2015 05-20 Radboudumc REshape breakfast meeting Alain van Gool
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Biomarkers in Personalized Health(care), moving beyond Targeted Medicine Professor of Personalized Healthcare Head Radboud Center for Proteomics, Glycomics and Metabolomics Coordinator Radboud Technology Centers Head Biomarkers in Personalized Healthcare Prof Alain van Gool 20 May 2015
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Transcript of 2015 05-20 Radboudumc REshape breakfast meeting Alain van Gool
Biomarkers in Personalized Health(care), moving beyond Targeted Medicine
Professor of Personalized Healthcare Head Radboud Center for Proteomics, Glycomics and Metabolomics Coordinator Radboud Technology Centers
Head Biomarkers in Personalized Healthcare
Prof Alain van Gool 20 May 2015
My mixed perspectives in personalized health(care)
8 years academia (NL, UK)
(molecular mechanisms of disease)
13 years pharma (EU, USA, Asia)
(biomarkers, Omics)
3,5 years med school (NL)
(personalized healthcare, Omics, biomarkers)
3,5 years applied research institute (NL, EU)
(biomarkers, personalized health, nutrition)
A person / citizen / family man
(adventures in EU, USA, Asia)
1991-1996 1996-1998 2009-2012
1999-2007 2007-2009 2009-2011
2011-now
2011-now
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2
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3
Consider individual differences in personalized health(care)
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Source: Chakma Journal of Young Investigators. Vol 16, 2009.
Principle of Personalized/Precision/Targeted Medicine
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5
Patient
Radboud Personalized Healthcare
A significant impact
on healthcare
Molecule
Population
Personalized Healthcare @Radboudumc
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Biomarkers
{Biomarkers definition working group, 2001 }
Definition: ‘a characteristic that is objectively measured and evaluated as an
indicator of normal biological processes, pathogenic processes, or
pharmacologic responses to a therapeutic intervention’
Or ‘Whatever works in adding value’
Molecular biomarkers provide a molecular impression of a biological system
(cell, animal, human)
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Genomic Proteomic Metabolomic Imaging
Exponential developments in biomarker technologies
• 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
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www.radboudumc.nl/research/technologycenters
Genomics
Bioinformatics
Animal studies
Stem cells
Translational neuroscience
Image-guided treatment
Imaging
Microscopy
Biobank
Health economics
Mass Spectrometry
Radboudumc Technology
Centers Investigational
products
Clinical trials
EHR-based research
Statistics
Human physiology
Data stewardship
Molecule
Flow cytometry
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EC DG for Research and Innovation
Alain van Gool
Brussels, 11 Sept 2012
System biology in:
Diagnosis Prognosis Treatment Monitoring
People are complex biological systems which requires a systems biology approach
Precision medicine @USA
President Obama State of Union 2015
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Biomarkers in Personalized Health(care) an evolving role
• From only diagnosis
• To Translational Medicine
• To Personalized/Precision/Targeted Medicine
• To Personalized Health(care)
present
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Personalized Health(care), more than pathways only
Source: Barabási 2007 NEJM 357; 4}
• People are different • Different networks and influences • Different risk factors • Different preferences
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‘New’ data
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Personalized Health(care) in a systems view
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System Biology view needed β-cell Pathology
gluc Risk factor
{Source: Ben van Ommen, TNO}
Visceral
adiposity
LDL elevated
Glucose toxicity
Fatty liver
Gut
inflammation
endothelial
inflammation
systemic
Insulin resistance
Systemic
inflammation
Hepatic IR
Adipose IR
Muscle metabolic
inflexibility
adipose
inflammation
Microvascular
damage
Myocardial
infactions
Heart
failure
Cardiac
dysfunction
Brain
disorders
Nephropathy
Atherosclerosis
β-cell failure
High cholesterol
High glucose
Hypertension
dyslipidemia
ectopic
lipid overload
Hepatic
inflammation
Stroke
IBD
fibrosis
Retinopathy
Chronic Stress Disruption
circadian rhythm
Parasympathetic
tone
Sympathetic
arousal
Endorphins Gut
activity
Inflammatory
response
Adrenalin
Heart rate Heart rate
variability
High cortisol
α-amylase
System Biology view needed β-cell Pathology
gluc Risk factor
{Source: Ben van Ommen, TNO}
therapy
Visceral
adiposity
LDL elevated
Glucose toxicity
Fatty liver
Gut
inflammation
endothelial
inflammation
