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Biomarkers in personalized healthcare,
a changing world
Health Valley Event 2014
13 March 2014
Nijmegen
Head Radboud Center for Proteomics, Glycomics
and Metabolomics
Coordinator Radboud Technology Centers
Head Biomarkers in Personalized Healthcare
Prof Alain van Gool
Mixed perspectives in personalized healthcare
8 years academia (NL, UK)
(molecular mechanisms of disease)
13 years pharma (EU, USA, Asia)
(biomarkers, Omics)
2.5 years applied research institute (NL, EU)
(biomarkers, personalized health)
2.5 years med school (NL)
(Omics, biomarkers, personalized healthcare)
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
2
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Biomarkers in personalized healthcare,
a changing world
• From Personalized Medicine to Personalized Healthcare
• Disruptive technologies
• Need to accelerate the development of useful tools
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Personalized diagnostics in early days
This urine wheel was published
in 1506 by Ullrich Pinder, in his
book Epiphanie Medicorum.
The wheel describes the
possible colors, smells and
tastes of urine, and uses them
to diagnose disease.
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Source: wikipedia
{Kumar and van Gool, RSC, 2013}
Personalized Medicine
Right patient
with right drug
at right dose
at right time
for right outcome
Only part of the biomarker use in pharmaceutical development.
Driven by the need to develop better drugs that work optimal in a selection
of patients, rather than work mediocre in a larger patient group.
Often translated to:
Co-develop (molecular) biomarkers as diagnostic companions of a drug.
In changing world: biomarkers are diagnostic companions of a person.
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Pharmaceutical Companion Diagnostics – some numbers
At present in pharmaceutical development:
40.000 clinical trials ongoing
16.000 trials in oncology
8.000 trials in oncology have a companion diagnostic (many genetic)
At present on market:
113 Biomarker in drug label (2012; up from 69 in 2010 = +64%)
16 CDx testing needed (2012; up from 4 in 2010 = +400%)
Costs of development:
>1.000 MUSD per drug
~10 MUSD per diagnostic
Source: www.fda.gov
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Companion Diagnostics
Metabolism
Efficacy or
safety
Source: www.fda.gov
{Kumar and van Gool, RSC, 2013}
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Clinical efficacy of Vemurafenib (PLX-4032, Zelboraf)
Key biomarkers:
Stratification: BRAFV600E mutation
Mechanism: P-ERK
Cyclin-D1
Efficacy: Ki-67
18FDG-PET, CT
Clinical endpoint: progression-free survival (%)
{Source: Flaherty et al, NEJM 2010}{Source: Chapman et al, NEJM 2011}
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Clinical effects of Vemurafenib
{Wagle et al, 2011, J Clin Oncol 29:3085}
Before Rx Vemurafenib, 15 weeks Vemurafenib, 23 weeks
• Strong initial effects vemurafenib
• Emerging drug resistancy
• Reccurence of aggressive tumors
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Tumor tissue heterogeneity
• BRAFV600D/E is driving mutation
• However, also no BRAFV600D/E
mutation found in regions of a
primary melanoma
• Molecular heterogeneity in
diseased tissue
• Biomarker levels in tissue will
vary
• Biomarker levels in body fluids
will vary
• Major challenge for
(companion) diagnostics
{Source: Yancovitz, PLoS One 2012}
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
‘Complicating’ factors in oncology therapy
Source: 11 Sept 2013 @de Volkskrant
• Biological clock
• Smoking
• Pharma-Nutrition
• Drug-drug interaction
• Alternative medicine
• Genetic factors
• …
Interview with Prof Ron Matthijssen, ErasmusMC, Rotterdam
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Changing world: Personalized Medicine@ USA
“The term "personalized medicine" is
often described as providing "the
right patient with the right drug at
the right dose at the right time."
More broadly, "personalized
medicine" may be thought of as the
tailoring of medical treatment to the
individual characteristics, needs, and
preferences of a patient during all
stages of care, including prevention,
diagnosis, treatment, and follow-up.”
(FDA, 1 nov 2013)
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Changing world: Personalized Medicine@ EU
(ESF, 30 Nov 2012) (IMI2, 8 July 2013) (EC, draft Nov 2013)
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Emerging: Personalized Healthcare in a systems view
Source: Barabási 2007 NEJM 357; 4}
• People are different
• Different networks and influences
• Different risk factors
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Personalized Healthcare in a systems view
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Personalized Healthcare in a systems view
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Patient participation
and empowerment
included !!
