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PatientDisease
Diagnosis T t dPersonalizedmedecine
Diagnosis
Risk
Targetedtherapies
Biomarkerprediction
Theranostic:Diagnostic TreatmentTheranostic:EfficayToxicity
g Treatment
y
Biomarkers and PM are included in medical practices since the 19th Biomarkers and PM are included in medical practices since the 19th century but their development has accelerated in the last century but their development has accelerated in the last decadedecadey py p
Biomarker of diabetes: glycemia
Biomarker of diabetes: Hb A1c
Biomarker of cancer:
Ovarian (CA 125) Prostatic (PSA)
Erbitux (Merck/Imclone) or Vectibix (Amgen) &
KRAS test
« Omics » and start of the genome sequencing
Couple Tysabri®/Stratify‐JCV antibody Elisa
test (Biogen Idec/Quest)
1960
1848 1980Couple
Selzentry/Trofile (Pfizer)
1986
Fi t f Couple1960 Amplichip Cyp450
(Roche/Affymetrix)Biomarker of myeloma: Ig chain (BJ)
in 75% cases
1959 First use of Pharmacogenomic
definition
Couple Xalkori®/Vysis® ALK Break Apart test (Pfizer/Abbott)
1998
20102000 2005 2007
2006
First use of Pharmacogenetic
definition
Discovery of genetic polymorphism of TPMT (Weinshilboum & Sladek)
1997 2011 2012
Biomarkers of cancer : alpha‐foetoprotein & CE
antigenCouple
Herceptin/Herceptest
(Roche Genentech/Dako)
Ig : immunoglobulin
BJ : protein of Bence‐Jones
1998 2006
Dasatinib (BMS) & Philadelphia chromosome
Couple Zelboraf®/ Cobas® 4800
BRAFV600E mutation test (Roche/Daiichi)
(Roche, Genentech/Dako)PSA : prostate specific antigen
TPMT : thiopurine‐méthyltransférase
chromosome
Medical genomics: a disruptive changeMedical genomics: a disruptive change
Time Period Genomes Turn‐around time
FTEs Cost per genome
1990‐2003 1. NIH reference2. Celera reference
~5 years ~5,000 ~2‐3 billion USD
2003‐2009 10 additional ~6 months Dozens 300,000→38,000 USD
2010‐2014 103‐104 2‐4 weeks 3‐4* 3,800/19,500→1,000 USD
2015‐2020 Millions 15 minutes <<1 100‐250 USD
*Excluding bioinformatics analysts
The top 10 CDx biomarkers evaluated in phases II andThe top 10 CDx biomarkers evaluated in phases II andThe top 10 CDx biomarkers evaluated in phases II andThe top 10 CDx biomarkers evaluated in phases II andIII confirm the dominant position of biomarkers in III confirm the dominant position of biomarkers in oncologyoncology
Top 10 biomarkers evaluated in phase II Top 10 biomarkers evaluated in phase III
Chr. PhKRASEGFRHER‐2
EGFRHER‐2Cyp
AKTCyp
BRCA1/BRCA2VEGFRBRAFc‐KIT
BRCA1/BRCA2ELM4‐ALK
Chr. PhBRAFKRASc‐KIT
Number of phase II clinical trials
0 10 20 30 40 50 60 70 80
PTEN
0 2 4 6 8 10 12 14 16
ERBRCA1/BRCA2
Number of phase III clinical trials
Cyp: cytochromes P450, HER‐2: Human Epidermal Growth Factor Receptor‐2, EGFR: Epidermal Growth Factor Receptor, c‐KIT: v‐kit Hardy‐Zuckerman 4 feline sarcoma viral oncogene‐like protein, KRAS: V‐Ki‐ras2 Kirsten Rat Sarcoma viral oncogene homolog, BRAF: v‐Raf murine sarcoma viral oncogene homolog B1, Chr.ph: chromosome de Philadelpie, EML4‐ALK: Echinoderm Microtubule‐associatedprotein‐Like 4‐ Anaplastic Lymphoma Kinase, ER: Estrogen Receptor, BRCA: Breast Cancer gene, TTPA: activated partial thromboplastin time, Anti‐XA: anti‐activated factor X.
