2016-02-18 innovation for health 2016 conference, rotterdam alain van gool
TRANSCRIPT
Personalized Health(care): more than ‘just’ targeted medicines
Professor of Personalized Healthcare Head Radboud Center for Proteomics, Glycomics and Metabolomics Coordinator Radboud Technology Centers
Senior Scientist Integrator Biomarkers
Prof Alain van Gool
Innovation for Health Rotterdam, 18 Feb 2016
My background in personalized health(care)
8 years academia (NL, UK)
(molecular mechanisms of disease)
13 years pharma (EU, USA, Asia)
(biomarkers, Omics)
4 years med school (NL)
(personalized healthcare, Omics, biomarkers)
4 years applied research institute (NL, EU)
(biomarkers, personalized health, nutrition)
1991-1996 (PhD)
1996-1998 (post-doc)
2009-2012 (visiting prof)
1999-2007 2007-2009 2009-2011
2011-now
2011-now (prof)
2
A person / citizen / family man (adventures in EU, USA, Asia)
Alain van Gool, Innovation for Health, 18 Feb 2016
2016 (Scientific lead DTL-Technologies)
2016 (Head Biomarker Platform)
Source: Chakma, Journal of Young Investigators, 16, 2009
Principle of Personalized/Precision/Targeted Medicine
4
• The right drug for right patient at right dose at right time • Molecular biomarkers as key drivers of patient selection
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Emerging Personalized / Precision / Targeted Medicine
Good examples personalized medicine in Oncology and Neurosciences:
• Her2/neu, BRCA, BRAF, EGFR, EML4/ALK, Cyp450, etc
Emerging companion diagnostics, also linked to non-drug therapies:
• Volker: Intestinal surgery → XIAP → Cord blood
• Beery twins: Cerebral palsy → SPR → Diet 5HTP
• Wartman: Leukemia → FLT3 → Sunitinib
• Gilbert: Healthy → BRCA → Mas/Ovarectomy
• Snyder: T2Diabetes → GCKR, KCNJ11 → Diet, exercise
• Lauerman: Scotoma, leg → JAK2 → Aspirin
• Bradfield: Healthy → CDH1 → Gastrectomy
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Moving to Personalized Health(care)
{Source: Barabási 2007 NEJM 357; 4}
• People are different • Different risk factors (molecule, system, environment) • Different preferences • Shared desire not to get ill at all !
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3 key aspects of personalized health(care)
‘I want to stay healthy. If not, how do I get healthy?’
1. What to measure?
2. How much can it change?
3. What should be the follow-up for me?
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1. What to measure?
Exponential technological developments • Next generation sequencing
• DNA, RNA
• Risk analysis and therapy selection
• Mass spectrometry • Proteins, metabolites • Monitoring of disease and treatment effects
• Imaging • Non invasive images, real time • Spatial view of intact organs and organisms
500
1000
1500
2000
m/z
5 10 15 20 25 30 35 40 Time [min]
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3 key aspects of personalized health(care)
‘I want to stay healthy. If not, how do I get healthy?’
1. What to measure?
2. How much can it change?
3. What should be the follow-up for me?
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healthy disease disease + treatment
2. How much can it change?
Subgroups
100%
Individual
Population
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Personalized health(care) model Personalized Intervention
of patients-like-me Personal thresholds of persons-like-me
Big Biomarker Data
Molecular Non-molecular Environment …
Ho
meo
sta
sis
A
llo
sta
sis
D
isease
Time
Disease
Health
Selfmonitoring
Adapted from Jan van der Greef, TNO
Personal profile
Personalized health
Personalized medicine
{See eg Chen … Snyder, Cell 2012, 148: 1293}
16 Alain van Gool, Innovation for Health, 18 Feb 2016
3 key aspects of personalized health(care)
‘I want to stay healthy. If not, how do I get healthy?’
1. What to measure?
2. How much can it change?
3. What should be the follow-up for me?
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3. What should be the follow-up for me?
Personal profile data
Knowledge
Understanding
Decision
Action
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Translation is key in Personalized Healthcare !
