from biomarker mutation discovery to approval

Ivacaftor (Kalydeco)

Phase-III trial approval based on 161 subjects (Placebo 78; Ivacaftor 83)

10.5% mean absolute improvement in lung function

Fo

rmu

late

d T

oR

esu

lts

First in class targeted cancer therapeutic

Targets the BCR-ABL protein only occurring in Chronic Myelogenous Leukemia (CML)

Imatinib (Gleevec)

Now considered standard of care for Myelogenous Leukemia (CML)

Indication expanded to Gastrointestinal Stromal Tumors (GIST) with KIT mutations

Targets CFTR G551D mutation, present in 5% of cystic fibrosis patients


Biomarker Uses in Drug Development

Discover Develop Deliver


Requirements for Incorporating Molecular Analytics

Integrates with EDC

Systematic way to manage genomic data generated in a clinical trial

Genomic profile and analysis reporting

Single study and cross-study analysis of biomarkers

Integrates with well-established public domain data for joint analysis with your own data

a

Individual Clinical Trial


Oracle Products enabling Precision Medicine

Specimen

Enrolled Patient

Genomic profiling Molecular data analysis for

statisticians FDA submission

Laboratory

Doctor / NurseClinical Data

Molecular measurements

InForm AMA(Advance Molecular Analysis)

InForm/DMW (Study Data)

IRT(Enrollment Decisions)

Data Warehouse(Data Models)

Cohort Explorer

(Data Analysis)

Purchased or Public Domain Data

Big Data(Prescription, Institutional, Government, etc.)


Case Studies from Leading Molecular Data Initiatives

• To support Total Cancer Care program• 19 hospitals, 10 states, 90k cancer patients

• To power Moon Shots program• To change 8 cancer types from terminal to chronic diseases

• $100M personalized medicine effort• UPMC strategy – Science Driven, Patient-centric Care

• To power Center for Individualized Medicine (CIM)• Translational Research & Clinical use of 100k genomes


MD Anderson

Background / Needs Results With OracleMoon Shots initiative to cure 6

cancers in 5 years

Single platform for clinical and genomic data aggregation and analysis

Scalability to address data growth

One source of truth for all data

CASE

STU

DY

In less than 6 months, deployed a reporting environment that contains in excess of 1 million patients many thousands with genomic tests

Reduced time to run complex cohort identification queries from weeks to minutes in self service mode


Strategic Vision for Precision Medicine

Post linked and processed data is also warehoused and openly available

Increase tools and data linkage to increase the precision

Patient consent and biomarker collection is standard of care and industry shared

A world wide Genomic/Biomarker data warehouse

Is standard for Drug Discovery and Clinical Trials and Submission

Patients provides additional life long device data


[email protected]

+1.800.633.0643

www.oracle.com/healthsciences

mailto:[email protected]

http://www.oracle.com/healthsciences



The Present and Future Role ofBiomarkers in Clinical DevelopmentA Partnership Journey towards Precision Medicine

Presented by

Sponsored by

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | The Present and Future Role of Biomarkers in Clinical Development A Partnership.

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