Source: http://clinicaltrials.gov/, LEEM
The involvement of the pharmaceutical The involvement of the pharmaceutical industryindustry
in the clinical development of companion in the clinical development of companion diagnostic testsdiagnostic tests
Top 10 pharmaceutical companies involved in phase II clinical trials with companion diagnostics
nical tria
lsNum
ber o
f clin
Top 10 pharmaceutical companies involved in phase III clinical trials with companion diagnostics
Roche/ Genentech
Novartis BMS GSK Merck &CoPfizer AmgenAstraZeneca Sanofi/Genzyme
Eli Lilly
Top 0 pharmaceutical companies involved in phase III clinical trials with companion diagnostics
cal tria
lsNum
ber o
f clin
ic
Roche/ Genentech
Novartis BMSGSK Merck SeronoPfizer AbbottAstraZenecaSanofi/Genzyme
Ipsen
Source: http://clinicaltrials.gov
bioMerieux Silliker
bioMerieux
Transgene ABL industry
Food AndWater SafetyIn vitro Immunotherapy Water Safety
Nutrition/HealthIn vitro
DiagnosticsImmunotherapy
Therapeutic VaccineOncolytic viruses
Biomarkers(ADNA program)(ADNA program)
8
PARTNERSHIPS BETWEEN PHARMAS / BIOTECHS AND DIAGNOSTIC COMPANIES: MUTUAL BENEFITS
Benefits for
AND DIAGNOSTIC COMPANIES: MUTUAL BENEFITS
Benefits for Pharma & Biotech companies
Benefits for Diagnostic Companies
DiagnosticPharmas
•Reduction of cost / Development duration
•Capture of added value on Pharmas products
BiotechsDiagnostic
duration
•Drug salvage
p(royalties, patents, …)
N b i •Drug safety and Efficacy
De elop “niche”
•New business model (Companion test), source of income
Some times« ambiguous »
•Develop “niche” busters
source of income (co-marketing)
g
9
The impact of companion diagnostic tests on the The impact of companion diagnostic tests on the future of the pharma industry business model ? future of the pharma industry business model ?
Pros:
Improved evaluation of a given therapyImproved evaluation of a given therapy Life cycle management : differentiation against biosimilars/new entrants without Companion pdiagnostic tests Patient stratification during clinical development allows the patenting of new drug use & application
Cons: restricted patient populations and market
potential Increased and novel regulatory constraintswhich payor – price for the diagnostic test ? obligations to partner with IVD/biotechSource: Analyse Bionest Partners, Nature Reviews march 2009, « Biomarkers : The expanding global market », Yonker 2006
obligations to partner with IVD/biotech royalties on biomarker
‘’cancer biomarkers’’
n = 11,639
Kulasingam V and Diamandis EP (2008) Strategies for discovering novel cancer biomarkers through utilization of emerging technologies
Nat Clin Pract Oncol doi:10.1038/ncponc1187
What types of biomarkers do we have ?What types of biomarkers do we have ?
Di P i
Diagnostic PronosticScreening Follow-upPredictionof response
Disease Progression
gg ppto treatment
1. Screening (e.g. mammography, fecal occult blood)
2. Diagnostic (e.g. cardiac troponin)
3. Prognosis (e.g. cytokeratins, estrogen receptors)
4. Prediction of response to treatment (e.g. HER2)
5. Patient follow-up (e.g. PSA)
What Drives Successful Diagnostic Test (DX) Development?