Radboud Personalized Healthcare
Stratification by multilevel diagnosis
Exchange experiences in
care communities
+
Patient’s preference of treatment
People are different
Select personalized therapy
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
System biology model for Personalized Health(care)
(a.k.a. Next Generation Life Sciences)
HomeostasisAllostasisDisease
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)
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Example System-based Personalized Healthcare
{Chen et al, Cell 2012, 148: 1293}
Concept:
• Continuous monitoring (n=1)
• Routine biomarkers to alert
• Omics to explain
• Early intervention
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
The big current bottleneck in Next Generation Life Sciences:
(Big) data
Knowledge
Understanding
Decision
Action
Translation !
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Systems view on metabolic health and disease
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
β-cell Pathology
gluc Risk factor
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
{Source: Ben van Ommen, TNO}
therapy
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
EC DG for Research and Innovation
Alain van Gool
Brussels, 11 Sept 2012
Relating tissue pharmacology – biomarker - therapy
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Translating knowledge to field labs
• Implementation-plan ‘personalized diagnosis of
(pre)diabetic and their lifestyle treatment in
Dutch Health care’.
• Use of OGTT as a stratification biomarker for
subgroups of (pre)diabetic patients
• Use diagnosis for a tailored lifestyle
(and medical) treatment
for these subgroups
Being implemented in
1st line care
regio Hillegom
Alliance “Expedition Sustainable Care,
starting with diabetes”
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Pharma-Nutrition potential
Effect
Dose
Horizon2020 consortium, call PHC-13
Higher efficacy / less side effects
However …
The world is changing and doesn’t wait for
scientific rigor to catch up
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Next Generation Life Sciences in USA
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Singularity University’s FutureMed 2013 speakers
Exponential
technologies
Digital
medicine
Integrated
care
Artifical
intelligence
Robotics
Patients
included
Lifestyle
Self
quantification
Global
health
WatsonArtifical
intelligence
Regenerative
medicine
23andme
Robotics
and Jamie Heywood (Patientslikeme)
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Singularity University’s FutureMed 2013 conference
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Exponential progress
“The only constant is change,
and the rate of change is
increasing”
We are at the knee
of the exponential curve
of progress
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
1. Imaging of every part of human body in high resolution
2. Smartphone as the most important pieve of clothing
3. Self-diagnosis as a continous monitoring to quantified self
4. Artifical intelligence and robots
5. Digital medicine, Big Data and wisdom of the crowd
6. Our body as a lego box using 3D printing for spare parts
7. Our brain online using brainsensing headbands to transfer thoughts
Exponential trends
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Digital medicine
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Self-diagnosis
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
The future is nearly there …
Personalized advice
Action
Selfmonitor
Cloud
Lifestyle
Nutrition
Pharma
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Big Data
Exponential health(care) technologies
• IBM Watson
• AI system on top of recorded medical data + connected to Big Data clouds
• Independent data-driven clinical diagnosis with very high accuracy
• Artifical intelligence
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
3 days high speed innovation in one slide
• Buzzwords:
• Exponential technologies
• Disruptive innovation
• Progress and beyond
• Digital quantified self
• Focus on:
• Where will we be in 5-20 years?
• Technologies, genomics, robotics, Big Data, eHealth, patient empowerment
• Less focus on:
• What to do next year?
• Biomarkers, robustness assays for decision, translating data to knowledge,
innovation in clinical drug testing
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
However …
Knowledge and Innovation gap:
1. What to measure?
2. How much should it change?
3. What should be the follow-up for me?
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
A problem in biomarker land
Imbalance between biomarker discovery and application.
• Gap 1: Strong focus on discovery of new biomarkers, few biomarkers progress
beyond initial publication to multi-center clinical validation.
• Gap 2: Insufficient demonstrated added value of new clinical biomarker and
limited development of a commercially viable diagnostic biomarker test.
