Great yearly conference with good speakers and audience.

1. Biomarkers in a changing world
Prof Alain van Gool
Head Radboud Center for Proteomics, Glycomics
and Metabolomics
Coordinator Radboud Technology Centers
Head Biomarkers in Personalized Healthcare

2. Mixed perspectives
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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

3. Biomarkers in a changing world
3
• From Personalized Medicine to Personalized Healthcare
• Disruptive technologies for biomarker R&D
• Need to accelerate the development of useful
biomarkers and tools
9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

4. TNO =
Netherlands Organisation for Applied Scientific Research
Mission = to drive ideas to reach their full market value.
We partner with:
Governmental & regulatory organisations
Universities
Pharma, chemical and food companies
International consortia
Knowledge
development
Knowledge
application
Knowledge
exploitation
Develop
fundamental
knowledge
With
universities
With
partners
With
customers
Embedded in the
market
TNO TNO companies
4

5. TNO
Netherlands Organisation for Applied Scientific Research
Founded in 1932
Non-for-profit research institute
Member of EARTO
~3500 employees
19 sites in Netherlands
+ 18 sites/countries globally
Funding:
• Government (NL)
• Contract research (world)
• Public-private partnerships (world)
7 main themes
www.tno.nl
5

6. TNO in European public-private partnerships
Healthy Living
Defence, Safety & Security
Transport & Mobility
Information Society
Industrial Innovation
Energy
Built Environment
Participation in EU projects:
(Jan 2013)
260 projects (3100 partners)
Roles of TNO:
Technical expertise
Focus on applications
PPP management skills
(in 10% role as coordinator)
32% success rate
(average FP7 is 21%)

7. TNO’s applied biomarker tool box
Widely used preclinical translational models
Pharma, nutrition and chemical industry, academia
Focus on etiology of disease and mechanism of action
Human studies
Experimental medicine through CRO’s
Microdosing
Validated analytical platforms
Metabolomics profiling and targeted analysis, with focus on
lipids, ceramids, cannabinoides
Genomics, transcriptomics, proteomics and imaging through
a wide network of selected partners
Clinical chemistry
Data analysis
Network biology for mechanistic understanding
Multiparameter statistics and chemometrics
PK/PD translational modelling
Comprehensive system dynamics modelling
Biomarker expertise
Best practise strategies and approaches
A wide network with biomarker academia and industry
Metabolic Syndrome
• Atherosclerosis
• Diabetes
• Obesity
• Vascular inflammation
• NASH, fibrosis
7

8. Year 1
Applying lessons learned across fields
e.g. System Biology @TNO
Year 2
Year 3

9. Radboudumc
• Mission: “To have a significant impact on healthcare”
• Strategic focus on Personalized Healthcare
• Core activities:
• Patient care
• Research
• Education
• 11.000 colleagues
• 50 departments
• 3.000 students
• 1.000 beds
• First academic centre outside US to fully implement EPIC

10. Radboud Personalized Healthcare
Stratification by multilevel diagnosis
Exchange experiences in
care communities
+
Patient’s preference of treatment
People are different
10
Select personalized therapy

11. Translational medicine @ Radboudumc

12. Radboudumc Technology Centers
Genomics
Bioinformatics Preclinical
therapies
Flow
cytometry
Translational
neuroscience
Novel concepts
in surgery
Imaging
Microscopy
Biobank
Data
stewardship
Proteomics
Metabolomics
Radboudumc
Technology
Centers
GMP products
Clinical
trials
(February 2014)

13. Biomarkers in a changing world
13
• From Personalized Medicine to Personalized Healthcare
• Disruptive technologies for biomarker R&D
• Need to accelerate the development of useful
biomarkers and tools
9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

14. 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.
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

15. 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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

16. Companion Diagnostics
Metabolism
Efficacy or
safety
Source: www.fda.gov
{Kumar and van Gool, RSC, 2013}
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

17. 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}
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

18. 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
• Drug resistancy
• Reccurence of tumors
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

19. Tumor tissue heterogeneity
20
• 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}
9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

20. ‘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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

21. 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)
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

22. Changing world: Personalized Medicine@ EU
(ESF, 30 Nov 2012) (IMI2, 8 July 2013) (EC, draft Nov 2013)
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

23. Emerging: Personalized Healthcare in a systems view
Source: Barabási 2007 NEJM 357; 4}
• People are different
• Different networks and influences
• Different risk factors
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

24. Personalized Healthcare in a systems view
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

25. 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)
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

26. Example personal profile-based healthcare
{Chen et al, Cell 2012, 148: 1293}
Concept:
• Continuous monitoring (n=1)
• Routine biomarkers to alert
• Omics to explain
• Early intervention
27

27. The big current bottleneck in Next Generation Life Sciences:
28
(Big) data
Knowledge
Understanding
Decision
Action
Translation !
9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

28. 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
Systems view on metabolic health and disease
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}

