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
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
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
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
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
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
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.