2016 03-17 Diesviering Maasziekenhuis, Boxmeer, Alain van Gool

The future is nearly here: Personalized Health(care)

Professor of Personalized Healthcare Head Radboud Center for Proteomics, Glycomics and Metabolomics Coordinator Radboud Technology Centers

Senior Scientist Integrator Biomarkers

Prof Alain van Gool

Diesviering Maasziekenhuis Pantein, Boxmeer 17 March 2016

Scientific lead DTL-Technologies Head Biomarker Platform

My background in personalized health(care)

8 years academia (NL, UK)

(molecular mechanisms of disease)

13 years pharma (EU, USA, Asia)

(biomarkers, Omics)

4 years med school (NL)

(personalized healthcare, Omics, biomarkers)

4 years applied research institute (NL, EU)

(biomarkers, personalized health, nutrition)

1991-1996 (PhD)

1996-1998 (post-doc)

2009-2012 (visiting prof)

1999-2007 2007-2009 2009-2011

2011-now

2011-now (prof)

2

A person / citizen / family man (adventures in EU, USA, Asia)

Alain van Gool, Maasziekenhuis Pantein, Boxmeer, 17 Mar 2016

2016 (Scientific lead DTL-Technologies)

2016 (Head Biomarker Platform)

3 Alain van Gool, Maasziekenhuis Pantein, Boxmeer, 17 Mar 2016

Consider individual differences in life science research

4


Source: Chakma, Journal of Young Investigators, 16, 2009

Principle of Personalized Medicine

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• The right drug for right patient at right dose at right time • Molecular biomarkers as key drivers of patient selection • = Precision medicine or Targeted medicine


Crash course in molecular biology

6

DNA, protein, cell, tissue, system biology


Biomarkers

{Biomarkers definition working group, 2001 }

‘a characteristic that is objectively measured and

evaluated as an indicator of normal biological

processes, pathogenic processes, or pharmacologic

responses to a therapeutic intervention’

Dutch CC meeting ‘Personalized Health Care”

Ede, 2 October 2013

Alain van Gool

Lecture LKCH, UMC Utrecht

29 October 2013

Alain van Gool

DNA, RNA proteins biochemicals images


http://www.google.com/imgres?imgurl=http://upload.wikimedia.org/wikipedia/en/thumb/4/49/Cholesterol_structure.png/800px-Cholesterol_structure.png&imgrefurl=http://picsdigger.com/image/9bbfe1e8/&usg=__lgIeM7XqXX386731BUQz3NedgF8=&h=359&w=800&sz=24&hl=en&start=4&sig2=Zx35nHL-T3JMZ-sJMEym5A&um=1&itbs=1&tbnid=gcQNbxseIbu3DM:&tbnh=64&tbnw=143&prev=/images?q=cholesterol+structure&um=1&hl=en&tbs=isch:1&ei=PPYRTPbEFsKvrAea0dW3BA

http://www.google.com/imgres?imgurl=http://www.mc.uky.edu/Structuralbiology/psa_for_jack.jpg&imgrefurl=http://www.mc.uky.edu/Structuralbiology/&usg=__YXLZwCJp85cTWQYJzer1AzfgMHE=&h=535&w=750&sz=234&hl=en&start=1&sig2=AqVXjE_3CNeBw04PJ2IlZA&um=1&itbs=1&tbnid=tVXfc3lHcX1jHM:&tbnh=101&tbnw=141&prev=/images?q=psa+structure&um=1&hl=en&tbs=isch:1&ei=UPYRTPSiNcK-rAee6Mm0BA

http://www.google.com/imgres?imgurl=http://levis.tongji.edu.cn/gzli/image/t1-mri-brain-glioma.jpg&imgrefurl=http://levis.tongji.edu.cn/gzli/direction.htm&usg=__I1zN5qHq6Dy-XeIoV7PEErv_U50=&h=512&w=512&sz=59&hl=en&start=15&sig2=bkDWF22aiEMBpA-IuA0aZw&um=1&itbs=1&tbnid=rzCYX-mOOCfnxM:&tbnh=131&tbnw=131&prev=/images?q=mri+brain+tumor&um=1&hl=en&tbs=isch:1&ei=vfYRTPqYBorCrAfJ2bDDBA

Example: Personalized medicine in melanoma

B-RAFV600E mutation Strong growth of cell Growth of tumor

• B-RAFV600E cells always grow and become cancer cells

• RAF inhibitors will block pathway, block cell growth and inhibit cancers that have a B-RAFV600E mutation

• 60% of melanoma patients have B-RAFV600E mutation

• Basis for a personalized medicine !