Discovery Clinical
validation/confirmation
Diagnostic
test
Number of
biomarkers
Gap 1
Gap 2
The innovation gap in biomarker
research & development
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Some numbers
Data obtained from Thomson Reuters Integrity Biomarker Module
(April 2013)
Alzheimer’s Disease
Chronic Obstructive
Pulmonary Disease
Type II Diabetes
Mellitis
Eg Biomarkers in time: Prostate cancer
May 2011: 2,231 biomarkers
Nov 2012: 6,562 biomarkers
Oct 2013: 8,358 biomarkers
24 Feb 2014: 9,240 biomarkers with
28,538 biomarker uses
EU: CE marking
USA: LDT, 510(k), PMA
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Reasons for biomarker innovation gap
• Not one integrated pipeline of biomarker R&D
• Publication pressure towards high impact papers
• Lack of interest and funding for confirmatory biomarker studies
• Hard to organize multi-lab studies
• Biology is complex on organism level
• Data cannot be reproduced
• Bias towards extreme results
• Biomarker variability
• …
{Source: John Ioannidis, JAMA 2011} {Source: Khusru Asadullah, Nat Rev Drug Disc 2011}
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
“It is simply no longer possible to believe much of the clinical
research that is published, or to rely on the judgment of trusted
physicians or authoritative medical guidelines.
I take no pleasure in this conclusion, which I reached slowly and
reluctantly over my two decades as an editor of The New
England Journal of Medicine.”
Marcia Angell, MD
Former Editor-in-Chief NEJM
Oct 2010
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Shared biomarker development through open innovation
Needed: open innovation network to join forces in:
1. Assay development of (diagnostic) biomarkers
2. Clinical biomarker quantification/validation/confirmation
Shared knowledge,
technologies and objectives
through public-private partnerships (national, European, world-wide)
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Biomarker Development Center (Netherlands)
STW perspectief grant
Biomarker Development Center
Public-private partnership 4 years
Project grant 4.3M Eur of which 2.2M government,
and 2.1M industry (0.9M cash/1.2M kind)
Close interactions with:
- Clinicians (biomarker application)
- Industry
- Patient stakeholder associations
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Translational medicine @ Radboudumc
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Radboudumc Technology Centers
Genomics
Bioinformatics Preclinical
therapies
Flow
cytometry
Translational
neuroscience
Novel concepts
in surgery
Imaging
Microscopy
Biobank
Data
stewardship
Proteomics
Glycomics
Metabolomics
Radboudumc
Technology
Centers
GMP products
Clinical
trials
(February 2014)
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Example: cross-technology diagnostics development
• 12 families with liver disease and dilated cardiomyopathy (5-20 years)
• Initial clinical assessment didn’t yield clear cause of symptoms
• Specific sugar loss of serum transferrin identified via glycoproteomics
ChipCube-LC- Q-tof MS
• Outcome 1: Explanation of disease
• Outcome 2: Dietary intervention as succesful personalized therapy
• Outcome 3: Glycoprofile transferrin applied as diagnostic test
• Genetic defect in glycosylation enzyme (PGM1) identified via exome sequencing
{Tegtmeyer et al, NEJM 370;6: 533 (2014)}
Genomics Glycomics Metabolomics
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Personalized Healthcare
Ways forward:
• Patients included
• Participation + collaboration
• Selfmonitoring
• Personal profiles
• System biology
• (Big) Data sharing
• Personal preferences
• Personalized therapies
• Lifestyle + Nutrition + Pharma
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Acknowledgements
Jan van der Greef
Ben van Ommen
Peter van Dijken
Bas Kremer
Marijana Radonjic
Thomas Kelder
Robert Kleemann
Suzan Wopereis
Ton Rullmann
Lars Verschuren
William van Dongen
and others
Andrea Evers
Lucien Engelen
Jan Kremer
Paul Smits
Maroeska Rovers
Nathalie Bovy
Ron Wevers
Jolein Gloerich
Hans Wessels
Dirk Lefeber
Leo Kluijtmans
and others
Lutgarde Buydens
Jasper Engel
Jeroen Jansen
Geert Postma
and others
Members of the
Radboud umc Personalized Healthcare Taskforce (2013)
Radboud umc Technology Centers (2014)
alain.vangool@tno.nl
alain.vangool@radboudumc.nl
www.linkedIn.com
Many external collaborators
Health Valley Event 2014
Nijmegen
13 March 2014
Alain van Gool
Year 1
Applying lessons learned across fields
e.g. System Biology @TNO
Year 2
Year 3

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Health Valley Event 2014: Alain van Gool, Radboudumc

  • 1. Biomarkers in personalized healthcare, a changing world Health Valley Event 2014 13 March 2014 Nijmegen Head Radboud Center for Proteomics, Glycomics and Metabolomics Coordinator Radboud Technology Centers Head Biomarkers in Personalized Healthcare Prof Alain van Gool
