2014 03-13 Health Valley 2014, Nijmegen
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Alain van Gool presented on biomarkers in personalized healthcare. He discussed how personalized medicine is shifting to personalized healthcare with a systems view that considers multiple factors. Exponential technologies will transform healthcare in the coming years through digital medicine, self-diagnosis, artificial intelligence, and big data. However, gaps remain in translating biomarker discoveries into clinical applications and demonstrating added value. Open innovation is needed to accelerate biomarker development through multi-center validation studies.
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2014 03-13 Health Valley 2014, Nijmegen
- 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
- 34. Big Data
- 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
- 51. Year 1 Applying lessons learned across fields e.g. System Biology @TNO Year 2 Year 3