DX regulatory approval drivers
Analytical Validity
Clinical Validity
1. Prototype2. RUO/LDT
Scientific HypothesisClinical Evidence1. Training, test set2. External validation-single site2. External validation single site3. External validation-multi-site
Clinical Utility
Health Economics
1. Demonstrate dx utility2. Demonstrate therapeutic
changes as SOC
1. Demonstrate quality of life impact
2. Demonstrate cost reduction
DX reimbursement drivers
For market success, developping a test represents a compelling investment for DX company…
Biomarker Research and Validation:A Long JourneyA Long Journey
Cli i l
Clinical utility & Health economicsPrototype
Final assay
Analytical validity
Clinical validity
Clinical utility Analytical validity
Product Development
15
Analytical and clinical validity drive regulatory approvalClinical utility and health economics benefits drive reimbursement
Product Development ProcessDrug-Diagnostic Co-Development Process:
Theranostic Theranostic
Cli i l D l tTherapyCommercial
LaunchNDA
SubmissionPhase IIIPhase IIPhase IPreclinicalDevelopment
Clinical DevelopmentTherapyCompound
OptimizationLead
Discovery
CE markedtest
Companion Diagnostic testPMA
A d T t
test
Phase 4Commer-
Phase 3Validation
Phase 2bVerification
Phase 2aDesign &
Phase 1Feasibility
Phase OBusiness
Diagnostic testBiomarker
Discovery & Validation of
Approved Test
Commer-cialization
ValidationVerificationDesign & Optimization
FeasibilityProposal
Design Controls
yClinical Utility
16
The steps of biomarker discovery and validation
Discovery Marker Marker y&
Technical feasibility
Leadgeneration
Lead confirmation
validation in a clinical
setting
Marker validated
(on 1platform)y platform)
Clinical studies
S l il bilit d litSample availability and quality
Quality insurance
Information management
Main challenges in biomarker discoveryMain challenges in biomarker discovery
Evidence‐based biomarker validation
+++++ long‐term randomized prospective study in the general population
++++ prospective study in a selected population
+++ retrospective study in a set of non representative+++ retrospective study in a set of non‐representative patients
t ti t d i t f t ti++ retrospective study in a set of representative patients
+ lab investigation taken from « Levels of evidence », BJU Int, vol. 101, 2008, p. 150
Personalised Medecine: Difficulties and challengesA novel model, based on data integration and validation of biomarkers:
-Technology: genomics proteomics metabolomics-Technology: genomics, proteomics, metabolomics
imaging etc..
-Clinical studiesDiff t ti b k dDifferent genetic background
Different environmental contexts (life style, nutrition…)
Clinical studies: quality, ethics etc..
- Public health
- Economics: Cost-benefit reimbursment etc- Economics: Cost-benefit, reimbursment etc..
Personalised Medecine: Difficulties and challenges
• A change of paradigm :
A novel model, based on data integration and validation
• A change of paradigm :- Shift from unique to mutiple, complex, biomarkers(multi-parameters = data intégration, bioinformatics,( p g , ,Computational biology, systems biology)
Intellectual property?- Intellectual property?.
- Management and transfer of information: physicians,
patients (cell phone etc )patients (cell phone, etc…).
Criteria for success Access to biobanks infrastructures clinical data . Access to biobanks infrastructures, clinical data, standardization (sampling procedures etc.)
A novel paradigm for industrial partners:M i t ll b ti i t d f i l tiMoving to collaboration instead of « isolation »Refining the intellectual property bases
• Academic environment: Project-driven
• Pharma-Diagnostics companies win-win interactions
• Simplified discussions with regulatory agenciesEarly discussions to define the requirements
Pharma Diagnostics companies win win interactions
Early discussions to define the requirementsReimbursements…
Public Private Partnerships:• Public-Private Partnerships:NCI biomarker networkFDA
‘’How long does it take to reach 10,000 cases in a cohort study with 500 000 people?”in a cohort study with 500,000 people?”
