2016-02-18 Innovation for Health 2016 conference, Rotterdam Alain van Gool

Personalized Health(care): more than ‘just’ targeted medicines

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

Senior Scientist Integrator Biomarkers

Prof Alain van Gool

Innovation for Health Rotterdam, 18 Feb 2016

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, Innovation for Health, 18 Feb 2016

2016 (Scientific lead DTL-Technologies)

2016 (Head Biomarker Platform)

3 Alain van Gool, Innovation for Health, 18 Feb 2016

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

Principle of Personalized/Precision/Targeted Medicine

4

• The right drug for right patient at right dose at right time • Molecular biomarkers as key drivers of patient selection


Emerging Personalized / Precision / Targeted Medicine

Good examples personalized medicine in Oncology and Neurosciences:

• Her2/neu, BRCA, BRAF, EGFR, EML4/ALK, Cyp450, etc

Emerging companion diagnostics, also linked to non-drug therapies:

• Volker: Intestinal surgery → XIAP → Cord blood

• Beery twins: Cerebral palsy → SPR → Diet 5HTP

• Wartman: Leukemia → FLT3 → Sunitinib

• Gilbert: Healthy → BRCA → Mas/Ovarectomy

• Snyder: T2Diabetes → GCKR, KCNJ11 → Diet, exercise

• Lauerman: Scotoma, leg → JAK2 → Aspirin

• Bradfield: Healthy → CDH1 → Gastrectomy


6

Optimal Personalized / Precision / Targeted Medicine

People are more than linear pathways

Moving to Personalized Health(care)

{Source: Barabási 2007 NEJM 357; 4}

• People are different • Different risk factors (molecule, system, environment) • Different preferences • Shared desire not to get ill at all !


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?


1. What to measure?

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]


11

New data (generators, owners)


… but not all data is useful data !



1. What to measure?




healthy disease disease + treatment


Subgroups

100%

Individual

Population


Personalized health(care) model Personalized Intervention

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

Big Biomarker Data

Molecular Non-molecular Environment …

Ho

meo

sta

sis

A

llo

sta

sis

D

isease

Time

Disease

Health

Selfmonitoring

Adapted from Jan van der Greef, TNO

Personal profile

Personalized health

Personalized medicine

{See eg Chen … Snyder, Cell 2012, 148: 1293}




1. What to measure?





Personal profile data

Knowledge

Understanding

Decision

Action


Translation is key in Personalized Healthcare !

“I’m afraid you’re

suffering from an

increased IL-1β and

an aberrant miR843

expression”

Adapted from:

?


Lab values Clinical outcomes

Pain Mobility Fatigue

INTEGRATE-HTA {R van Hoorn, W Kievit, M Tummers, GJ van der Wilt}

Intervention

Participatory healthcare

Shared decision making


EC DG for Research and Innovation

Alain van Gool

Brussels, 11 Sept 2012

Field lab testing

Booth #15

? Effect drugs on individual driving skills

→ TNO moving base driving simulator

{Marike Hoedemaeker, Steven Erpelinck}


EC DG for Research and Innovation

Alain van Gool

Brussels, 11 Sept 2012

Personalized Nutrition and Health Research

Program

For a society in which

each individual can and

wants to make a

motivated and sustainable

choice for a healthy diet

and lifestyle.

(pre-competitive public-private

innovation program)

{Nard Clabbers}

Booth #15

However … quality of data !?!

• Extremely important for personalized healthcare model

• Lack of reproducibility of reported studies

• Bayer – 75% NOT reproducible (n = 67)

• Amgen – 89% NOT reproducible (n = 53)

• Quality of data needs to be improved in:

• Data capture

• Data stewardship (FAIR)

{Prinz, Nat Rev Drug Disc, 2011}

{Bengley, Nature, 2012}


Biomarker innovation gaps

Discovery Clinical

validation/confirmation

Diagnostic

test

Number of

biomarkers

Gap 1

Gap 2

Gap 3

• Too much science-focussed biomarker discovery • Too little development to application


Biomarker innovation gaps

Test, interpret, advice

“Post-traumatic Test Syndrome” ?


Build biomarker validation pipelines

Standardisation, harmonisation, knowledge sharing in:

1. Assay development

2. Clinical validation

NL Roadmap Molecular Diagnostics (2012) NL Grant 4.3M Eur (2014)


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

Ongoing independent biomarker activities

27

Europe

USA

{Asadullah et al, Nature Reviews Drug Discovery, Dec 2015}


The Good Biomarker Practice initiative

Join forces among Europe’s major academic infrastructures + industry to:

1. Establish “Good Biomarker Practice” guidelines

- on translational research, biomarker technologies, biobanking, data stewardship.

2. Efficiently execute high quality biomarker projects

- work together in clinical validation and development of probable biomarkers.

EU


HEALTH-RI: ENABLING PERSONALISED HEALTH RESEARCH

Agro

Biomedical

Design of multi-

disciplinary experiments

Information & Insight

e-health & quantified self data

Model systems

measure genotype & phenotype e.g. genomics, transcriptomics, proteomics,

metabolomics, bioimaging, microscopy, quantified self, lifestyle, nutritional studies

data design, analytics & stewardship

e.g. bioinformatics, computer science, biostatistics, computational (systems)

biology, e-science, ICT, …

Biomaterial and data

collections

International reference

data

Linked-(FAIR)-data backbone for distributed analytics & learning

Research project

Health objective

Nutrition & lifestyle

Biomedical & e-health .nl

{See www.dtls.nl}

NL

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

Lars Verschuren

Ivana Bobeldijk

Marjan van Erk

Carina de Jongh

Peter van Dijken

Peter Wielinga

Robert Kleemann

Suzan Wopereis

and many others

CarTarDis


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

2016-02-18 Innovation for Health 2016 conference, Rotterdam Alain van Gool

Health & Medicine

Transcript of 2016-02-18 Innovation for Health 2016 conference, Rotterdam Alain van Gool