Personalized medecine Biomarker
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1 Patient Disease Diagnosis Risk prediction Personalized medecine Biomarker Targeted therapies Diagnostic Theranostic: Efficay Toxicity Treatment 1
2 THE CASE FOR PERSONALIZED MEDICINE IS COMPELLING.. Toxicity Challenge Efficacy Challenge Adverse Drug Reactions Therapeutic Areas Efficacy Rate w/ Standard Treatment 4th leading cause of death Depression Schizophrenia Cardiac Arrhythmias Asthma Diabetes Osteoporosis Hepatitis C 62% 60% 60% 60% 57% 48% 47% Annual costs of around $136Bn Alzheimer Cancer (All Types) 30% 25% 0% 15% 30% 45% 60% 75% 90% $600B WW Rx spend, 50% with no efficacy- $300B placebo effect Source: Harvard Business Review Realizing the Promise of Personalized Medicine ; FDA ; biomérieux Internal Database ; Cowen & Co 2
3 WHAT ARE BIOMARKERS? «A biological substance, characteristic or image that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention». NIH Biomarkers Definitions Working Group,
4 BIOMARKERS GLOBAL MARKET In vitro diagnostic market (2007) : 27 BE Biomarker global market (2007): 5.6 BE Growth rate varies with the field it is estimated to be 5 to 18% Source: PIPAME, rapport biomarqueurs ministère de la recherche 4
5 WHAT TYPES OF BIOMARKERS DO WE HAVE? Disease Progression Screening Diagnostic Pronostic Prediction of response to treatment Follow-up 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) Ubiquitous vs Tissue specific Blood (serum/plasma, circulating cells), Tissue 5
6 biomerieux Silliker Transgene ABL biomerieux industry In vitro Diagnostics Immunotherapy Therapeutic Vaccine Oncolytic viruses Food And Water Safety Nutrition/Health Biomarkers (ADNA program) 11/01/
7 PERSONALIZED MEDICINE AT BIOMÉRIEUX Largest global pure play diagnostics company with strategic theranostics business focus Scale: more than ~$1.7Bn in sales in IVD, a global diagnostic leader in theranostics space, present in 150 countries via 39 subsidiaries and 6,500 employees Broad platform competencies Molecular biology, immunoassays, microbiology History of established successful partnerships in sector Deep knowledge of best partnering practices and emerging global regulatory requirements Full commercialization partnerships with GSK (2 deals), Merck, Ipsen, Transgene Large global S&M teams, installed instrument base, and flexible business model CLIA subsidiary biotheranostics in San Diego
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9 THE STEPS OF BIOMARKER DISCOVERY AND VALIDATION Discovery & Technical feasibility Lead generation Lead confirmation Marker validation in a clinical setting Marker validated (on 1 platform) Basic research Research infrastructures Competitive carreer tracks Clinical studies Sample availability and quality Quality insurance Information management 9
10 Excellence-based science «curiosity-driven» Project-driven Technological Transfert Translational Medecine Valorisation: Economical Medical Social Early phases of innovation: proof of concept Education, training Centres of excellence, innovation clusters, infrastructures 10
11 CONVERGENCE BETWEEN DIAGNOSIS AND THERAPY HAS BECOME A REALITY DIAGNOSTICS PROGNOSIS & TREATMENT Follow-up TREATMENT Patients Disease staging Treatment efficacy tolerance Breast cancer HER2 receptor expressed HER2 receptor Non expressed Trastuzumab (Herceptin ) Other chemotherapy) COLON cancer KRAS mutations Contra-indication to anti EGFR Cetuximab ou Panitumumab VIH infection CCR5 (vs CXCR4) receptor CCR5 inhibitors(maraviroc) 11
12 THE GERMAN QUALITY ASSURANCE SYSTEM FOR THE MOLECULAR- PATHOLOGICAL DETECTION OF KRAS- MUTATIONS IN COLORECTAL CANCER Quality assurance system 15% of laboratories failed A. Jung et al B.J Clin Oncol 27:15s, 2009 (suppl; abstr 4018) 12
13 EVIDENCE-BASED BIOMARKER VALIDATION long-term randomized prospective study in the general population ++++ prospective study in a selected population Change the medical practice? +++ retrospective study in a set of non-representative patients ++ retrospective study in a set of representative patients + lab investigation taken from «Levels of evidence», BJU Int, vol. 101, 2008, p
14 WHAT DRIVES SUCCESSFUL DIAGNOSTIC TEST (DX) DEVELOPMENT? DX regulatory approval drivers 1. Prototype 2. RUO/LDT Analytical Validity Clinical Validity Scientific Hypothesis Clinical Evidence 1. Training, test set 2. External validation-single site 3. External validation-multi-site 1. Demonstrate quality of life impact 2. Demonstrate cost reduction Health Economics Clinical Utility DX reimbursement drivers 1. Demonstrate dx utility 2. Demonstrate therapeutic changes as SOC For market success, developing a test represents a compelling investment for DX company 14
15 Clinical studies Different genetic background PERSONALISED MEDECINE : DIFFICULTIES AND CHALLENGES A novel model, based on data integration and validation of biomarkers : Technology : genomics, proteomics, metabolomics,imagingetc..: Infrastructures Different environmental contexts (life style, nutrition ) Clinical studies: quality, ethics etc.. Public health/ Economics : Cost-benefit, reimbursment etc. 15
16 PERSONALISED MEDECINE : DIFFICULTIES AND CHALLENGES A novel model, based on data integration and validation : A change of paradigm : Shift from unique to mutiple, complex, biomarkers (multi-parameters = data integration, bioinformatics, Computational biology, systems biology) Intellectual property? Management and transfer of information: physicians, patients (cell phone, etc ). 16
17 LOGISTICAL CHALLENGES How long does it take to reach 10,000 cases in a cohort study with 500,000 people? Breast cancer 17 yrs Colorectal cancer 22 yrs Prostate cancer 22 yrs Lung cancer 34 yrs Stroke 18 yrs MI and coronary death 8 yrs Diabetes mellitus 6 yrs COPD 13 yrs Hip fracture 21 yrs Alzheimer s disease 18 yrs Parkinson s disease 23 yrs From P. Burton, UK BioBank Technical Report
18 CRITERIA FOR SUCCESS Academic environment : Project-driven, Basic research Research infrastructures Access to biobanks infrastructures, clinical data, standardization (sampling procedures etc.) A novel paradigm for industrial partners : Moving to collaboration instead of «isolation» Refining the intellectual property bases Pharma-Diagnostics companies win-win interactions Simplified discussions with regulatory agencies Early discussions to define the requirements Reimbursements Public-Private Partnerships : NCI biomarker network FDA Critical Path Initiative: Predictive Safety Testing Consortium 18
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