Paul Burton, UK BioBank Technical Report 2005
Breast cancer 17 yrsColorectal cancer 22 yrsProstate cancer 22 yrsLung cancer 34 yrsStroke 18 yrsStroke 18 yrsMI and coronary death 8 yrsDiabetes mellitus 6 yrsyCOPD 13 yrsHip fracture 21 yrsAlzheimer’s disease 18 yrs
Parkinson’s disease 23 yrs
Disease Consortium Number Subjectsof teams
• Parkinson GEO‐PD 18 10,000• Osteoporosis GENOMOS 10 30,000• Preterm birth PREGENIA 10 20 000• Preterm birth PREGENIA 10 20,000• Allergy/Asthma GA2LEN 50 20,000• Breast, Lung…K EPIC 20 500,000
L h INTERLYMPH 15 20 000• Lymphoma INTERLYMPH 15 20,000• Lung K ILLCO 30 51,000• Head & Neck K INHANCE 13 28,000• Melanoma GENOMEL 12 3,000• Pancreatic K PACGENE 10 5,000
Thematic network of biobanks
Main challenges in biomarker discovery
Bi l i l l T l
Main challenges in biomarker discovery
Biological samples ToolsBlood : plasma, serum DNA Tissue ; CellsUrine ; Stools
mRNA, miRNAMetabolome
Saliva ; Exhaled breath… ProteomeGlycomeyMicrobiomeImagingg g
BasicTranslational research needs
Model
Basicscienceshigh quality specimens
systems
Annotated biological samples
Patients ‐OmicsHTSsamples HTS
BioinformaticsData basesData bases
BiomarkersDrug targetsKnowledge
Personalized medicineg gKnowledge
Biobanks => 2 different conceptsBiobanks => 2 different concepts……
S i P hi• Service
S l i i d
• Partnerships
S l d il d i f i Samples + minimum data set
One‐way service
Samples + detailed information + outcome of patients + …
One way service
MTA + cash
Bi‐directional information
Customer service:From nothing to optional
MTA, contract + IPR
Customer service:From nothing to optional Customer service:Full expertise and advices
How to select a biobank ?main bottlenecksmain bottlenecks
Quality of both biological samples and linked y g pannotations, based on international standards and guidelines
Scientific and medical background
Quality of management
Well defined access policy
Expertise
Willingness and reactivity Willingness and reactivity
Ethical and regulatory issues
Inter- and Multidisciplinarity
Handling of data: knowledge managementBioinformatics, Systems Biology
« Big Science » and « curiosity-driven » science
BiomarkerInformationTechnologyF H lth
Public healthEthicsdiscoveryFor Health
« services »Business model
Ethics
Technologies: « omics »Research-Sequencing
- Epigenetic analysis- Proteomics
CohortsClinical studies
ResearchConsortia
AndNetworks
-MetabonomicsNetworks
Recherche académique-industrielleqLes « difficultés »
L i ibilité d l h h dé i La « visibilité » de la recherche académique pour l’industriel
La « frustration » générée par les choix de l’industrie (marketing…)industrie (marketing…)
R&D: le « D » plus que le « R »
Recherche sur projet, management
Recherche académique-industrielleRecherche académique-industrielleLes « besoins»
Un partage très précoce des objectifs et une définition précise de ces objectifs
Une absence « d’à priori »:U té li t- Une communauté: lieu, temps
- Des équipes « mixtes »
- Formation précoce des étudiants
Excellence-based TechnologicalTransfert
science
« curiosity-
TranslationalMedecine
« curiositydriven » Valorisation:
EconomicalProject-driven
MedicalSocial
Early phases of innovation: proof of concept
Education, training
Centres of excellence, innovation clusters
BIOASTER A j t ll th A project well on the go
What is at the base? Key figures Where do we stand?2 Co‐leaders :
• Lyonbiopôle• Institut Pasteur • 585 M€ budget over 9 years
• 180 M€ public funding
• Project set up team since May 2011
• Scientific Cooperation Foundation created (April 17, 2012)
3 Major industrial companies : • Sanofi Pasteur• Institut Mérieux• Danone Research
• 180 M€ public funding
• 40 projects at the 3 year mark
• 700 + scientists over 9 years
• Global Funding agreement signed with French National Research Agency (July 5, 2012)
• 1st BIOASTER board (July 6 2012)
3 Academic research institutions : • INSERM• CNRS
• ±35 000 m² new infrastructures• 300 + contributors involved in setting up the BIOASTER project
• 1st BIOASTER board (July 6, 2012)• BIOASTER scientific strategy released (28 Aug 2012)
• 1st wave of projects selected• CEA
2 Sites• Lyon : Gerland• Paris : Institut Pasteur
g p p j 1st wave of projects selected End of 2012 ‐ 6 projects launched
• Operational team in place End of Jan 2013 ‐ 20 people on board
• Paris : Institut Pasteur
1 Cluster of 50+ SME’s • Rhône‐Alpes & Ile‐de‐France
• Technology centers & Core facilities End of Feb 2013 ‐ 300m2 in Lyon & 600m2 in Paris
33Confidential
BIOASTER A change of scale in the infectious disease
fi ldfield•A new approach for infectious disease research : create a new operator to boost technological R&D and speed up the time to market of new products and services