“I’m afraid you’re
suffering from an
increased IL-1β and
an aberrant miR843
expression”
Adapted from:
?
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Lab values Clinical outcomes
Pain Mobility Fatigue
INTEGRATE-HTA {R van Hoorn, W Kievit, M Tummers, GJ van der Wilt}
Intervention
Participatory healthcare
Shared decision making
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EC DG for Research and Innovation
Alain van Gool
Brussels, 11 Sept 2012
Field lab testing
Booth #15
? Effect drugs on individual driving skills
→ TNO moving base driving simulator
{Marike Hoedemaeker, Steven Erpelinck}
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EC DG for Research and Innovation
Alain van Gool
Brussels, 11 Sept 2012
Personalized Nutrition and Health Research
Program
For a society in which
each individual can and
wants to make a
motivated and sustainable
choice for a healthy diet
and lifestyle.
(pre-competitive public-private
innovation program)
{Nard Clabbers}
Booth #15
However … quality of data !?!
• Extremely important for personalized healthcare model
• Lack of reproducibility of reported studies
• Bayer – 75% NOT reproducible (n = 67)
• Amgen – 89% NOT reproducible (n = 53)
• Quality of data needs to be improved in:
• Data capture
• Data stewardship (FAIR)
{Prinz, Nat Rev Drug Disc, 2011}
{Bengley, Nature, 2012}
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Biomarker innovation gaps
Discovery Clinical
validation/confirmation
Diagnostic
test
Number of
biomarkers
Gap 1
Gap 2
Gap 3
• Too much science-focussed biomarker discovery • Too little development to application
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Biomarker innovation gaps
Test, interpret, advice
“Post-traumatic Test Syndrome” ?
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Build biomarker validation pipelines
Standardisation, harmonisation, knowledge sharing in:
1. Assay development
2. Clinical validation
NL Roadmap Molecular Diagnostics (2012) NL Grant 4.3M Eur (2014)
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Ongoing independent biomarker activities
27
Europe
USA
{Asadullah et al, Nature Reviews Drug Discovery, Dec 2015}
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The Good Biomarker Practice initiative
Join forces among Europe’s major academic infrastructures + industry to:
1. Establish “Good Biomarker Practice” guidelines
- on translational research, biomarker technologies, biobanking, data stewardship.
2. Efficiently execute high quality biomarker projects
- work together in clinical validation and development of probable biomarkers.
EU
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HEALTH-RI: ENABLING PERSONALISED HEALTH RESEARCH
Agro
Biomedical
Design of multi-
disciplinary experiments
Information & Insight
e-health & quantified self data
Model systems
measure genotype & phenotype e.g. genomics, transcriptomics, proteomics,
metabolomics, bioimaging, microscopy, quantified self, lifestyle, nutritional studies
data design, analytics & stewardship
e.g. bioinformatics, computer science, biostatistics, computational (systems)
biology, e-science, ICT, …
Biomaterial and data
collections
International reference
data
Linked-(FAIR)-data backbone for distributed analytics & learning
Research project
Health objective
Nutrition & lifestyle
Biomedical & e-health .nl
{See www.dtls.nl}
NL
Acknowledgements
Ron Wevers
Jolein Gloerich
Hans Wessels
Dirk Lefeber
Monique Scherpenzeel
Leo Kluijtmans
Lucien Engelen
Nathalie Bovy
Paul Smits
Maroeska Rovers
Bas Bloem
the Technology Centers
and many others
www.radboudumc.nl/personalizedhealthcare
www.radboudresearchfacilities.nl
www.radboudumc.nl/research/technologycenters
www.linkedIn.com
www.slideshare.net/alainvangool
Many collaborators and funders
Jan van der Greef
Ben van Ommen
Bas Kremer
Lars Verschuren
Ivana Bobeldijk
Marjan van Erk
Carina de Jongh
Peter van Dijken
Peter Wielinga
Robert Kleemann
Suzan Wopereis
and many others
CarTarDis
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