29. EC DG for Research and Innovation
Alain van Gool
Brussels, 11 Sept 2012
Important processes in
T2D
Diagnosis Potential interventions
Dietary/Lifestyle Pharma
1.Pancreatic β-cell function
(impaired insulin secretion)
*OGTT: I/ΔG and DI(0)
*PYY, Arg, His, Phe, Val, Leu
Lifestyle; β-cell
protective nutrients
(MUFA/isoflavonoids);
β -cell protective
medication (TZDs,
GLP-1 analogs,
DPP4-inhibitors)
2.Muscle insulin resistance
(decreased glucose uptake)
*OGTT: Muscle insulin resistance index,
Insulin secretion/insulin resistance index
*Val, Ile, Leu, Gamma-glutamylderivates,
Tyr, Phe, Met
PUFA/SFA balance;
Physical activity;
Weight loss;
TZDs (e.g.PPARγ)
3.Hepatic insulin resistance
(decreased glucose uptake and
increased hepatic glucose
production-HGP)
*Hepatic insulin resistance index *OGTT:
Hepatic insulin sensitivity index
*ALAT, ASAT, bilirubine, GGT, ALP, ck-18
fragments, lactate, α-hydroxybutyrate,
β-hydroxybutyrate
Decrease SFA and n-
6 PUFA, and increase
n-3 PUFA;
Weight loss;
Metformin;
TZDs;
Exenatide (GLP-1
analog);
DPP4 inhibitors
4. Adipocyte insulin resistance
and lipotoxicity
*basal adipocyte insulin resistance index
*FFA platform, glycerol
α-lipoic acid;
PUFA/SFA balance;
Omega 3 fatty acids;
Chitosan/plantsterols;
TZDs; Acipimox
5. GI tract (incretin
deficiency/resistance)
*ivGTT vs OGTT
*GLP-1, GIP, glucagon, galzuren
MUFA; Dietary fibre
(pasta/rye bread);
Exenatide
6. Pancreatic α-cell
(hyperglucagonemia)
*fasting plasma glucagon ? Glucagon receptor
antagonists;
Exenatide;
DPP4 inhibitors
7A.Chronic low-grade
inflammation in pancreas,
muscle, liver, adipose tissue,
hypothalamus
7B. Vascular inflammation
*CRP, total leucocytes
* V-CAM, I-CAM, Oxylipids, cytokines
Fish oil/n-3 fatty
acids; Vit. C/Vit.
E/Carotenoids;
Salicylates; TNF-α
inhibitors and others
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

30. Field labs: implementation in 1st line health care
• 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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

31. Pharma-Nutrition
Effect
Dose
Currently consortium building in Horizon2020, call PHC-13
Coordinator Bas Kremer (bas.kremer@tno.nl)

32. However …
33
The world is changing and doesn’t wait for
scientific rigor to catch up
9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

33. Learn from Next Generation Life Sciences in USA
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

34. 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)
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

35. Singularity University’s FutureMed 2013 conference
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

36. 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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

37. 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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

38. Digital medicine
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

39. Self-diagnosis
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

40. The future is nearly there …
41
Personalized advice
Action
Selfmonitor
Cloud
Lifestyle
Nutrition
Pharma
9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

41. Big Data

42. 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
43
9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

43. 44
9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

44. 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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

45. 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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

46. 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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

47. 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}
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

48. “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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

49. Shared biomarker research through open innovation
We need to set up a open innovation network to share biomarker
knowledge and expertise to jointly develop and validate biomarkers :
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)
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

50. 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
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

51. Personalized healthcare
Ways forward:
• Participation + collaboration
• Selfmonitoring
• Personal profiles
• System biology
• (Big) Data sharing
• Personal preferences
• Personalized therapies
• Lifestyle + Nutrition + Pharma
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool

52. Acknowledgements
Jan van der Greef
Ben van Ommen
Peter van Dijken
Ton Rullmann
Lars Verschuren
Bas Kremer
Marijana Radonjic
Thomas Kelder
Robert Kleemann
Suzan Wopereis
William van Dongen
and others
Ron Wevers
Jolein Gloerich
Hans Wessels
Dirk Lefeber
Monique Scherpenzeel
Leo Kluijtmans
Udo Engelke
Ulrich Brandt
Lucien Engelen
and others
Lutgarde Buydens
Jasper Engel
Lionel Blanchet
Jeroen Jansen
and others
Radboud umc Personalized Healthcare Taskforce:
Paul Smits, Andrea Evers, Alain van Gool, Maroeska Rovers,
Joris Veltman, Jan Kremer, Bas Bloem, Jack Schalken, Gerdi
Egberink, Nathalie Bovy, Bob de Jonge, Viola Peulen, Marcel
Wortel, Martijn Hoogboom, Martijn Gerretsen
alain.vangool@tno.nl
alain.vangool@radboudumc.nl
www.linkedIn.com
And external collaborators
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9th Annual Biomarker Congress
Oxford Global, Manchester
25th February 2014
Alain van Gool