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1 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
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© 2013 Benoit Dubuis © 2013 IBM Corporation
Medical revolution and new technologies
Dr. Benoit Dubuis, Directeur Eclosion, Président BioAlps 11 juin 2013
MEDTECH
“Medical revolution and new technologies”
The challenges
Towards an integrated health system
Our contribution
Innovation: The New Currency of
Competition
MEDTECH
“Medical revolution and new technologies”
The challenges
Towards an integrated health system
Our contribution
Innovation: The New Currency of
Competition
Crossing Visions
13.06.2013 | 4
PRINCIPAUX DEFIS DANS LE DOMAINE DE LA SANTE
DEFIS SCIENTIFIQUES
AUTRES DEFIS
Démographie
Coûts
Accès
Adoption lente de l’innovation
Utilisation inefficace de l’information
…
Crossing Visions
13.06.2013 | 5
CAUSE DE MORTALITE
TOUTES LES CAUSES 100%
Cardiopathie ischémique
13%
Maladies Cardio-vasculaire
29% Maladies Infectieuses et
parasite 23%
Cancers 12%
Maladies vasculaires cérébrales
9%
Maladies respiratoires
7%
SIDA 4.87%
Crossing Visions
13.06.2013 | 6
P
DEMOGRAPHIE: NOUS VIVONS PLUS
LONGTEMPS 90
80
70
60
50
40
Espéra
nce
de v
ie à
la n
ais
sance
1900 1950 2000
CH: 77
CH: 82
CH: 77
CH: 82
Age 60 – 2 Mia
Age 80 – 380 Mio
Age 100 – 2 Mio
2050
Point de référence:
Espérance de vie durant l’empire Romain était de ~30 ans
Crossing Visions
13.06.2013 | 7
DEMOGRAPHIE: NOUS VIVONS EN MEILLEURE
SANTE Ancien modèle
En bonne santé Malade
Malade
Modèle comprimant la morbidité
En bonne santé Années de vie gagnées
Malade
Modèle actuel
En bonne santé
Crossing Visions
13.06.2013 | 9
LA CHARGE DES MALADIES CHRONIQUES
Près de la moitié d’entre
nous aura un état chronique
d’ici 2030 :
Diabètes
Hypertension
Arthrite
Athéroscléroses
Accident vasculaire cérébrale
Cancer
Obésité
Hyperlipidémie
Maladie Neurodégénérative
Maladie Dégénérative Articulaire
Maladie pulmonaire obstructive
Etc. Dépense dans le
domaine de la santé
pour une personne avec
maladie chronique
Dépense dans le domaine
de la santé pour une
personne sans maladie
chronique
Etats chroniques
représenteront près
83% des coûts de
santé
Crossing Visions
13.06.2013 | 10
COÛT DE LA SANTE
Crossing Visions
13.06.2013 | 11
LES NOUVELLES PISTES
Médecine 3P
Pharmacogénomique
Bioconvergence
Médecine Translationnelle
Télémédecine
Crossing Visions
13.06.2013 | 12
DE LA MEDECINE « PRÊT-A PORTER » à
LA MEDECINE PERSONALISEE
Génomique Protéomique
Crossing Visions
13.06.2013 | 13
PREVENTIVE PREDICTIVE
PERSONNALISEE
Modèle comprimant la morbidité
En bonne santé Années de vie gagnée Malade
Personnalisé
Mortalité
Préventif
Morbidité
Prédictif
Crossing Visions
13.06.2013 | 14
VERS UN SYSTEME DE SANTE INTEGRE
Rx
2009
15 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Click to edit Master title style
MEDTECH
“Medical revolution and new technologies”
The challenges
Towards an integrated health system
Our contribution
Innovation: The New Currency of
Competition
Crossing Visions
13.06.2013 | 16
LA FORCE DU
RESEAU
CENTRES
MEDICAUX
OUTILS DE
RECHERCHE
INDUSTRIES
START-UP
CENTRES
ACADEMIQUES
Crossing Visions
13.06.2013 | 17
INNOVATION et INTERDISCIPLINARITE
Crossing Visions
13.06.2013 | 18
INNOVATION et INTERDISCIPLINARITE
Biotechnologie, Systèmes Biologiques
et Biologie Synthétique
Nanotechnologie Science des Matériaux
et Ingénierie de
Miniaturisation
Informatique de pointe
et WIRELESS
19 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Interdisciplinarity (science driven)
20 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Interdisciplinarity (science driven)
21 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Click to edit Master title style
MEDTECH
“Medical revolution and new technologies”
The challenges
Towards an integrated health system
Our contribution
Innovation: The New Currency of
Competition
22 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Micro / nanotech cluster
Bio-cluster
A unique hub
for Medtech/Biotech R&D in Europe
Crossing Visions
13.06.2013 | 23
INSTITUTIONS R&D DE CLASSE
INTERNATIONALE
Générer des connaissances Créer des opportunités
Crossing Visions
13.06.2013 | 24
QUALITE DES RECHERCHES
Nombre de publication par 1000 habitants
dans tous les domaines de connaissances et dans le domaine des Sciences de la vie
25 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
'evolutionary developmental biology'
Electronic health record'
ACCES AUX TECHNOLOGIES,
OUTILS ET CONNAISSANCES
Crossing Visions
13.06.2013 | 26
De l’idée au produit Créer de la valeur économique et des
emplois
Crossing Visions
13.06.2013 | 27
SARAH MARQUIS CONNECTEE
Coupure de journal Sarah Marquis…
Crossing Visions
13.06.2013 | 28
IMPACT SUR LA PRISE EN CHARGE
0
20
40
60
80
100 Chf 13’800
Chf 5’900
DIABETE: COÛT TOTAL vs COÛT DES MEDICAMENTS
Crossing Visions
13.06.2013 | 29
SYSTEME DE SANTE INTEGRE
0
20
40
60
80
100 Chf 13’800
Chf 5’900
Prédiction Personnalisation
Suivi à distance d’un Patient
30 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Remote Patient Monitoring
Worldwide Mobile Network
Carrier Moving data from body to
instrument (Programmer/Patient
Companion) to wireless carrier
worldwide.
