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2014 07-08 Selectbio Biomarkers 2014, Cambridge

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Closing lecture at the CNS biomarker conference.

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2014 07-08 Selectbio Biomarkers 2014, Cambridge

  1. 1. Biomarkers in personalized health(care), from discovery to clinical diagnostics Head Radboud Center for Proteomics, Glycomics and Metabolomics Coordinator Radboud Technology Centers Head Biomarkers in Personalized Healthcare Prof Alain van Gool
  2. 2. Biomarkers in personalized health(care), from discovery to clinical diagnostics Head Radboud Center for Proteomics, Glycomics and Metabolomics Coordinator Radboud Technology Centers Head Biomarkers in Personalized Healthcare Prof Alain van Gool
  3. 3. Mixed perspectives in personalized health(care) 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 4 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  4. 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 Triskelion 5 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  5. 5. TNO Facts &Figures: Founded in 1932 Member of EARTO Non-for-profit research institute ~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 6 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  6. 6. TNO’s research themes 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%) (nutrition, pharma, lifestyle) SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  7. 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 8 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  8. 8. Year 1 Applying lessons learned across fields e.g. System Biology @TNO Year 2 Year 3 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  9. 9. Radboudumc • Mission: “To have a significant impact on healthcare” • Strategic focus on Personalized Healthcare • Core activities: • Patient care • Research • Education • 11.000 colleagues • 52 departments • 3.300 students • 1.000 beds • First academic centre outside US to fully implement EPIC SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  10. 10. Implementing Personalized Healthcare Stratification by multilevel diagnosis Exchange experiences in care communities + Patient’s preference of treatment People are different 11 Select personalized therapy SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  11. 11. Translational medicine @ Radboudumc SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  12. 12. Radboudumc Technology Centers Genomics Bioinformatics Animal studies Flow cytometry Translational neuroscience Novel concepts in surgery Imaging Microscopy Biobank Data stewardship Mass Spectrometry Radboudumc Technology Centers GMP products Clinical trials (June 2014) SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  13. 13. Radboudumc Technology Centers • Proteins • Metabolites • Preclinical • Clinical • Behavioural • Animal facility • Systematic review • Cell analysis • Sorting • Pediatric • Adult • Phase 1, 2, 3, 4 • Vaccines • Pharmaceutics • Radio-isopes • Malaria parasites • Management • Analysis • Sharing • DNA • RNA • Internal • External • HTA • Evidence-based surgery • Field lab • Statistics • Biological • Structural • Preclinical • Clinical Expertises SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  14. 14. Radboudumc Technology Centers Alain van Gool Dirk Lefeber Leo Kluijtmans Uli Brandt Frans Russel David Burger Marcel Nelen Alexander Hoischen Joris Veltman Arnoud van der Maas Ariaan Siezen Kasper van Beem Maroeska Rovers Alain van Gool Marieke Welzen Carl Figdor Jolanda de Vries Harry Dolstra Otto Boerman Robert Sauerwein Frans Pieters Gerhard Zielhuis Peggy Manders Maroeska te Loo Dyonne van Duren Marieke Welzen Hein Gooszen Maroeska Rovers Mathias Prokop Otto Boerman Mathias Prokop Chris de Korte Peter Friedl Jack Fransen Judith Hornberg Guillen Fernandez Merel Ritskes Alain van Gool Nathalie Bovy Bob de Jonge Marcel Wortel Dirkjan Masman John Schalken People Harry Dolstra Frank Preijers Joop Jansen Carl Figdor Martijn Huijnen Gert Vriend Christian Gillissen About 200 people working in all Technology Centers, ~1500 users (internal, external), ~100 consortia SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  15. 15. Cross-technology interactions SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  16. 16. Center for proteomics, glycomics & metabolomics Research Biomarkers Diagnostics • Mass spectrometry – NMR based, 20 dedicated fte • Part of Department Laboratory Medicine (core diagnostic laboratory ) • Close interaction with Radboudumc scientists and external partners SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  17. 17. Example of Omics in personalized healthcare • 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 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  18. 18. Biomarkers in an evolving role • From only diagnosis • To Translational Medicine • To Personalized Medicine • To Personalized Healthcare • To Person-centered Health(care) SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  19. 19. Biomarkers in the early days This urine wheel was published in 1506 by Ullrich Pinder, in his book Epiphanie Medicorum. The wheel describes the possible color, smell and taste of urine, and uses them to diagnose disease. Source: wikipedia {Kumar and van Gool, RSC, 2013} SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  20. 20. Limited view from the outside SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool Source: Gary Larson Animal models Patient-related outcome Source: National University Hospital Singapore
  21. 21. Biomarker need in pharmaceutical drug development SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool • Translational medicine  Exposure  Mechanism  Efficacy  Safety • Personalized medicine  Diagnosis  Prognosis  Response prediction • Tools for data-driven decision making  Biologically relevant  Clinically accepted  Quantitative  Different analytes/types  Fit-for-purpose application {Source: Van Gool et al, Drug Disc Today 2010}
