Rare Diseases Experience as a Model to Critically Affect Innovation in Biomarker Strategy and Precision Medicine

Moderator

Candida Fratazzi MD

SpeakersClaudio Carini, PhD, FRCPath Giora Feuerstein MD, MSc. F.A.H.A. Mark Trusheim PhD Colin Williams PhD

Precision Medicine The Time is now

Claudio Carini, MD, PhD, FRCPathPfizer Inc.

Drug Development is a lengthy, high- attrition process

More Spending – Less Apparent Productivity and Innovation?

What is missing?

Biomarkers

Biomarker DefinitionA molecule that indicates an alteration ofthe physiological state of an individual in relationship to health or disease state, drug treatment, toxins etc

Biomarkers are by virtue of their shortterm availability predictors of long term events

Why Biomarkers are Important in Medicine?

Patient/Subject Selection

Prognosis of TX intervention

Patient/Subject Selection

Staging or Severityof Disease

Discriminate Health from Disease Stage

Safety/Prediction of AE

Monitoring ClinicalResponse to

Therapy

The Elephant in the Room

Understanding Biology

A multi -” omics”Strategy

Understanding Drug PK/PD

It’s

RA It’s

SLE

It’s

CD

It’s

JIA

It’s

UC

It’s

AS

It’s

RA It’s

SLE

It’s

CD

It’s

JIA

It’s

UC

It’s

AS

Putting it all together

nTarget

nEfficacy

nPK/PD

nSafety/ /Tox

nMechanism

n Pharmacology

n Disease progression

nClassification

n Precision Medicine

QualifiedBiomarkers

RT- PCR

IHC

Genechip

Flow cytometry

Molecular imaging

Protein analysis

Mass Spectrometry

Proteomics profiling

Biomarkers: Potential Guides to Effectiveness and Safety

• The -omics • Clinical• New study paradigms*• Experimental human

biology

• ImagingProteomicsPharmacogenetics

Metabonomics

An Integrated Approach

Building Bridges Between Research and Clinical Development

Exchange of Information

Biomarkers Connect Discovery and Clinical Research

Discovery & Preclinical Phases

Omics, Screening Based on Cellular ,

PhysiologicModels,

Driven by Target

PopulationAnalysis

• Better Qualified

Compounds• Patient EnrichmentStrategies

Clinical Research Phases

Clinical Medicine

Diagnostic tests

PreclinicalAnimal Testing Compounds

Biomarkers

Patient samples Missing? Impact on clinical medicine

Bench to Bedside

What Patients Expect Today and More So in The Future?

• Drugs that work

• Drugs that are safe

• Doses that are right

for me

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A fit-for-Purpose Biomarker

13

Qualified Biomarker

Biology Clinical endpoints

A qualified biomarker must link a biomarker with biology and clinical end-points

Why Do we Need Biomarkers?

• To treat diseases more effectively: Disease Biomarkers• Disease BM will enable the:

• 1. Differentiation/stratification of otherwise similar disease states• 2. Better identifies which disease states are more responsible to the study drug• 3. Evaluation of disease susceptibility• 4. Treat high risk pts before the onset of symptoms• 5. Tracking disease progression

• To predict clinical efficacy: Patient Selection BM• Patient BM will provide:

• 1. Explain why Pts are responding differently to different drugs• 2. Basis for differentiating “high responders” from “low responders”• 3. To target “ high responders” who stand better chances of success

What is Personalized Medicine?

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Major Drugs Ineffective for Many…

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Beneficial to Some

Harmful to Others

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Why do individuals respond differently to the same drug?

Why do individuals require different doses?Why do some experience AE after taking the drug?

Genetic variation of the drug target gene

Genetic and genomic factors related to the etiology of the disorder

Genetic variation in the biochemical pathways affected by the drug

Other factors (age, sex, diet, environment ...)

Pharmacogenetics looks at inherited factors that may influence these differences.

