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Tools for personalised
medicine in clinical trials
Wolfgang Kuchinke
Heinrich-Heine University Duesseldorf,
Germany
ECRIN Annual Meeting
16 May, 2013, Warsaw,
Poland
Personalized medicine is
different!
Clinical trials in personalized
medicine is a different way
of doing clinical research by
large clinical trials aiming for
statistical significance
Variability in human
responses
• It has been recognized that there is variability in human
responses to medical treatments and that not all
therapeutics are equally effective on all patients.
• It has become possible to identify the reason for many
sources of such human variability
• Development of specific treatments directed to the
individual
• To achieve the necessary customization and standardisation
of diagnostic tests and therapeutics for such small target
populations, researchers require new methods
• One of these areas is gene profiling and association studies
between drug response and DNA sequence variation
What is personalized medicine?
• Medical model that separates people into different
groups with medical decisions, practices, drugs,
interventions being tailored to the individual
patient based on their predicted response
• Personalized medicine provides understanding of
the molecular basis of disease, particularly
genomics giving an evidence base to stratify
related patients
• For example, personalized medicine can employ
therapies that target specific genetic changes that
cause each individual cancers
Study of the human
genome
• Basis was the study of the human genome and its variation over
the last two decades, which was accompanied by the innovation
of laboratory techniques and instrumentation
• Especially advancement in automated DNA sequencing and PCR
using automated thermal cyclers
• Studying sequence variations in specific regions of the genome
– Techniques have evolved to analyze microsatellite DNA and single-
stranded conformational polymorphisms (SSCPs)
– Use of expressed sequence tags (ESTs), cDNAs, antisense molecules, small
interfering RNAs (siRNAs), full-length genes and their expression products
and haplotypes
• Study of SNPs, which represents the most abundant form of
variation in the human genome
• SNPs account for over 90% of the differences between individuals
• Large-scale association studies between SNPs and drug responses
Personalised medicine
clinical trials
• Genetic, physiological and life style characteristics can
be used to individualize diagnosis, treatment and
prevention of diseases
• Personalised medicine has become an active area of
research, with tremendous potential to improve the
health
• This approach has consequences for clinical research:
– Replacement of a few large-scale trials with many smaller ones
– Integration of clinical trials data management with biosample
management, imaging, patient data from EHR or HIS and
inclusion of patient empowerment
How to prepare clinical research networks
for clinical trials in personalized
medicine?
Aim of personalized
medicine
• Equipped with tools that are more
precise, physicians can select a
therapy or treatment protocol based
on a patient’s genetic and molecular
profiles that may not only minimize
harmful side effects and ensure a
more successful outcome, but can
also help contain costs
Need for a highly
integrated infrastructure
• Adoption of Personalized Medicine requires an
active and flexible and highly integrated
infrastructure
• Joining of many different competences and
technologies and allowing continuous improvement
• Hospitals, clinics and diagnostic centres are no
longer separated from other disciplines like basic
science, information technologies, ethics
• Interaction between Biochemistry, Internal
Medicine, Psychiatry, Imaging, IT, Oncology
• Focus on data sharing between separate databases
Drawbacks of
personalized medicine
• Protection of patient’s privacy when collecting and storing large
anount of patient data without loosing effectiveness
• How to deal with incidental findings, for example life threatening
diseases with no treatment?
• Incorrect findings can become a moral problem
• Significant increase of genetic literacy required among physicians and
patients
• Lack of understanding of how the risk contribution of certain markers
could vary across several groups
• Lack of understanding about how the inheritance of markers
influences disease manifestation, and the interaction of genetic
factors with environmental factor
• Massive investment in infrastructure for collecting, storing, and
sharing data necessary
• A legal and security infrastructure to protect the data is necessary
The p-medicine project
aims for developing new
tools, IT infrastructures
and VPH models to
accelerate personalized
medicine for the benefit
of patients
p-medicine project
• Title: From data sharing and integration via VPH
models to personalized medicine
• 4-year Integrated Project funded under the European
Community’s 7th Framework Programme
• Involvement of ECRIN
– ECRIN supports the management of international
clinical trials by academic centres
– Integration of p-medicine tools in the international
clinical research infrastructure (ECRIN)
– Evaluation of the usability and effectiveness of p-
medicine tools used in ECRIN clinical trial
We asked the question:
can the tools developed for
personalized medicine in the
p-pedicine project be
employed effectively in a
clinical trials network
Use Cases for the clinical
trial network ECRIN
Use case / p-medicine
services
User
Imaging: involve reference
radiologist in clinical trial for second /
third opinion
Investigator, radiologist
Design CRF with semantically
assistance (ontology based)
Investigator, data
manager, sponsor
Patient empowerment to find
feasible trials / eligible patients
Investigator, patients
Patient empowerment in clinical
trials to access own data, increased
patient retention rates, informed
consent
Patients
ObTiMA as CDMS Investigator, CT stuff,
data manager
ObTiMA is a data
management system
specifically created for
data collection in
personalized medicine
clinical trials
ObTiMA System - Overview
From: Stenzhorn, VPH 2012 Conference – September 19, 2012 – London, UK
User Interface not found
in conventional clinical
trials data collection
forms: Biosample input
into Case Report Form
ObTiMA: Biobanking
Sample CRF (Case Report
Form)
From: 2nd Review Meeting p-medicine – April 25, 2013 – Brussels, EC
Analysis of integration and
evaluation requirements
• Based on the survey results, the tendency for ECRIN is to use
software as a service in the form as SaaS or ASP
• ECRIN data centres will (probably) not install and employ p-
medicine tools in one of their data centres
• p-medicine tools show different degrees of maturity, which
makes decision about future employment difficult
• A robust business model for the provision of services does not
yet exist
• Scenario: integration be reciprocal exchange of services
• Integration of services into ECRIN for evaluation
– Depending on tool/service maturity – document review, evaluation, gap-
analysis, validation approach
– Usability of p-medicine services, test trial (e.g. by a simulated trial)
– Conclusions about further use, sustainability, business model
How can the personalized
medicine infrastructure p-
medicine and the clinical
trials network ECRIN gain
from each other?