  22. 22. Biomarker as tools for data-driven decisions SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool Target engagement? Effect on disease? yes yes ! no no • No need to test current drug in large clinical trial • Need to identify a more potent drug • Concept may still be correct • Concept was not correct • Abandon approach • Proof-of-Concept • Proceed to full clinical development “Stop early, stop cheap” “More shots on goal”
  23. 23. Source: John Arrowsmith: Nature Reviews Drug Discovery 2011 • Success rates of clinical proof-of-concept have dropped from 28% to 18% • Insufficient efficacy as the most frequent reason Increasing failures in drug development Analysis of 108 failures in phase II Reason for failure Therapeutic area SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  24. 24. Need for 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. SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  25. 25. Companion Diagnostics Metabolism Efficacy or safety Source: www.fda.gov {Kumar and van Gool, RSC, 2013} SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool 113 drug labels with biomarker test (end 2012)
  26. 26. 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} SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  27. 27. Clinical efficacy 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 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  28. 28. 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 vary • Biomarker levels in body fluids will vary • Major challenge for (companion) diagnostics {Source: Yancovitz, PLoS One 2012} SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  29. 29. Other ‘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 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  30. 30. 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) SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  31. 31. A changing world: Personalized Medicine @Europe European Science Foundation 30 Nov 2012 32 Innovative Medicine Initiative 8 July 2013 European Commission Horizon2020 10 Dec 2013) SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  32. 32. Emerging: Personalized Healthcare in a systems view Source: Barabási 2007 NEJM 357; 4} • People are different • Different networks and influences • Different risk factors SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  33. 33. Personalized Healthcare in a systems view SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  34. 34. Personalized Healthcare in a systems view SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  35. 35. Personalized Health(care) model 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) 36 Personalized Participatory Pre-emptive SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  36. 36. Analogy: TOMTOM 37 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool Used as planner for best route to destination Utrecht Amsterdam Utrecht Amsterdam Route 1 Route 2 = Default Traffic jam near Utrecht Alternative route Route: Nijmegen to Amsterdam
  37. 37. Personalized Health(care) model 38 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool Used as planner for best route to health Risk Health Route 1 Route 2 = Default First signs of disease near site of risk Alternative route Now Risk Health Now Route: Now to Health
  38. 38. Example personal profile-based healthcare {Chen et al, Cell 2012, 148: 1293} Concept: • Selfmonitoring (n=1) • Routine biomarkers to alert • Omics to explain • Early intervention 39 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  39. 39. Selfmonitoring 40 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  40. 40. The future is nearly there … Personalized advice Action Selfmonitor Cloud Lifestyle Nutrition Pharma SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  41. 41. healthy disease disease + treatment Identify subpopulations in Personalized Healthcare healthy disease disease + treatment • Biomarkers in populations often have a wide range • Within this range, subpopulations can behave quite differently • Chemometric methods dealing with multiple biomarker data points are needed to define subgroups • Leading to n=1 clinical trials (Source: Jasper Engel, Lionel Blanchet, Udo Engelke, Ron Wevers and Lutgarde Buydens) 42 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  42. 42. However … Knowledge and Innovation gap: 1. What to measure? 2. How much should it change? 3. What should be the follow-up for me? SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  43. 43. Biomarker innovation gap • Imbalance between biomarker discovery, validation and application • Many more biomarkers discovered than available as diagnostic test Discovery Clinical validation/confirmation Diagnostic test Number of biomarkers Gap 1 Gap 2 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  44. 44. 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 45 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  45. 45. 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} 46 {Source: Khusru Asadullah, Nat Rev Drug Disc 2011} SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  46. 46. Needed: open innovation in biomarker research Standardisation, harmonisation, knowledge sharing needed in: 1. Assay development 2. Clinical validation Shared knowledge, technologies and objectives 47 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  47. 47. 48 Good example of multi-laboratory biomarker validation 48 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  48. 48. 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 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool Open slot!