Intimate Body Network Device to Device within the body
Personal Body Network Move data from device to
programmer or device to device
Distance: inches to several feet
31 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Personalized Medicine
Smart Sensing
Intelligent Information Management
Effective Interfaces
Putting the patient at the center of their health system
32 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
CSEM’s
Technology Progrms
MEMS
Ultra-low-power integrated
systems
Systems
Surface engineering
Non-invasive wearable sensors
Personal biosensors
Environmental sensors
New data streams + machine
learning = “New vital signs”
Smart sensing
33 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
CSEM: Human vital signs Multiparameter
Sensing
SpO2 / CBT
NIBP
ECG respiration
HR / HRV CO2 / O2
34 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Geophysical ExperimentWal
kin
g
Sitting
Donning
Sitting Wal
kin
g
DoffingTaking sample
Fall
• CBT
• HR
• BR
• SpO2
• 3D-ACC
CSEM : LTMS clinical study sample
35 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Intelligent Information Management
Longitudinal data
Personal baseline
Detect trends & deviations from norm
Personal health records
Privacy
Sharing
Anonymous aggregation
Patient-centered decision support
36 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Effective Interfaces
Multimodal
GUI, touch, gesture, speech, …
Mobile
Portable, networked, wearable
Intuitive
Easy to learn, use, maintain
Adaptive
Proactive
Source: Henry Kautz Department of Computer Science, Rochester University
37 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Ten Targets for Wireless Medicine
Alzheimer’s 5M Vital signs, location, activity, balance
Asthma 23M RR, FEV1, Air quality, oximetry, pollen
count
Breast Cancer 3M Ultrasound self-exam Web
COPD* 10M RR, FEV1, Air quality, oximetry
Depression 21M Med Compliance, Activity, Communication
Diabetes 24M Glucose, Hemoglobin A1C
Heart Failure 5M Cardiac pressures, weight, BP, fluid status
Hypertension 74M Continuous BP, Med compliance
Obesity 80M Smart scales, Glucose, Caloric in/out,
Activity
Sleep Disorders 40M Sleep phases, quality, apnea, vital signs
Disease No. Affected Wireless Solutions Disease Wireless Solutions No. Affected Disease Wireless Solutions
* Chronic obstructive pulmonary disease
Source: Burrill
38 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
The shift to patient-empowering,
information-leveraging technologies
“PI” (patient-empowering and information-leveraging) technologies
39 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Source: George Poste
Access,
cost and
quality
of care
Molecular
and
personalized
medicine
Proficient
use of
information
(e.health)
Link between Genomic and physiology
40 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Biocorpora –Drugdesigntech SA
Collaborative Drug Discovery
Sourc
e:
Dr.
Cédric M
erlo
t, D
rug D
esig
n T
ech
Information matters – Data lifecycle
41 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Sharing information
Huge amount of data produced, but not shared
Produced by HT technologies: screening, -omics
Stored in data silos, only useable by specialists
Need for one-stop-shop for all data for everybody
Provide a single point-of-entry to all project data
Explain raw data to non-specialists scientists
Share data across multi disciplinary research teams
Enable re-analysis, reuse data
Combine information from multiple sources
Drill down from summarized data to raw data
Sourc
e:
Dr.
Cédric M
erlo
t, D
rug D
esig
n T
ech
42 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Collaborative Drug Discovery
publication
molecules High troughput
project leaders data analysis labs
in-context
reporting
Biocorpora
proposals CRO
Sourc
e:
Dr.
Cédric M
erlo
t, D
rug D
esig
n T
ech
43 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
The application of various 'omic'-technologies is
leading to the generation of vast amounts of data
Systems Biology studies assemblies of interacting biomolecular
components at multiple levels of biological abstraction.