Integration of services into
a clinical research network
• International clinical research networks are heterogeneous
regarding their policies and decisions what clinical trials to
conduct
• In general, one wants to conduct more standard clinical trials
• Investment into a new, large IT infrastructure is not really
supported
• Personal medicine infrastructures and clinical trials networks
exchange their services to gain jointly from each other
• Therefore:
– Suggestion of integration be reciprocal exchange of services
– Not only software as a service, but also reciprocal knowledge
exchange and joint staff training
Integration of p-medicine tools in
ECRIN clinical trial network
Summary of evaluation
results
• Personalized medicine clinical trials is a new way of
conducting clinical research
• This doesn’t fit into the way conventional clinical trials are
conducted
• The main focus of clinical trials is standardization, to achieve
high quality of data with large patient populations and many
trial sites involved
• The simple addition of personalized medicine tools into an
operating clinical trials network doesn’t work
• A new IT infrastructure, but also new knowledge and
processes have to be supported
• We suggest the reciprocal exchange of services as a way to
make software tools for personalised medicine available, but
also to gain by knowledge exchange, exchange of personnel,
joint staff training, joint help, etc.
wolfgang.kuchinke@uni-duesseldorf.de
wokuchinke@outlook.de
More information about the personalized
medicine tools: www.p-medicine.eu
Contact
Wolfgang Kuchinke
Heinrich-Heine University, Duesseldorf, Germany
This presentation contains
additional explanatory material
for the workshop and Q&A session

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Personalized medicine tools for clinical trials - kuchinke

  • 1. Tools for personalised medicine in clinical trials Wolfgang Kuchinke Heinrich-Heine University Duesseldorf, Germany ECRIN Annual Meeting 16 May, 2013, Warsaw, Poland
  • 2. Personalized medicine is different! Clinical trials in personalized medicine is a different way of doing clinical research by large clinical trials aiming for statistical significance
  • 3. Variability in human responses • It has been recognized that there is variability in human responses to medical treatments and that not all therapeutics are equally effective on all patients. • It has become possible to identify the reason for many sources of such human variability • Development of specific treatments directed to the individual • To achieve the necessary customization and standardisation of diagnostic tests and therapeutics for such small target populations, researchers require new methods • One of these areas is gene profiling and association studies between drug response and DNA sequence variation
  • 4. What is personalized medicine? • Medical model that separates people into different groups with medical decisions, practices, drugs, interventions being tailored to the individual patient based on their predicted response • Personalized medicine provides understanding of the molecular basis of disease, particularly genomics giving an evidence base to stratify related patients • For example, personalized medicine can employ therapies that target specific genetic changes that cause each individual cancers
  • 5. Study of the human genome • Basis was the study of the human genome and its variation over the last two decades, which was accompanied by the innovation of laboratory techniques and instrumentation • Especially advancement in automated DNA sequencing and PCR using automated thermal cyclers • Studying sequence variations in specific regions of the genome – Techniques have evolved to analyze microsatellite DNA and single- stranded conformational polymorphisms (SSCPs) – Use of expressed sequence tags (ESTs), cDNAs, antisense molecules, small interfering RNAs (siRNAs), full-length genes and their expression products and haplotypes • Study of SNPs, which represents the most abundant form of variation in the human genome • SNPs account for over 90% of the differences between individuals • Large-scale association studies between SNPs and drug responses
  • 6. Personalised medicine clinical trials • Genetic, physiological and life style characteristics can be used to individualize diagnosis, treatment and prevention of diseases • Personalised medicine has become an active area of research, with tremendous potential to improve the health • This approach has consequences for clinical research: – Replacement of a few large-scale trials with many smaller ones – Integration of clinical trials data management with biosample management, imaging, patient data from EHR or HIS and inclusion of patient empowerment How to prepare clinical research networks for clinical trials in personalized medicine?