Current Treatments Take Little Account of Human Variation

Non-Responders

Responders

Adverse Drug Events

Personalized Medicine Foresees Greater Use of Diagnostics in Therapeutic Decision Making

Non-Responders

Responders

Adverse Drug Events

DxTest

A

B

C

Choose the RIGHT DRUG at the RIGHT DOSE for the RIGHT PERSON

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To avoid adverse events: 2.2 million people are hospitalized and

100,000 deaths occur each year due to adverse effects of prescription drugs

Why is Personalized Medicine Important?

To identify novel drug targets: Current drugs are based on less than 500

targets.

To better treat disease: Development of predictive markers would allow for

earlier treatment

Why we Need Personalized Medicine in Research and Drug Development?

Safer and more Effective Drugs

22

Six Blinded Scientists Examining an Elephant

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Translational Medicine: the lacking piece of the puzzle

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Gene discovery and genomic prediction of Atherosclerosis disease states and susceptibility

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Biomarkers In Drug Discovery and Development: Orphan Diseases and Orphan Therapeutics

Giora Feuerstein MDFARMACON LLC

Washington DC

June 28, 2011

…and its getting worse

Translational Medicine in Pharmaceutical Industry:

from “nice to have” to “do or die”

Translational Medicine in Pharmaceutical Industry: from “nice to have” to “do or die”

• Aims at reducing the Attrition Rate – Increase Successful Deliveries by Rigorous Science

• From “Bench to Bed and Bed to Bench” (BB2)

• Identification, validation and implementation of Biomarkers in lieu of clinical end-points

• Harmonize and Rationalize Pre-clinical Research, Safety/ADME and Early Clinical Development

Biomarkers: A Utilitarian Classification

• Biomarkers that validate the importance of the target in human disease

• Biomarkers that define the direct interaction of the compound with its discrete target

• Biomarkers that define consequences of compound interaction with the target relative to PK

• Biomarkers that correlate with disease (initiation, progression, regression, remission, relapse or modification)

• Biomarkers that define likelihood of patients to respond (or not) to the compound

Target/CompoundInteraction

Pharmacodynamic Activity (PK/PD)

Target Validation

Disease Biomarker& Disease Modification

Patient selection andStratification

PK/PD Biomarkers in Orphan Disease show the way

• Case Study 1: Muckle–Wells syndrome• Rare genetic disorder provides biomarkers that ‘pave the way’ for target validation

•The case of anti-IL-1b development for RA• PK/PD- Biomarkers

• Bayesian methodology• Target validation in M-W syndrome

• Registration for Rheumatoid arthritis

Target Validation: When Biology Trumps Chemistry

• Case Study 2: Diabetes• Diabetes drugs are available but unmet medical need high

•Insulin injection is the ultimate treatment in chronic diabetes• Insulin sensitivity drugs (TZDs) of limited efficacy and carry safety issues

• 11beta-HSD-1 inhibitors have the potential to improve insulin sensitivity• Neuro-endocrine liabilities observed with all HSD-1 inhibitors

                      Website for this imagehealth.com

•Full-size image - Same sizex largerThis image may be subject to copyright.

Translational Medicine Case Study: When Biology “trumps” the compound, The 11bHSD1 Inhibitor saga

[cortisol]n

[Drug]

Plasma

[HSD-1]act

Tissue

[Drug]

[cortisol]

~

~~

Hypothalamus

Pituitary

Adrenal

-

Cortisol

~

~ ~IR

PK

PDPlasma

Adipose Tissues

Liver

Translational Medicine Issue: Can 11beta-HSD-1 inhibitors reduce peripheral tissue local cortisol and reduce tissue IR w/o activating the HPA

• Translational Medicine study (Univ Edinburgh, B walker)

Tissue cortisol production is significant In non-diabetics:

