Transcript Roche Template - Aalter Medisch Labo Medina

Gepersonaliseerde gezondheidszorg
Van utopie tot realiteit
Personalised Healthcare
Hype or reality?
Rob Geraerdts
Personalised Healthcare (PHC)
Is it more than a media reality – hype – or will it truly develop ?
Personalised medicine may be our future approach
Targeted drugs: The race is on
Targeted cancer drugs gain backers
Personalised drugs draw biotech dollars
Personalised approach to cancer
Personalised medicine: New approach to staying well
‘Targeted‘ drugs prove powerful against forms of cancer
FDA acts to foster ‘personalised drugs`
The Challenge of Personalised Healthcare
What the public came to expect of PHC are truly individualised therapies – something science and
industry may not be able to deliver for some time
Source: JAMA. 2006;296:1453-1454.
Why a new approach to staying well is required ?
What's the challenge and promise of Personalised Healthcare?
Same symptoms
Same findings
Same disease
Same Drug...
...different effects
Variability of disease
Drug metabolism
Drug-drug interactions
Non-compliance
Development towards A More Personalised Healthcare
Using clinical differentiators to achieve optimal pharmaceutical efficacy
and safety for the purpose of creating sustainable clinical benefits
Increasingly, treatment
will be tailored to patient
groups defined by their
genetic disease pattern
Still today, almost all patients
are treated in a few similar ways
Therapeutic stratification
Personalised Healthcare
Not a totally new concept but an evolution
For more than 10, 000 years
Diagnosis and treatment based on what could be seen,
smelled, tasted, palpated or intuited
The last 100 years
Diagnosis and treatment expanded with knowledge about
biochemistry and cellular processes
Today
Diagnosis and treatment expanded with rapidly growing insights
into molecular processes and variations in our genes
Challenges for the Healthcare system
Technological development and evolution in Diagnostics
Potential future role for the General Practioner
Health Economic Value of Medical Devices
The outside world is changing
Cost pressure
Aging
population
Payers
Cost
control
Empowered people with
increased health consciousness
and demands to the system
Payers controlling providers and
redistributing costs to people
Borderless world
IT revolution
Medical
innovation
Providers forced by people and payers to
change the way they perform medical
practice
Involvement of all players in the creation of
health networks that form strong health care
brands.
Challenges for the Healthcare system
Technological development and evolution in Diagnostics
Potential future role for the General Practioner
Personalised Healthcare: hype or reality?
Evolution in literature of definitions for In Vitro Diagnostics
In Vitro Diagnostics are Medical Devices which enable analysis of bodily fluids and tissues
for determining disease conditions
In Vitro Diagnostics are enabling technologies to structure tomorrow's health care
processes based on medical evidence
In Vitro diagnostics are a valuable tool for preventing illness, for early diagnosis and for
optimising therapy through patient monitoring and/or stratification
Personalised Healthcare: hype or reality?
The need for health information as basis for medical decisions
Result
Standardisation
Today:
• Tests with blood, liquid and tissue
Tomorrow:
Improved
Information
Novel
Content
• Health information
- „the right information in the right place at the right time“
- individual patient treatment (i.e. test result, risk profile,
treatment recommendation)
- transition of today's IVD products into specific biomarkers
Personalised Healthcare: hype or reality?
How did technological development in IVD testing contribute to creating value in the
laboratory ?
Productivity
Re-engineering
Medical Processes with IVD
Total IVD infrastructure
( Lab Network / IT )
- DRG’s
- Indication management
- Personalised Health Care
- IT solutions
-Hospital solution
Laboratroy Organisation
- Increase laboratory productivity
Systems
Reagents
- System portfolio
- Professional System Service
- Reagent harmonization
- Robustness improvement
- Result standardisation
investments
Personalised Healthcare: hype or reality?
