I– INTRODUCTION - Collège de France

peaceevenBiotechnology

Oct 4, 2013 (3 years and 2 months ago)

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1
Chaire d’innovation technologique
Liliane Bettencourt
Recherche et Médecine
Translationnelle
Quelles Stratégies?
Elias Zerhouni
7 MARS 2011
Le Problème
• Malgré des avancées scientifiques
remarquables, notre capacité à traduire ces
avancées en bénéfices médicaux a diminué
• Le nombre de cibles biologiques potentielles
a explosé grâce aux progrès génomiques
• Taux de succès en biopharma : passés de 1/8
à 1/14

Durée de développement : doublée
Approbation des médicaments (FDA)
53
39
30
35
27
24
17
21
31
18 18
17
3
6
7
3
2
5
7
6
5
2
4
2
0
10
20
30
40
50
60
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Nouvelles entités moléculaires
Applications biologiques
Licences accordées aux nouvelles entités moléculaires et
biologiques approuvées par la FDA (E.U.) par années
Source: 2007 FDA drug approvals: a year of flux, Nature, February 2008
Croissance des dépenses de R&D >150%,
Nouvelles molécules baisse de 50%
February 20, 2005 Elias A. Zerhouni, M.D.,
Director, NIH
Central roles of molecular
biology, genetics and
genomics
Double Helix at 50
Exciting Times
:
Acceleration of Gene Discoveries for Common Complex Diseases
Human
Genome
Project
Complet
ed
Human
Genome
Project
Begins
HapMap
Project
Complet
ed
Genes and
Environme
nt
Initiative
Launched
Genetic
Associatio
n
Informatio
n Network
Launched
HapMap
Project
Initiated
The
Cancer
Genome
Atlas
Launche
d
Genome
Wide
Associatio
n Studies
Launched
NIH Research Initiatives
YR
90
91
92
93
94
95
96
97
98
99
00
01
02 03
04
05 06 07
Encyclope
dia of DNA
Elements
Launched
L’EXPLOSION DES DONNEES
N’EST PAS EQUIVALENTE
A L’EXPLOSION DU SAVOIR !
Aujourd’hui, notre
capacité limitée à
étudier les systèmes
biologiques complexes
est un obstacle
scientifique majeur!
Besoin de mieux
comprendre la compléxite
des systèmes biologiques
Défi scientifique:
Décrypter la complexité biologique
Source image : UCSD
Réponses cellulaires à
l’agression
Diagramme électronique
L’ERE de la BIOLOGIQUE
QUANTITATIVE des RESEAUX
Passer du “Hardware” au
“Software” de la vie
par la compréhension des voies moléculaires organisées
en modules fonctionnels
et leur régulation en santé comme en pathologie
Maladie 1
Maladie 2 a-b
Maladie 3 a-b
… les médicaments constitueront une part des solutions thérapeutiques
Prochaine frontière: le développement de cartes biologiques
quantitatives et fonctionnelles
Anticorps
monoclonal
Petite Molecule
Artificiels
peptide
Micro RNA
Bridging the translational divide
Standard Model
Laboratory
Research
Translational
Research
Population
Research
Clinical
Research
Public
Health
T1
T2
T3 T4
The key Factors
• Scientific Factors
– Biases of the past 20 years
– The target validation gap
– Mode of action and the ability to measure it in humans
• Professional Factors
– Clinician-Scientists
– Professional career pathways
– The changing roles of academic medical centers
• Socio-economic factors
– Regulations
– Stakeholders behaviors
Scientific Factors
T1 translational research
• Many targets, many cellular and animal models but low
predictivity in human disease
• Heavy reliance on surrogate biology away from human
biology
• Strategies:
– Systematic validation of published findings
– Development of specific biomarkers related to mode of
action
– Human samples as early as possible to validate
hypothesis
– Introduce more potent sampling and analytical methods
for human materials- LCMass Spec, Array readouts,
proteomics
Scientific Factors
T2 Translational Research
• Core issues: Predictive Efficacy and Safety
– A clear readout of efficacy via surrogate markers
– Development of novel methods of predictive safety-
More heterogeneous animal models, human iPSCells,
proteomics others?
– Phase 0 and investigational exploratory trials to
confirm mode of action, validate biomarkers
– Adaptive trial designs
– New Biostatistical approaches