systemic
Insulin resistance
Systemic
inflammation
Hepatic IR
Adipose IR
Muscle metabolic
inflexibility
adipose
inflammation
Microvascular
damage
Myocardial
infactions
Heart
failure
Cardiac
dysfunction
Brain
disorders
Nephropathy
Atherosclerosis
β-cell failure
High cholesterol
High glucose
Hypertension
dyslipidemia
ectopic
lipid overload
Hepatic
inflammation
Stroke
IBD
fibrosis
Retinopathy
Physical inactivity Caloric excess
Chronic Stress Disruption
circadian rhythm
Parasympathetic
tone
Sympathetic
arousal
Worrying
Hurrying
Endorphins Gut
activity Sweet & fat foods
Sleep disturbance
Inflammatory
response
Adrenalin
Fear
Challenge
stress
Heart rate Heart rate
variability
High cortisol
α-amylase
Lipids, alcohol, fructose
Carnitine, choline
Stannols, fibre
Low glycemic index
Epicathechins
Anthocyanins
Soy
Quercetin, Se, Zn, …
Metformin
Vioxx
Salicylate
LXR agonist
Fenofibrate Rosiglitazone
Pioglitazone
Sitagliptin
Glibenclamide
Atorvastatin
Omega3-fatty acids
Pharma
Nutrition Lifestyle
Personalized interventions by Pharma-Nutrition
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Higher efficacy / less side effects
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Goal of Personalized Health(care)
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Source: prof Jan Kremer
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But …
Knowledge and Innovation gap:
1. What to measure?
2. How much can it change?
3. What should be the follow-up for me?
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Biomarker innovation gaps
Discovery Clinical
validation/confirmation
Diagnostic
test
Number of
biomarkers
Gap 1
Gap 2
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Gap 3
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Biomarker innovation gaps: some numbers
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5 biomarkers/
working day
1 biomarker/
1-3 years
1 biomarker/
3-10 years
?
Eg Biomarkers in time: Prostate cancer
May 2011: n= 2,231 biomarkers
Nov 2012: n= 6,562 biomarkers
Oct 2013: n= 8,358 biomarkers
Nov 2014: n= 10,350 biomarkers
Discovery Clinical
validation/confirmation
Diagnostic
test
Number of
biomarkers
Gap 1
Gap 2
Gap 3
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But …
Knowledge and Innovation gap:
1. What to measure?
2. How much can it change?
3. What should be the follow-up for me?
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Personalized Health(care) model
Ho
meo
sta
sis
A
llo
sta
sis
D
isease
Time
Disease
Health
Personalized Intervention
of patients-like-me
Big Data
Risk profiles of persons-like-me
Molecular Non-molecular Environment …
Personal profile
Selfmonitoring
Adapted from Jan van der Greef (2013)
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Personalized Participatory Pre-emptive
But …
Knowledge and Innovation gap:
1. What to measure?
2. How much can it change?
3. What should be the follow-up for me?
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Most important for biomarkers in Personalized Healthcare:
Focus on the end user: the patient
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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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?
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Translation is key in Personalized Healthcare !
Select personalized therapy
Treatment options
Succ
ess
rate
s
Example from Prostate cancer patient guide
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Translation is key in Personalized Healthcare !
Treatment options
Pro’s
Con’s
Select personalized therapy
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Translation is key in Personalized Health(care) !
Personal profile data
Knowledge
Understanding
Decision
Action
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33 Alain van Gool, Pharma-Nutrition 2015, 13 March 2015
Optimal targeted / precision / personalized health(care)
Acknowledgements
Ron Wevers
Jolein Gloerich
Hans Wessels
Monique Scherpenzeel
Dirk Lefeber
Leo Kluijtmans
Lucien Engelen
Paul Smits
Maroeska Rovers
Nathalie Bovy
Bas Bloem
and many others
www.radboudumc.nl/personalizedhealthcare
www.radboudumc.nl/research/technologycenters
www.radboudresearchfacilities.nl
www.linkedIn.com
www.slideshare.net/alainvangool
Many collaborators
Jan van der Greef
Ben van Ommen
Bas Kremer
Lars Verschuren
Ivana Bobeldijk
Marjan van Erk
Carina de Jongh
Peter van Dijken
Robert Kleemann
Suzan Wopereis
and many others
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And funders
CarTarDis
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Biomarker innovation gaps: some numbers
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Data from Thomson Reuters Integrity database, February 2015
Alzheimer’s Disease
Chronic Obstructive
Pulmonary Disease
Type II Diabetes Mellitis
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