Populating the laboratory health value chain with tools and content to create personalised healthcare
Targeted
monitoring
Preventive
measures
Diagnosis
Tools
CONTENT
TOOLS
Predisposition
screening
+
Therapy
decision
Therapy
monitoring
toring
Personalised Healthcare: hype or reality?
More fundamental knowledge of the "system biology" increases our understanding for
underlying causes for diseases
Personalised Healthcare: hype or reality?
To unveil the secrets of the "system biology" novel technologies are to be developed – used
for diagnostic purposes
DNA
(gene)
mRNA
(transcript)
genome
transcriptome
genomics
transcriptomics
Bioinformatics
protein
proteome
proteomics
Personalised Healthcare: hype or reality?
To understand "system biology", convergence of novel technologies will provide the full
potential to understanding disease patterns
Ascher Shmulewitz et al, Nature Biotechnology – March 2006
Personalised Healthcare: hype or reality?
"Systems biology" transparency in disease processes
Creating PHC from an industrial perspective
Diagnostics input is key - from discovery to market of pharmaceuticals
Research
Develop
Lead
Target
Generation/
Phase 0
Selectio
Optimisatio
n
n
Discover
Exploratory Phase
y
Phase
Biomarker
development
Target identification
Research assay
Phase I
Commercialise
Phase II Phase III
Filing
Market
Phase IV
PoC
Companion diagnostic
feasibility & attractiveness
Patient selection
Technically validated assay
Confirmatory Phase
Dx launch/ Post-launch
assessment
Tailored prescribing
& monitoring
Clinically validated IVD assay
Personalised healthcare: hype or reality?
Understanding of disease "genetic" pattern will drive usage of new technologies in
Diagnostics
Examples
Parameters (eg, Genes, Mutations)
1
PCR
Point Mutations;
10
Linear Arrays
100
1000
Microarrays
Simple Gene Analysis Complex Gene Analysis
Resequencing
Genotyping Examples:
• CYP450 2C9
• Factor II/V
• CF Linear
Array (US)
• AmpliChip CYP450
Test (CE-IVD)
• AmpliChip p53*
Expression Examples:
Single parameter
“Expression”:
Complex Expression:
• Taqman HIV Monitor
• Taqman HCV Monitor
• Leukemia*
• Breast Cancer
• Cardiovascular Disease
* under development
Personalised Healthcare in the market today
Current examples in oncology
• Implementing biomarker strategy for all pipeline drugs
• Distribution of K-RAS and EGFR Cancer Mutation Tests
– Tests identify genetic mutations that can affect patient
response to certain cancer drugs
• Identifying patients who have an improved response to
launched drugs
– e.g. Tarceva in 1st line maintenance NSCLC / SATURN
trial
• Assessing opportunities for companion diagnostics
– Pertuzumab/HER dimerization inhibitors: Expression of
HER 2
– MDM2: Active only in p53 wild-type patients
– PLX4032: Presence of BRAF V600E gene mutation
Personalised Healthcare today in the market
Current examples in virology
• Detecting Hepatitis C virus subtype and monitoring
viral load/ Pegasys response
– Determine length of treatment by strain of virus
– Monitor viral load to determine likelihood of
response and aid in compliance
• Determining genotype 16 and 18 of Human
Papilloma Virus
– Reduce risk of cervical cancer by closer
monitoring
– Support Roche Pharma studies on therapeutic
vaccines
Personalised Healthcare in the market today
IAT-Beispielliste
Oncology
Tamoxifen
Tamoxifen
Tamoxifen
Tamoxifen
Chemotherapy
Arimidex
Herceptin
Xeloda
6-Mercaptopurine
Gleevec (CML)
Gleevec (GIST)
Dasatinib
Iressa
Tarceva
Irinotecan
Erbitux
Retinoic acid
MabThera
Tykerb
ER/PR Status
BRCA1
BRCA2
CYP2D6
Oncotype Dx
ER/PR status
HER2 assay
Enzyme activity
TPMT
BCR-ABL
C-Kit
BCR-ABL
EGFR Status
EGFR/HER1
UGT1A1
EGFR status
PML/RAR gene
CD20
EGFR status
Pegasys/Copegus
HIV Prot. Inh. (1st to mkt)1
HIV Prot. Inh. (2nd to mkt)2
HIV Prot. Inh. (1st to mkt)1
HIV Prot. Inh. (2nd to mkt)2
Isoniazid
Tamiflu
PegintronA
Roferon
Azathioprine
Neoral (Cyclosporine)
Prograf (Tacrolimus)
Rapamune (Sirolimus)
Mabthera
1. Invirase; 2. Crixivan
IA
TPMT
IA’s for CsA
IA
IA
RA profiles
HCV Genotyping
Viral Load
Viral Load
Viral Genotyping
Viral Genotyping
NAT
Influenza A/B test
HCV EVL
HCV EVL
Respiratory
Prolastin
Theophylline
PiZZ, PiZ Pi
CYP2D6
GIT
Omeprazole
Proton pump inh.