  • 2. Mixed perspectives in personalized healthcare 8 years academia (NL, UK) (molecular mechanisms of disease) 13 years pharma (EU, USA, Asia) (biomarkers, Omics) 2.5 years applied research institute (NL, EU) (biomarkers, personalized health) 2.5 years med school (NL) (Omics, biomarkers, personalized healthcare) 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 2 Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 3. Biomarkers in personalized healthcare, a changing world • From Personalized Medicine to Personalized Healthcare • Disruptive technologies • Need to accelerate the development of useful tools Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 4. Personalized diagnostics in early days This urine wheel was published in 1506 by Ullrich Pinder, in his book Epiphanie Medicorum. The wheel describes the possible colors, smells and tastes of urine, and uses them to diagnose disease. Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool Source: wikipedia {Kumar and van Gool, RSC, 2013}
  • 5. Personalized Medicine Right patient with right drug at right dose at right time for right outcome Only part of the biomarker use in pharmaceutical development. Driven by the need to develop better drugs that work optimal in a selection of patients, rather than work mediocre in a larger patient group. Often translated to: Co-develop (molecular) biomarkers as diagnostic companions of a drug. In changing world: biomarkers are diagnostic companions of a person. Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 6. Pharmaceutical Companion Diagnostics – some numbers At present in pharmaceutical development: 40.000 clinical trials ongoing 16.000 trials in oncology 8.000 trials in oncology have a companion diagnostic (many genetic) At present on market: 113 Biomarker in drug label (2012; up from 69 in 2010 = +64%) 16 CDx testing needed (2012; up from 4 in 2010 = +400%) Costs of development: >1.000 MUSD per drug ~10 MUSD per diagnostic Source: www.fda.gov Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 7. Companion Diagnostics Metabolism Efficacy or safety Source: www.fda.gov {Kumar and van Gool, RSC, 2013} Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 8. Clinical efficacy of Vemurafenib (PLX-4032, Zelboraf) Key biomarkers: Stratification: BRAFV600E mutation Mechanism: P-ERK Cyclin-D1 Efficacy: Ki-67 18FDG-PET, CT Clinical endpoint: progression-free survival (%) {Source: Flaherty et al, NEJM 2010}{Source: Chapman et al, NEJM 2011} Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 9. Clinical effects of Vemurafenib {Wagle et al, 2011, J Clin Oncol 29:3085} Before Rx Vemurafenib, 15 weeks Vemurafenib, 23 weeks • Strong initial effects vemurafenib • Emerging drug resistancy • Reccurence of aggressive tumors Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 10. Tumor tissue heterogeneity • BRAFV600D/E is driving mutation • However, also no BRAFV600D/E mutation found in regions of a primary melanoma • Molecular heterogeneity in diseased tissue • Biomarker levels in tissue will vary • Biomarker levels in body fluids will vary • Major challenge for (companion) diagnostics {Source: Yancovitz, PLoS One 2012} Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 11. ‘Complicating’ factors in oncology therapy Source: 11 Sept 2013 @de Volkskrant • Biological clock • Smoking • Pharma-Nutrition • Drug-drug interaction • Alternative medicine • Genetic factors • … Interview with Prof Ron Matthijssen, ErasmusMC, Rotterdam Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 12. Changing world: Personalized Medicine@ USA “The term "personalized medicine" is often described as providing "the right patient with the right drug at the right dose at the right time." More broadly, "personalized medicine" may be thought of as the tailoring of medical treatment to the individual characteristics, needs, and preferences of a patient during all stages of care, including prevention, diagnosis, treatment, and follow-up.” (FDA, 1 nov 2013) Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 13. Changing world: Personalized Medicine@ EU (ESF, 30 Nov 2012) (IMI2, 8 July 2013) (EC, draft Nov 2013) Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 14. Emerging: Personalized Healthcare in a systems view Source: Barabási 2007 NEJM 357; 4} • People are different • Different networks and influences • Different risk factors Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 15. Personalized Healthcare in a systems view Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 16. Personalized Healthcare in a systems view Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool Patient participation and empowerment included !!
