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)
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)
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
Watson Artifical 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)
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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