and Antibiotics
Autoimmune and Transplant
Cellcept
CNS
Virology/Infectious Diseases
Ethnicity
NAT
NAT
Troponin
Troponin
CYP2C9
CYP2D6
CYP2D6
CYP2D6
CYP2D6
CYP2D6
COMT
COMT
CYP2D6
Metabolic and Vascular Disease
Fosamax
Somatropin
Insulin
Simvastatin
CYP2C19
H Pylori
Cardiovascular
BiDiL
Hydralazine
Procainamide
GPIIb/IIIa
Streptokinase
Phenytoin
Venlafaxine
Modafinil
Resperidone
Atomoxetine
Thioridazine
Levodopa
Tasmar
Aripiprazole
P1NP
Chr 15
HbA1c
Lipid profiles
Haematology
Warfarin
Warfarin
Heparin
EPO
CYP2C9
VKORC1
APTT
CBC
Anaesthesia
Succinylcholine
PseudocholInesterase levels
Challenges for the Healthcare system
Technological development and evolution in Diagnostics
Potential future role for the General Practioner
Personalised Healthcare: hype or reality
The proven promise of personalised health care is to further improve effectiveness of
treatment
Effectiveness of treatment can be improved…
• 20-75% of patients do not receive effective treatment1
• >100.000 deaths/yr from adverse drug reactions in US2
…by tailoring treatments to selected patient groups defined by biomarkers
1
2
Spears et al., Trends Mol Med, 2001
Lazarou et al., JAMA, 1998
New testing algorithms –
A new paradigm shift in "how to treat" patients
Earlier, better diagnosis allowing for better and cost effective treatment –
Early patient stratification
Today
Today diagnostics often addresses end stages
of diseases. Here (e.g. late cancer phase)
treatment is expensive and may not cure the
patient.
for the individual patient
Likelihood of treatment success
lower
higher
New markers for the disease onset change this
picture dramatically. Health care cost go down
and treatment success improves.
lower
Future
Patient Status
asymptomatic
symptomatic
higher
This is were marker identification programs
like proteomics and genomics come in.
Personalised healthcare: hype or reality
Role of the treating physician across the healthcare value chain
Healthy
Risk
Assessment
Predisposition
for developing
disease
Asymptomati
c disease
Symptomatic disease
Chronic disease
Cured
Screening/
Diagnosis
Prognostic
Predictive
Monitoring
Early
detection
Predict
probable
disease
course
Predict likely
response to a
drug
Monitor
efficacy/
recurrence
Patient Stratification / Therapy Selection
Therapy adaptation
Personalised Healthcare: hype or reality?
Benefits for patients and healthcare system
Patients
Best treatment
Regulators & Policy Makers
Physicians & Providers
Increased efficacy & safety
Reduced healthcare costs
Maximum benefit,
minimum toxicity
Payers & Reimbursers
Efficient use of healthcare
budgets