– Liver: Major source (~90%) of splanchnic cortisol release into the circulation– SubQ fat: Account for ~10% of cortisol release – Visceral fat: does not appear to contribute to net cortisol output

SubQ Fat Visceral Fat

D4-Cortisol/D3-Cortisol

The “Killer Study”

HSD1 inhibitors can reduce IR w/o change in plasma cortisol

Rare Diseases as Stratified Medicine Economic Models

Mark Trusheim

Visiting Scientist, MIT

trusheim@mit.edu

President, Co-Bio Consulting

What We Mean by Stratified Medicine

• Matching therapies to patient sub-populations with clinical biomarkers

• Objective: Do more good (efficacy) or avoid ill (adverse reactions)

• Clinical Biomarkers -- beyond genotyping

• Molecular (gene expression, proteomic, biochemical)• Imaging• Clinical observation• Patient self-reporting

• Clinical Biomarkers: Any information which shows a reliable, predictive correlation to differential patient responses

The Patient Therapeutic Continuum: Stratified Medicines are not “Personalized”

Nature Reviews Drug Discovery: April 2007

Orphan Drugs Demonstrate Economic Potential

(thousands of patients, average yearly price in $thousands)

StratifiedMedicinesIncreasinglyApproachingOrphan sizes

Comparing Orphan and Stratified Medicines

Orphan

• Known mechanism & marker

• Small population

• Strong patient and provider networks

• Modest payer impact

Stratified

• Known mechanism & marker

• May be small or large population

• Perhaps unrecognized strata and no networks

• Modest payer impact for one, but large if entire field (like oncology) stratifies

When are Orphan Drugs Good Models for Stratified Economics?

• Stratification creates a small population• Strong patient advocacy exists• Clinical trial and regulatory models for small populations

BUT

• Market exclusivity and lower competition may not apply• Payer concern that a large stratified condition is not ‘rare’

10% of all Alzheimer’s patients is a lot of patients, and cost.

Orphans Modeling Stratified Medicines: Expect Price and Profitability Premiums?• Supporting Arguments

• Stratified medicines will perform substantially better for their target populations than alternative treatments (assumption)

• Recently introduced therapies have commanded price premiums: biologics, stratified medicines, adjuvant therapies

• Payers have formal or informal policies to “pay for performance”

• Counter Arguments• Limited payer ability to afford increased costs• Diagnostics will siphon profitability• Multiple entrants in new “stratified” drug classes will lower prices

• Analytical Task• Develop a Performance Differential/Price Premium curve by examining price premiums

obtained in the market today by “classic” therapies LIKE ORPHAN DRUGS

PricePremium

Performance Differential

Orphans Modeling Stratified Medicines: Development Processes• Opportunities

• Strong patient and provider networks to enable clinical trials• Novel clinical trial designs to accommodate few patients available can speed

development and lower costs• Potentially more rapid entry into man based on strong mechanism

understanding and high need

• Challenges• Need to develop and validate biomarker lower since embedded in diagnosis• Regulatory skepticism that stratification is tactic to avoid ‘gold standard’ clinical

trials

ClinicalTrialSize

Biomarker Driven Performance Differential

Potential: Lower Cost and Higher Success

Probability ofRegulatoryApproval

Orphans Modeling Stratified Medicines: Public Policy and Incentives?

• Federal Research and Development Support• NIH grants for research, and even development (Bench to Bedside Awards)• Expedited regulatory pathways

• Federal Financial Incentives• Market exclusivity grants to INDICATION• High value reimbursement• R&D support above

• Registries to identify, monitor and involve patients and samples• Role for Disease Foundations

• Awareness, network creation and dissemination• Direct research support• Expert science panels validates early, small company science

Orphan Learnings in Stratified Medicine Examples

• Tysabri re-introduction for Multiple Sclerosis enabled by patient advocacy, patient registries and now, a biomarker