Personalized medicine in melanoma

Treat patients with

B-RAFV600E mutation Inhibit growth of cell

Patients live longer Tumors disappear Cells stop growing

B-RAF inhibitor


Emerging Personalized / Precision / Targeted Medicine

2010:

5% of drugs in pipeline had companion diagnostic biomarker test

2015:

80%

50%


11 Alain van Gool, Rotary Oss, 3 Mar 2016

Optimal Personalized / Precision / Targeted Medicine

People are more than linear pathways

Moving to Personalized Health(care)

“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, October 2013)

13


Societal need in efficient personalized health(care)

{Source: prof Jan Kremer}

Towards cost effective care, less cure


Personal need in efficient personalized health(care)

It’s personal !

‘I want to stay healthy.’ ‘If not, how do I get healthy?’



My route to Personalized Health(care)


Analogy: TOMTOM

GPS to a location

Amsterdam

Traffic jam

Amsterdam

Route 1 Route 2

= Default Traffic jam near Utrecht Alternative route


Personalized Health(care) model

GPS to health

Health

Route 1 Route 2

= Default First signs of disease risk

Alternative route

Now

Disease risk

Health

Now

Health


3 key aspects of personalized health(care)

‘I want to stay healthy. If not, how do I get healthy?’

1. What to measure?

2. How much can it change?

3. What should be the follow-up for me?


Exponential technological developments • Next generation sequencing

• DNA, RNA • Risk analysis and therapy selection

• Mass spectrometry • Proteins, metabolites • Monitoring of disease and treatment effects

• Imaging • Non invasive images, real time

• Spatial view of intact organs and organisms

500

1000

1500

2000

m/z

5 10 15 20 25 30 35 40 Time [min]


News from a molecular biomarker lab • Mass spectrometry analysis of glycoproteins in human plasma • 1 microliter analysis: detection of 100.000 signals in one scan • ~40.000 peptides of which >80% contain sugar modification • Diagnose patients and identify new biomarkers

500

1000

1500

2000

m/z

5 10 15 20 25 30 35 40 Time [min]

Proof of principle study:

{Translational Metabolic Laboratory, Radboudumc, unpublished data} 22 Alain van Gool, Maasziekenhuis Pantein, Boxmeer, 17 Mar 2016

Research Biomarkers Diagnostics

Department of Laboratory Medicine, Radboudumc Integrated Translational Research and Diagnostic Laboratory, 220 fte, yearly budget ~ 28M euro. Close interaction with Dept of Genetics, Pathology and Medical Microbiology

Specialities: • Proteomics, glycomics, metabolomics • Enzymatic assays • Neurochemistry • Cellulair immunotherapy • Immunomonitoring

Areas of disease: • Metabolic diseases • Mitochondrial diseases • Lysosomal /glycosylation disorders • Neuroscience • Nefrology • Iron metabolism • Autoimmunity • Immunodeficiency • Transplantation

In development: • ~500 Biomarkers • Early and late stage • Analytical development • Clinical validation

Assay formats: • Immunoassay • Turbidicity assays • Flow cytometry • DNA sequencing • Mass spectrometry • Experimental human (-ized)

invitro and invivo models for inflammation and immunosuppression

Validated assays*: • ~ 1000 assays • 3.000.000 tests/year

Areas of application: • Personalized healthcare • Diagnosis • Prognosis • Mechanism of disease • Mechanism of drug action

Biomarker development pipeline @ Radboudumc

*CCKL accreditation/RvA/EFI


www.radboudumc.nl/research/technologycenters

Genomics

Bioinformatics

Animal studies

Stem cells

Translational neuroscience

Image-guided treatment

Imaging

Microscopy

Biobank

Health economics

Mass Spectrometry

Radboudumc Technology

Centers Investigational

products

Clinical studies

EHR-based research

Statistics

Human performance

Data stewardship

Molecule

Flow cytometry

24

Implementation phase

Nov 2014 -

About 250 dedicated people working in 18 Technology Centers, ~1600 users (internal, external), ~140 consortia www.radboudumc.nl/research/technologycenters/