  • 7. Aim of personalized medicine • Equipped with tools that are more precise, physicians can select a therapy or treatment protocol based on a patient’s genetic and molecular profiles that may not only minimize harmful side effects and ensure a more successful outcome, but can also help contain costs
  • 8. Need for a highly integrated infrastructure • Adoption of Personalized Medicine requires an active and flexible and highly integrated infrastructure • Joining of many different competences and technologies and allowing continuous improvement • Hospitals, clinics and diagnostic centres are no longer separated from other disciplines like basic science, information technologies, ethics • Interaction between Biochemistry, Internal Medicine, Psychiatry, Imaging, IT, Oncology • Focus on data sharing between separate databases
  • 9. Drawbacks of personalized medicine • Protection of patient’s privacy when collecting and storing large anount of patient data without loosing effectiveness • How to deal with incidental findings, for example life threatening diseases with no treatment? • Incorrect findings can become a moral problem • Significant increase of genetic literacy required among physicians and patients • Lack of understanding of how the risk contribution of certain markers could vary across several groups • Lack of understanding about how the inheritance of markers influences disease manifestation, and the interaction of genetic factors with environmental factor • Massive investment in infrastructure for collecting, storing, and sharing data necessary • A legal and security infrastructure to protect the data is necessary
  • 10. The p-medicine project aims for developing new tools, IT infrastructures and VPH models to accelerate personalized medicine for the benefit of patients
  • 11. p-medicine project • Title: From data sharing and integration via VPH models to personalized medicine • 4-year Integrated Project funded under the European Community’s 7th Framework Programme • Involvement of ECRIN – ECRIN supports the management of international clinical trials by academic centres – Integration of p-medicine tools in the international clinical research infrastructure (ECRIN) – Evaluation of the usability and effectiveness of p- medicine tools used in ECRIN clinical trial
  • 12. We asked the question: can the tools developed for personalized medicine in the p-pedicine project be employed effectively in a clinical trials network
  • 13. Use Cases for the clinical trial network ECRIN Use case / p-medicine services User Imaging: involve reference radiologist in clinical trial for second / third opinion Investigator, radiologist Design CRF with semantically assistance (ontology based) Investigator, data manager, sponsor Patient empowerment to find feasible trials / eligible patients Investigator, patients Patient empowerment in clinical trials to access own data, increased patient retention rates, informed consent Patients ObTiMA as CDMS Investigator, CT stuff, data manager
  • 14. ObTiMA is a data management system specifically created for data collection in personalized medicine clinical trials
  • 15. ObTiMA System - Overview From: Stenzhorn, VPH 2012 Conference – September 19, 2012 – London, UK
  • 16. User Interface not found in conventional clinical trials data collection forms: Biosample input into Case Report Form
  • 17. ObTiMA: Biobanking Sample CRF (Case Report Form) From: 2nd Review Meeting p-medicine – April 25, 2013 – Brussels, EC
  • 18. Analysis of integration and evaluation requirements • Based on the survey results, the tendency for ECRIN is to use software as a service in the form as SaaS or ASP • ECRIN data centres will (probably) not install and employ p- medicine tools in one of their data centres • p-medicine tools show different degrees of maturity, which makes decision about future employment difficult • A robust business model for the provision of services does not yet exist • Scenario: integration be reciprocal exchange of services • Integration of services into ECRIN for evaluation – Depending on tool/service maturity – document review, evaluation, gap- analysis, validation approach – Usability of p-medicine services, test trial (e.g. by a simulated trial) – Conclusions about further use, sustainability, business model
  • 19. How can the personalized medicine infrastructure p- medicine and the clinical trials network ECRIN gain from each other?
  • 20. Integration of services into a clinical research network • International clinical research networks are heterogeneous regarding their policies and decisions what clinical trials to conduct • In general, one wants to conduct more standard clinical trials • Investment into a new, large IT infrastructure is not really supported • Personal medicine infrastructures and clinical trials networks exchange their services to gain jointly from each other • Therefore: – Suggestion of integration be reciprocal exchange of services – Not only software as a service, but also reciprocal knowledge exchange and joint staff training
  • 21. Integration of p-medicine tools in ECRIN clinical trial network
  • 22. Summary of evaluation results • Personalized medicine clinical trials is a new way of conducting clinical research • This doesn’t fit into the way conventional clinical trials are conducted • The main focus of clinical trials is standardization, to achieve high quality of data with large patient populations and many trial sites involved • The simple addition of personalized medicine tools into an operating clinical trials network doesn’t work • A new IT infrastructure, but also new knowledge and processes have to be supported • We suggest the reciprocal exchange of services as a way to make software tools for personalised medicine available, but also to gain by knowledge exchange, exchange of personnel, joint staff training, joint help, etc.
  • 23. wolfgang.kuchinke@uni-duesseldorf.de wokuchinke@outlook.de More information about the personalized medicine tools: www.p-medicine.eu Contact Wolfgang Kuchinke Heinrich-Heine University, Duesseldorf, Germany This presentation contains additional explanatory material for the workshop and Q&A session