• Rare oncology sub-populations receiving Orphan level reimbursement

• Provenge autologous stem cell therapy: $93,000 for 3 course regimen• Erbitux and Vectibis: Up to $80,000 for 18 week regimen• Revlimid: Up to $10,000 per month for multiple myeloma• Gleevec: Up to $54,000 per year for CML

• High market shares (>80%) are possible

Conclusions

• Rare diseases and orphan drugs have blazed the trail for stratified medicine economic models

• From clinical development through regulatory to reimbursement and public policy, the lessons of rare diseases are being translated to stratified medicine

• However, the aggregate size of some stratified medicine markets may strain payers and induce skepticism by regulators that special treatment is appropriate

• An ‘integrated stakeholder chain” from research foundations to companies, regulators, payers and advocates is critical

Information in Biomarker discoveryHow effective use of information resources

can support innovation

Dr. Colin Williams

Thomson Reuters

Products used by more than 20 M researchers and clinicians worldwide

Checkpoint used by 99 of the top 100 U.S. accounting firms

Westlaw is used by 98% of the world’s major law firms

Applications used by over half a million professionals globally

Legal

Financial

Science

Healthcare

Tax & Accounting

Reuters News reaches over one billion people daily

Media

Informational healthcare products affecting more than 150 M lives

Why information?

• Knowledge differentiates organizations and delivers competitive advantage• Decreases risk• Enhances project level decision making• Focuses resource allocation• Empowers scientists to drive innovation• Creates efficiencies by preventing wasted experimentation

Conceptual biology: Unearthing the gems, Nature 416, 373; 2001 Blagosklonny, M and Pardee, A

“In 1990, all the necessary data for the concept of feedback control of p53 function were available, although this function was recognized only recently.”

The information challenge• Information overload

• Wide range of sources - Literature, Patents, Conferences and medical meetings, Press releases, Clinical trial reports

• Google 425k hits – Her2 and biomarker

• Highly variable terminology in Biology

• Lack of standard or Universal criteria on Biomarker development

• Variation in protocols, statistical analysis• So many parameters not enough subjects

• It is estimated scientists spend ~35% time dealing with information

Mesothelioma• Mesothelioma is a form of cancer that affects the Mesothelium

and can affect:• the inner surface of the chest wall where it is known as the

pleura• the abdomen, where it is known as the peritoneum.• Organs within those cavities eg lung, heart

• New diagnoses in US ~2,500 annually

• Mesothelioma drug pipeline – 52

• Compared to 1104 drugs under development for Obesity

• Source: Thomson Reuters Integrity

• Reported Biomarkers of Mesothelioma - 430

• 3,400 hits in Google search• PubMed 1143 results

Proof of efficacy with mesothelioma markers• Ranpirnase (activation of Caspase)• Cisplatin• Gemcitabine hydrochloride• Pemetrexed disodium • Troglitazone• PPAT agonist inhibitors• Lenvatinib Mesylate• BEZ-235 (Novartis Phase I/II breast cancer, mTor inhibitor)•Celecoxib• AZD-1152-HQPA

• Do the targets associated to these drugs have a role in other disease?

The Core cell cycle, Source MetaCore

Gene Expression and Mesothelioma• Developing insights from experimental information is also a critical

• Analyzing gene expression data from mesothelioma can give a glance in to the mechanism of the disease

• Analyse publically available dataset from Geo (GDS2604)

• Explore expression profile in responders to previously identified drugs and identify differentially expressed genes

Summary• Knowledge enhances decision making• Improve efficiency in project design through researching the area • Biomarker information is:

• published in a non standard way • is fragmented way• is expanding rapidly

• Disease segmentation based on molecular characteristics is going to create many new orphan diseases. • Will the ophan disease ‘model’ become the life blood of pharmaceutical

research• There are many biomarkers available which can prove efficacy of a

compound. • Using Mesothlioma (or other orphan diseases) as a model can prove

efficacy against a target quickly. • Understanding the biological function of that target can open new

indications for a therapeutic