– BIOASTER will constitute a strong link in the infectious disease innovation chain and will be the favored place to co-invest and share risks between industrials, intermediate size companies (ISC), SMEs and academic organizationsBIOASTER will speed up the time to market of innovative products and – BIOASTER will speed up the time to market of innovative products and services by changing knowledge and assets (patents, prototypes, licenses….) produced by interdisciplinary, collaborative public / private research, through short, medium and long-term projects meeting the market and industrial partners needs market and industrial partners needs
3434Confidential
BIOASTER will be structured around four main pillars
Technological Technological Internal and Internal and Technological Centers
Technological Centers Cooperative
R&D projectsCooperative R&D projects
Effective translational
research
Effective translational
research
Human resources
and Training
Human resources
and Traininggg
35
BIOASTERR&D programs performed through the technology centers & with partners
Program 1New
Therapies and Vaccines
Program 2Towards a real-time diagnosis
Program 3Microbiota, an indicator and health- New
therapeutic and Vaccines diagnosis care product therapeutic, preventive
and diagnostic products products
New
TC1A hub for the collection and
characterization f bi l i l
TC2Innovative
diagnostic and analytical
TC3Product
deorphaning, improvement
d
TC4Novel and
more efficient tools for
TC5Preclinical and
ealy clinical d l t
TC6Information technology,
data analysis d
New technologies and services
with high added valueof biological
resourcesanalytical
technologies and combination
tools for bioproduction development and
managementadded value
36Confidential
BIOASTERFirst round lab and office space – Paris & First round lab and office space – Paris &
Lyon Institut PasteurP t I tit t L bi l I f ti di François Jacob Center (BIME)Pasteur Institute Lyonbiopole – Infection disease
Center (CI)• 600 m2 available • 300 m2 available
– 250 m2 P1&P2 labs for core facilities– 150 m2 offices and meeting rooms– 100 m2 of labs for project teams
– 200 m2 P2, P2+ labs for core facilities– 100 m2 offices and meeting rooms
• Upcoming 500 m2 lab space
37
Market drivers in PMarket drivers in Personalised Medicineersonalised Medicine
Regulatory agencies & official bodies (EC)
PayorsP t f fbodies (EC)
Global improvement of healthcare, innovationGreater integration of Rx /Dx for more efficient and safer clinical trials
Payment for performancePayors/PBM are pushing for Rx‐Dx integrationespecially diagnostics that reduce healthcareexpenditures ‐ Ex: Medco Research Institute
L d hi l i H lth I tiIncreased vigilance on drug approvals and increased approval of genetic tests that influence safety and efficacy of drugs
Leadership role in Healthcare Innovation Establish clinical utility and cost effectiveness
Pharma companies Potential for higher price due to betterefficacy
Patients & Clinicians
yMore effective clinical trials – reduced groups with better resultsDx facilitates better Rx sales by enabling better market penetration differentiation
Increasing influence of patientadvocacy groupsPersonalized medicine reducesunnecessary therapies, leading
f d ffbetter market penetration, differentiation and expansion.
CDX: Life Cycle management tool, defence strategy against biosimilars threat Diagnostic Industry
Research progress in biomarker discovery
to fewer side effects
Research progress in biomarker discoverytranslating into more Dx testsNew emerging companies focusing on Dx
The European ChallengeThe European Challengegg
EPEMED White paper: Market access challenges in the EU for high medical value diagnostic testsIain Miller†1 2 Joanna Ashton Chess1 3 Herman Spolders1 4 Vincent Fert1 5 Joseph Ferrara6 Werner Kroll1 7 Jon Askaa8 PatrickIain Miller†1,2, Joanna Ashton-Chess1,3, Herman Spolders1,4, Vincent Fert1,5, Joseph Ferrara6, Werner Kroll1,7, Jon Askaa8, Patrick Larcier3, Patrick F Terry1,9, Anne Bruinvels10 & Alain Huriez1,3 Ref: Personalized Medicine (2011) 8(2), 137–148
EPEMED is an independent, broad and inclusive not-for-profit organisation founded in 2009 and bringing together forces in personalised medicine in the EU.
Key Value EPEMED’s Value PropositionEPEMED’s Value Proposition
p
Points for Members
•Forum to share best practices•Publications, white papers, conferences, education & promotion on promotion on Personalised Medicine subjects•Privileged access Privileged access to European decision makers•Input to policy makers on relevant legislation
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