Establish centers with access to human
pathologies and analytical methodologies
Scientific factors
T3 Translation
• Problem: from translation to effective diffusion of
translation
– Many advances are not applied to the degree
necessary to achieve expected results
– Typical of chronic diseases ( hypertension, diabetes)
– Need for « IMPLEMENTATION »research akin to
operational research
– Healthcare Delivery Systems redesign
– Discovering new therapeutic models: Chronic disease
management, novel drug delivery approaches
Scientific Factors
T4 Translation
• Limited understanding of population
epidemiology
– Natural prevalence and incidence are estimates
– No rigorous sentinel system to track epidemiologic
trends
– Insufficient surveillance to identify adverse therapy-
related events
– Need to use e-Health technologies
– Establish surveillance cohorts
– Behavioral and social sciences research
Professional Factors
• Clinician-Scientists
– Lack of critical « bridge » scientists who understand basic
research and experimental medicine
– Specific translational medicine training centers
• Professional career pathways
– Need to define a discipline of translational medicine with a
multidisciplinary viewpoint
• The changing roles of academic medical centers
– Overwhelming clinical service demands and focused away from
experimental medicine
– Inadequate for research on chronic diseases
– Need to balance clinical service and clinical investigations
Socio-Economic Factors
• Increasingly Complex Regulations
– Justified but ……..
– Drives scientists away from human research
– Not based on an explicit doctrine of risk and benefits
– What is an acceptable degree of risk relative to a given
benefit
– leads to loss of « greater good » concept towards an
absolute precautionary principle.
– Unknown epidemiology of underlying risks
– Industry is refocusing towards Specialty Drugs for
smaller populations and away from primary care drugs
Socio-economic Factors
• Stakeholders behaviors
– Payers believe medical innovation is key cause
of increased healthcare costs ( inappropriate
use of technological innovation is the culprit)
– Providers are not rewarded for supporting
innovation
– Patient groups are only stakeholders with a
strong interest in translational medicine
– NEED FOR PATIENT PARTICIPATION IS KEY
Trois thèmes principaux….
New Pathways
to Discovery
Re-engineering the
Clinical Research Enterprise
Research Teams
of the Future
NIH
New Pathways to Discovery
Genomic Era offers unprecedented
opportunities

Novel Approaches

Building blocks of biology (genes to
proteins)

Biological pathways and their controls

From Reductionist to Integrative biology

Innovative Technologies

Bioinformatics and computational biology

Molecular libraries

Nanomedicine

Novel research methodologies
Bioinformatics and
Computational Biology
Deploy a rigorous biomedical
computing environment to
analyze, model, understand and
predict dynamic and complex
biomedical systems across
scales and to integrate data and
knowledge at all levels of
organization
Bridging the translational divide
Standard Model
Laboratory
Research
Translational
Research
Population
Research
Clinical
Research
Public
Health
T1
T2
T3 T4
Bridging the translational divide
The Way it Should Work
Laboratory
Research
Patient-oriented
Clinical Research
Population-based
Clinical Research
Clinical Trials
TRANSLATIONAL MEDICINE
A NEW DISCIPLINE
La recherche biomédicale exige plus de
collaborations interdisciplinaires
PHYSIQUE
CHIMIE
BIOLOGIE
MOLECULAIRE
SCIENCES
INFORMATIQUES
MATHEMATIQUES
BIOENGINEERING
BIOMEDICAL
RESEARCH
A New Paradigm is Needed:
A Systems Based Approach
 Integrated approaches to
research and discovery
 Interdisciplinary training
 Translational research as a
recognized discipline
 Evolution from
departments to
interdisciplinary research
centers
 Widely shared resources
Haute résolution temporelle
Basse résolution temporelle
Multi-Dimensional
Uni-Dimensionelles
Cumulatives
Non cumulatives
Normes communes
Normes variables
Haute densité
Basse densité
Spatially resolved
Non localisées
Quantitatives
Qualitatives
Non-Destructives
Destructives
demain
Actuellement
Ceci va réclamer un changement radical des
caractéristiques des données biologiques
Maladie 1
Maladie 2 a-b
Maladie 3 a-b
… les médicaments constitueront une part des solutions thérapeutiques
Prochaine frontière: le développement de cartes biologiques
quantitatives et fonctionnelles
Anticorps
monoclonal
Petite Molecule
Artificiels
peptide
Micro RNA