The document summarizes a keynote presentation on medical revolution and new technologies. It discusses: 1. The challenges facing healthcare including rising costs, aging populations, and chronic diseases. 2. Towards developing an integrated healthcare system with personalized, predictive, and preventative medicine using technologies like remote monitoring, big data analytics, and mobile health. 3. Innovation in areas like genomics, proteomics, bioconvergence, and interdisciplinary collaboration between fields like nanotechnology, materials science, and computing can help address these challenges.

1. 1IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Click to edit Master title style
© 2013 Benoit Dubuis
© 2013 IBM Corporation
Medical revolution and
new technologies
Dr. Benoit Dubuis,
Directeur Eclosion, Président BioAlps
11 juin 2013

2. MEDTECH
“Medical revolution and new technologies”
The challenges
Towards an integrated health system
Our contribution
Innovation: The New Currency of
Competition

3. MEDTECH
“Medical revolution and new technologies”
The challenges
Towards an integrated health system
Our contribution
Innovation: The New Currency of
Competition

4. 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
…

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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%

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P
DEMOGRAPHIE:
NOUS VIVONS PLUS
LONGTEMPS90
80
70
60
50
40
Espérancedevieàlanaissance
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

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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

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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

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COÛT DE LA
SANTE

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LES NOUVELLES
PISTES
Médecine 3P
Pharmacogénomique
Bioconvergence
Médecine Translationnelle
Télémédecine

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DE LA MEDECINE « PRÊT-A PORTER »
à
LA MEDECINE PERSONALISEE
Génomique
Protéomique

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PREVENTIVE
PREDICTIVE
PERSONNALISEE
Modèle comprimant la morbidité
En bonne santé
Années de vie
gagnée Malade
Personnalisé

Mortalité
Préventif

Morbidité
Prédictif

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VERS UN SYSTEME DE
SANTE INTEGRE
Rx
2009

14. 15IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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

15. Crossing Visions
13.06.2013 | 16
LA FORCE
DU
RESEAU
CENTRES
MEDICAUX
OUTILS DE
RECHERCHE
INDUSTRIES
START-UP




CENTRES
ACADEMIQUES

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INNOVATION et
INTERDISCIPLINARITE

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INNOVATION et
INTERDISCIPLINARITE
Biotechnologie,
Systèmes Biologiques
et
Biologie Synthétique
Nanotechnologie
Science des Matériaux
et
Ingénierie de
Miniaturisation
Informatique de
pointe
et
WIRELESS

18. 19IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Interdisciplinarity (science driven)

19. 20IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Interdisciplinarity (science driven)

20. 21IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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

21. 22IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Micro /
nanotech
cluster
Bio-cluster
A unique hub
for Medtech/Biotech R&D in Europe

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INSTITUTIONS
R&D DE CLASSE
INTERNATIONALE
Générer des connaissances
Créer des opportunités

23. Crossing Visions
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QUALITE DES
RECHERCHES
Nombre de publication par 1000 habitants
dans tous les domaines de connaissances et dans le domaine des Sciences de la vie

24. 25IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
'evolutionary developmental biology'
Electronic health record'
ACCES AUX TECHNOLOGIES,
OUTILS ET CONNAISSANCES

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De l’idée au produit
Créer de la valeur économique et des
emplois

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SARAH MARQUIS
CONNECTEE
Coupure de journal
Sarah Marquis…

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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

28. Crossing Visions
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SYSTEME DE
SANTE INTEGRE
0
20
40
60
80
100
Chf 13’800
Chf 5’900
Prédiction
Personnalisation
Suivi à
distance
d’un
Patient

29. 30IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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

30. 31IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Personalized Medicine
Smart Sensing
Intelligent
Information
Management
Effective
Interfaces
Putting the patient at the center of their health system

31. 32IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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

32. 33IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
CSEM: Human vital signs Multiparameter
Sensing
SpO2 / CBT
NIBP
ECGrespiration
HR / HRV CO2 / O2

33. 34IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
GeophysicalExperiment
Walking
Sitting
Donning
Sitting
Walking
DoffingTaking
sample
Fall
• CBT
• HR
• BR
• SpO2
• 3D-ACC
CSEM : LTMS clinical study sample

34. 35IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Intelligent Information Management
Longitudinal data
Personal baseline
Detect trends & deviations from norm
Personal health records
Privacy
Sharing
Anonymous aggregation
Patient-centered decision support

35. 36IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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

36. 37IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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 SolutionsDisease Wireless SolutionsNo. AffectedDisease Wireless Solutions
* Chronic obstructive pulmonary disease
Source: Burrill

37. 38IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
The shift to patient-empowering,
information-leveraging technologies
“PI” (patient-empowering and information-leveraging) technologies

38. 39IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Source: George Poste
Access,
cost and
quality
of care
Molecular
and
personalized
medicine
Proficient
use of
information
(e.health)
Link between Genomic and physiology

39. 40IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Biocorpora –Drugdesigntech SA
Collaborative Drug Discovery
Source:Dr.CédricMerlot,DrugDesignTech
Information matters – Data lifecycle

40. 41IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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
Source:Dr.CédricMerlot,DrugDesignTech

41. 42IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Collaborative Drug Discovery
publication
molecules High troughput
project leaders data analysis labs
in-context
reporting
Biocorpora
proposals CRO
Source:Dr.CédricMerlot,DrugDesignTech

42. 43IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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

43. 44IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
- omics Data Management
Microarray Flow cytometry NMR Mass spectrometry
analysis
project leaders data analysis labs
in-context
reporting
Biocorpora
Source:Dr.CédricMerlot,DrugDesignTech

44. 45IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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
Source:megaclust.vital-it.ch

45. 46IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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
Source:megaclust.vital-it.ch

46. 47IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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
Source:megaclust.vital-it.ch

47. 48IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
Megaclust: Each individual has unique amounts
of each identified cell types (unique fingerprint)
50 individuals
16identifiedcelltypes
Each column represents a patient specific cellular fingerprint
A5
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
cellularfingerprint
Source:megaclust.vital-it.ch

48. 49IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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
Source:megaclust.vital-it.ch

49. 50IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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 phase3preclinical
animals
healthy
volunteers
small group of patients large group of patients
Source:megaclust.vital-it.ch

50. 51IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
IBM BlueGene/L

51. IBM Systems & Technology Group
EPFL / IBM Confidential | 6/13/201352
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

52. 53IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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
Source:Dr.CédricMerlot,DrugDesignTech

53. 54IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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 ?
Source:Dr.CédricMerlot,DrugDesignTech

54. 55IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
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

55. Crossing Visions
13.06.2013 | 56
COMMUNAUTE
INDUSTRIELLE

56. 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

57. 58IBM Technology Day 2013, Keynote B. Dubuis11.6.2013
A Successfull biocluster

58. UN
RESEAU
D’EXCELLENCE
…et tant d’autres!

59. © 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
bd@eclosion.com