The current challenge is to develop new computational tools and
analytical procedures that allow the integration of these various
datasets
44 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
- omics Data Management
Microarray Flow cytometry NMR Mass spectrometry
analysis
project leaders data analysis labs
in-context
reporting
Biocorpora
Sourc
e:
Dr.
Cédric M
erlo
t, D
rug D
esig
n T
ech
45 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Megaclust: SIB, Vital-IT & Genebio
Enabling flow cytometry data analysis
Rethinking Enabling
Data
acquisition
Result Analysis and
decision making Identification of cell types
Leveraging the power of flow cytometry in clinical trials is a
great challenge due to the size and complexity of the data
generated.
MegaClust thoroughly and accurately identifies the different
cell types present in the dataset
Sourc
e:
megaclu
st.
vital-
it.c
h
46 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Megaclust: SIB, Vital-IP & Genebio
Enabling flow cytometry data analysis
MegaClust is an integrated service for the analysis of large and
complex flow cytometry datasets
- Proprietary algorithm
- Optimized for massive parallelization
- Deployed on 256 processors
- Multidisciplinary
expertise
Sourc
e:
megaclu
st.
vital-
it.c
h
47 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Megaclust: Example of identification of AML
treated patients among 50 individuals
MegaClust
5 markers
per sample
...
50
individuals
1.5 M cells (30 K cells * 50 ) and 5 dimensions ( ) AML: acute myeloid leukemia
Sourc
e:
megaclu
st.
vital-
it.c
h
48 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Megaclust: Each individual has unique amounts
of each identified cell types (unique fingerprint)
50 individuals
16
ide
ntifie
d c
ell ty
pe
s
Each column represents a patient specific cellular fingerprint
A9
A172
A37
A95
A58
A33
C167A5
A174
A49
C62
C287
C330
C84
C201
A219
C200
C321
C35
C184
C206
C213
C77
C241
C86
C356
C315
C229
C41
C182
C320
C85
C317
C272
C282
C277
C178
C80
C91
C129
C254
C343
C251
C193
C265
C23
C217
C341
C78
C17
cellu
lar finge
rpri
nt
Sourc
e:
megaclu
st.
vital-
it.c
h
49 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Megaclust: Fingerprints have the power to
stratify individuals (separate controls from AML)
AML
Control
- No a priori assumptions →
unrestricted analysis
- No human bias
- Reproducible
- Handles very large data sets
- Fast
Sourc
e:
megaclu
st.
vital-
it.c
h
50 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Megaclustenables stratification and therefore
provides key insight at each phase of the drug
development pipeline
toxicity/effectiveness assessment
Stratification
design of focused patient group
markers selection
responders characterization
adverse effects
phase1 phase 2 phase3 preclinical
animals healthy
volunteers small group of patients large group of patients
Sourc
e:
megaclu
st.
vital-
it.c
h
51 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
IBM BlueGene/L
IBM Systems & Technology Group
EPFL / IBM Confidential | 6/13/2013
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52
EPFL’s Brain & Mind Institute: Application Needs
NeuroInformatics
• 10++ different databases, ~ 100TB of Storage required
• 1000 to 10’000 Cells structure information
NeuroSimulation
• BioChemical Networks
• Molecular Interactions underlying Synaptic Processes
• Microcircuits
NeuroVisualization
• Synaptic Structure
• Neuronal Structure
• Microcircuit Structure
53 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
Praesalio – Drugdesigntech SA
Predictive Toxicology
Lack of safety is a major cause of attrition
Raised during clinical phases, incl. Phase IV
Loss of all investments
Reduces therapeutic window (lack of efficacy)
Identify and fix potential issues in drug discovery
Structural modifications are still allowed
Deliver fully characterized compounds
Need for focused, fast evaluation of liabilities
Computer predictions to focus on relevant experiments
1000’s of endpoints evaluated fast and at low cost
Sourc
e:
Dr.
Cédric M
erlo
t, D
rug D
esig
n T
ech
54 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
From data to information
Activity DB Models Project
information
Crunching Predictions
1M+ structures
10M+ activities
3000 models
6Tb storage
1 answer
what are the liability in my
compound ?
Sourc
e:
Dr.
Cédric M
erlo
t, D
rug D
esig
n T
ech
55 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
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MEDTECH
“Medical revolution and new technologies”
The challenges
Towards an integrated health system
Our contribution
Innovation: The New Currency of
Competition
Crossing Visions
13.06.2013 | 56
COMMUNAUTE INDUSTRIELLE
Crossing Visions
13.06.2013 | 57
CHAMPION DU MONDE DE LA CROISSANCE
Vitesse moyenne de croissance annuelle 95-00, 00-06
Source: BAK, Basel Economics
58 IBM Technology Day 2013, Keynote B. Dubuis 11.6.2013
A Successfull biocluster
UN RESEAU
D’EXCELLENCE
…et tant d’autres!
© 2013 IBM Corporation
Find the slides on:
www.republic-of-innovation.ch
Dr. Benoit Dubuis Fondation Eclosion 14, Ch. Des Aulx CH-1228 Plan-les-Ouates Tel 022 880 10 10 [email protected]