  • 17. Radboud Personalized Healthcare Stratification by multilevel diagnosis Exchange experiences in care communities + Patient’s preference of treatment People are different Select personalized therapy Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 18. System biology model for Personalized Health(care) (a.k.a. Next Generation Life Sciences) HomeostasisAllostasisDisease 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) Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 19. Example System-based Personalized Healthcare {Chen et al, Cell 2012, 148: 1293} Concept: • Continuous monitoring (n=1) • Routine biomarkers to alert • Omics to explain • Early intervention Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 20. The big current bottleneck in Next Generation Life Sciences: (Big) data Knowledge Understanding Decision Action Translation ! Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 21. Systems view on metabolic health and disease 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 β-cell Pathology gluc Risk factor 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 {Source: Ben van Ommen, TNO} therapy Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 22. EC DG for Research and Innovation Alain van Gool Brussels, 11 Sept 2012 Relating tissue pharmacology – biomarker - therapy Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 23. Translating knowledge to field labs • Implementation-plan ‘personalized diagnosis of (pre)diabetic and their lifestyle treatment in Dutch Health care’. • Use of OGTT as a stratification biomarker for subgroups of (pre)diabetic patients • Use diagnosis for a tailored lifestyle (and medical) treatment for these subgroups Being implemented in 1st line care regio Hillegom Alliance “Expedition Sustainable Care, starting with diabetes” Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 24. Pharma-Nutrition potential Effect Dose Horizon2020 consortium, call PHC-13 Higher efficacy / less side effects
  • 25. However … The world is changing and doesn’t wait for scientific rigor to catch up Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 26. Next Generation Life Sciences in USA Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 27. Singularity University’s FutureMed 2013 speakers Exponential technologies Digital medicine Integrated care Artifical intelligence Robotics Patients included Lifestyle Self quantification Global health WatsonArtifical intelligence Regenerative medicine 23andme Robotics and Jamie Heywood (Patientslikeme) Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 28. Singularity University’s FutureMed 2013 conference Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 29. Exponential progress “The only constant is change, and the rate of change is increasing” We are at the knee of the exponential curve of progress Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 30. 1. Imaging of every part of human body in high resolution 2. Smartphone as the most important pieve of clothing 3. Self-diagnosis as a continous monitoring to quantified self 4. Artifical intelligence and robots 5. Digital medicine, Big Data and wisdom of the crowd 6. Our body as a lego box using 3D printing for spare parts 7. Our brain online using brainsensing headbands to transfer thoughts Exponential trends Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 31. Digital medicine Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 32. Self-diagnosis Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 33. The future is nearly there … Personalized advice Action Selfmonitor Cloud Lifestyle Nutrition Pharma Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 35. Exponential health(care) technologies • IBM Watson • AI system on top of recorded medical data + connected to Big Data clouds • Independent data-driven clinical diagnosis with very high accuracy • Artifical intelligence Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 36. Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 37. 3 days high speed innovation in one slide • Buzzwords: • Exponential technologies • Disruptive innovation • Progress and beyond • Digital quantified self • Focus on: • Where will we be in 5-20 years? • Technologies, genomics, robotics, Big Data, eHealth, patient empowerment • Less focus on: • What to do next year? • Biomarkers, robustness assays for decision, translating data to knowledge, innovation in clinical drug testing Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 38. However … Knowledge and Innovation gap: 1. What to measure? 2. How much should it change? 3. What should be the follow-up for me? Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 39. A problem in biomarker land Imbalance between biomarker discovery and application. • Gap 1: Strong focus on discovery of new biomarkers, few biomarkers progress beyond initial publication to multi-center clinical validation. • Gap 2: Insufficient demonstrated added value of new clinical biomarker and limited development of a commercially viable diagnostic biomarker test. Discovery Clinical validation/confirmation Diagnostic test Number of biomarkers Gap 1 Gap 2 The innovation gap in biomarker research & development Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 40. Some numbers Data obtained from Thomson Reuters Integrity Biomarker Module (April 2013) Alzheimer’s Disease Chronic Obstructive Pulmonary Disease Type II Diabetes Mellitis Eg Biomarkers in time: Prostate cancer May 2011: 2,231 biomarkers Nov 2012: 6,562 biomarkers Oct 2013: 8,358 biomarkers 24 Feb 2014: 9,240 biomarkers with 28,538 biomarker uses EU: CE marking USA: LDT, 510(k), PMA Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 41. Reasons for biomarker innovation gap • Not one integrated pipeline of biomarker R&D • Publication pressure towards high impact papers • Lack of interest and funding for confirmatory biomarker studies • Hard to organize multi-lab studies • Biology is complex on organism level • Data cannot be reproduced • Bias towards extreme results • Biomarker variability • … {Source: John Ioannidis, JAMA 2011} {Source: Khusru Asadullah, Nat Rev Drug Disc 2011} Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 42. “It is simply no longer possible to believe much of the clinical research that is published, or to rely on the judgment of trusted physicians or authoritative medical guidelines. I take no pleasure in this conclusion, which I reached slowly and reluctantly over my two decades as an editor of The New England Journal of Medicine.” Marcia Angell, MD Former Editor-in-Chief NEJM Oct 2010 Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 43. Shared biomarker development through open innovation Needed: open innovation network to join forces in: 1. Assay development of (diagnostic) biomarkers 2. Clinical biomarker quantification/validation/confirmation Shared knowledge, technologies and objectives through public-private partnerships (national, European, world-wide) Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 44. Biomarker Development Center (Netherlands) STW perspectief grant Biomarker Development Center Public-private partnership 4 years Project grant 4.3M Eur of which 2.2M government, and 2.1M industry (0.9M cash/1.2M kind) Close interactions with: - Clinicians (biomarker application) - Industry - Patient stakeholder associations Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 45. Translational medicine @ Radboudumc Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 46. Radboudumc Technology Centers Genomics Bioinformatics Preclinical therapies Flow cytometry Translational neuroscience Novel concepts in surgery Imaging Microscopy Biobank Data stewardship Proteomics Glycomics Metabolomics Radboudumc Technology Centers GMP products Clinical trials (February 2014) Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 47. Example: cross-technology diagnostics development • 12 families with liver disease and dilated cardiomyopathy (5-20 years) • Initial clinical assessment didn’t yield clear cause of symptoms • Specific sugar loss of serum transferrin identified via glycoproteomics ChipCube-LC- Q-tof MS • Outcome 1: Explanation of disease • Outcome 2: Dietary intervention as succesful personalized therapy • Outcome 3: Glycoprofile transferrin applied as diagnostic test • Genetic defect in glycosylation enzyme (PGM1) identified via exome sequencing {Tegtmeyer et al, NEJM 370;6: 533 (2014)} Genomics Glycomics Metabolomics Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 48. Personalized Healthcare Ways forward: • Patients included • Participation + collaboration • Selfmonitoring • Personal profiles • System biology • (Big) Data sharing • Personal preferences • Personalized therapies • Lifestyle + Nutrition + Pharma Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 49. Acknowledgements Jan van der Greef Ben van Ommen Peter van Dijken Bas Kremer Marijana Radonjic Thomas Kelder Robert Kleemann Suzan Wopereis Ton Rullmann Lars Verschuren William van Dongen and others Andrea Evers Lucien Engelen Jan Kremer Paul Smits Maroeska Rovers Nathalie Bovy Ron Wevers Jolein Gloerich Hans Wessels Dirk Lefeber Leo Kluijtmans and others Lutgarde Buydens Jasper Engel Jeroen Jansen Geert Postma and others Members of the Radboud umc Personalized Healthcare Taskforce (2013) Radboud umc Technology Centers (2014) alain.vangool@tno.nl alain.vangool@radboudumc.nl www.linkedIn.com Many external collaborators Health Valley Event 2014 Nijmegen 13 March 2014 Alain van Gool
  • 50.
  • 51. Year 1 Applying lessons learned across fields e.g. System Biology @TNO Year 2 Year 3

Editor's Notes

  1. Integrating metabolic parameters with psychological parameters. Diabetes is mainly viewed as a metabolic disease. It becomes increasingly apparent that psychological aspects play a crucial role.