  49. 49. And then … Translation to personalized action ! 50 Personal profile data Knowledge Understanding Decision Action SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  50. 50. 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 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  51. 51. SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  52. 52. Systems view on metabolic health and disease 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 Gut activity Inflammatory response Adrenalin Heart rate Heart rate variability High cortisol α-amylase SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  53. 53. Systems view on metabolic health and disease 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 Gut activity Inflammatory response Adrenalin Heart rate Heart rate variability High cortisol α-amylase {Nakatsuji, Metabolism 2009} SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  54. 54. Systems view on metabolic health and disease 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 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  55. 55. EC DG for Research and Innovation Alain van Gool Brussels, 11 Sept 2012 Relating tissue pharmacology – biomarker - therapy SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  56. 56. Translating knowledge to field labs 1. Implementation-plan ‘Personalized diagnosis of (pre)diabetic and their lifestyle treatment in Dutch Health care’. 2. Use of Oral Glucose Tolerance Test as a stratification biomarker for (pre)diabetic patients 3. Advice a tailored treatment (lifestyle and/or medical) 4. Monitor added value of stratification 5. Communicate results and lessons learned Being implemented in 1st line care (region Hillegom, Netherlands) Alliance “Expedition Sustainable Care, starting with diabetes” SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  57. 57. Personalized interventions by Pharma-Nutrition 58 Open invitation to join: • Shared Innovation Programs • Horizon2020 public-private consortia Higher efficacy / less side effects SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  58. 58. Data mining Models Modelling Analytics (Mx, Px, Tx) Organ-on- a-chip Imaging Academic/ ClinicalIndustry Shared Innovation Program Dia-Free 20+ partners Diagnostics Pharma Nutrition 20+ partners Better diagnosis and interventions Personalized ! 59 20+ partners 10+ partners
  59. 59. Biomarkers in an evolving role • From only diagnosis • To Translational Medicine • To Personalized Medicine • To Personalized Healthcare • To Person-centered Health(care) SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  60. 60. British Medical Journal SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  61. 61. Innovators Hypotheses Clinical trials Pilot implementation Everyday patient care Actual clinical implementation Knowledge center Optimal infrastructure for innovation SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  62. 62. Healthcare costs per patient (hospitals, drugs, community care) Regular care ParkinsonNet care SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  63. 63. Personalized Healthcare Ways forward: • Patients included • Participation + collaboration • Selfmonitoring • Personal profiles • System biology • (Big) Data sharing • Personal preferences • Personalized therapies • Lifestyle + Nutrition + Pharma SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool
  64. 64. Acknowledgements Lucien Engelen Jan Kremer Paul Smits Maroeska Rovers Nathalie Bovy Ron Wevers Jolein Gloerich Hans Wessels Dirk Lefeber Leo Kluijtmans Bas Bloem Marten Munneke 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 SelectBio Biomarkers 2014 Cambridge 8 July 2014 Alain van Gool 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

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