• Proteins • Metabolites • Drugs • PK-PD

• Preclinical • Clinical

• Behavioural • Preclinical

• Animal facility • Systematic review

• Cell analysis • Sorting

• Pediatric • Adult • Phase 1, 2, 3, 4

• Vaccines • Pharmaceutics • Cyclotron • Radio-isotopes • Malaria parasites

• Management • Analysis • Sharing • Cloud computing

• DNA • RNA

• Internal • External

• Early HTA • Evidence-based

surgery • Field lab

• Statistics • Biological • Structural

• Preclinical • Clinical • Economic

viability • Decision

analysis

• Experimental design • Biostatistical advice

• Electronic Health Records • Big Data • Best practice

• In vivo • Functional

diagnostics

• iPSC • Organoids

25

Working with other networks Region, nation, Europe, world

26


27

New data (generators, owners)

28

Demo room

Science fiction ?


Science reality



32

Personalized advice

Action

Selfmonitor Cloud

Lifestyle Nutrition Pharma

DIY monitoring of vital signs

DIY monitoring of glucose levels

34

• Measure your brain waves (EEG)

• Recognize conditions for maximal concentration or relaxation.

• Use device to train.

DIY brainwave monitoring


DIY blood biomarker analysis

• Measure key biomarkers in one drop of blood at few $ per test panel

• Download data to your smartphone to monitor your own trend



• DIY sequence your genome and/or your microbiome genome • at a provider, at a pharmacy, at home

• Take your genome to the doctor • Have a personalized healthcare advice

DIY sequencing

23% chance blond hair

What does my DNA tell me?

3.1% Neanderthaler DNA


Genetic risk lung cancer → don’t smoke !

What does my DNA tell me?

No expected adverse reaction to Warfarin


‘insideables’

‘wearables’


Try-outs at REshape Center of Health(care) Innovation

Lucien Engelen

… but not all data is useful data !

Need for optimal quality in health biomarker analyses

Test, interpret, advice

“Post-traumatic Test Syndrome” ?


3 key aspects of personalized health(care)

‘I want to stay healthy. If not, how do I get healthy?’

1. What to measure?

2. How much can it change?

3. What should be the follow-up for me?


Translation is key in personalized health(care)

Personal profile data

Knowledge

Understanding

Decision

Action

Shared decision making


Translation is key in Personalized Healthcare !

“I’m afraid you’re

suffering from an

increased IL-1β and

an aberrant miR843

expression”

Adapted from:

?


Personalized health(care) model

Personalized Intervention

of patients-like-me Personal thresholds of persons-like-me

Big Biomarker Data

Molecular Non-molecular Environment …

Time

Disease

Health

Selfmonitoring

Adapted from Jan van der Greef, TNO

Personal profile

Personalized health

Personalized medicine


Personalized health(care) monitoring as part of our lives

• Monitor on background

• Alert when you are at risk

• Advice what to do

Examples from car dashboard:

• Empty gas tank

• Traffic jam ahead


http://www.google.nl/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRxqFQoTCJ6kuJXIvcYCFYFcFAodO2oP3A&url=http://arstechnica.com/apple/2014/03/ios-in-the-car-becomes-carplay-coming-to-select-dashboards-this-year/&ei=TsSVVZ7FO4G5UbvUveAN&bvm=bv.96952980,d.d24&psig=AFQjCNHK-5180CQ5Wim0GGTOe8N0tIZRIQ&ust=1435964869551370

What is health?


What’s next?

Simulating YOUR health

Heleen Wortelboer Herman van Wietmarschen Jan van der Greef Esther Zondervan Wim van Hartingsveldt


What’s next?

Simulating YOUR health + Personalized advice + Feedback

View in the (very near) future


scanadu.m4v

Acknowledgements

Ron Wevers

Jolein Gloerich

Hans Wessels

Dirk Lefeber

Monique Scherpenzeel

Leo Kluijtmans

Lucien Engelen

Nathalie Bovy

Paul Smits

Maroeska Rovers

Bas Bloem

the Technology Centers

and many others

www.radboudumc.nl/personalizedhealthcare

www.radboudresearchfacilities.nl

www.radboudumc.nl/research/technologycenters

[email protected]

[email protected]

www.linkedIn.com

www.slideshare.net/alainvangool

Many collaborators and funders

Jan van der Greef

Ben van Ommen

Bas Kremer

Cyrille Krul

Ivana Bobeldijk

Lars Verschuren

Marjan van Erk

Peter van Dijken

Peter Wielinga

Ronald Mooij

Suzan Wopereis

and many others

CarTarDis


http://www.erasmusmc.nl/index.htm