Tools for personalised medicine in clinical trials. The implementation of clinical trials in personalized medicine is a different way of doing clinical research, compared to the standard way of large clinical trials aiming for statistical significance. Personalized medicine uses a 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. Basis for this approach is the progress of the study of the human genome and its variation over the last two decades. Especially advancements in automated DNA sequencing, PCR technologies and the use of expressed sequence tags (ESTs), cDNAs, antisense molecules, small interfering RNAs (siRNAs). But the adoption of personalized medicine requires an active and flexible and highly integrated infrastructure, which must allow the joining of many different competences and technologies. We asked the question: can the tools developed for personalized medicine in the p-pedicine project be employed effectively in a clinical trials network to support personalised clinical trials? We conducted an analysis of tool integration and the evaluation of tool usage requirements. Based on the survey results, the tendency for the clinical trial network ECRIN is to use software as a service in the form of SaaS or ASP. ECRIN data centres will (probably) not install and employ p-medicine tools in one of their data centres. A robust business model for the provision of services and the implementation and employment of tools does not yet exist. How can the personalized medicine infrastructure p-medicine and the clinical trials network ECRIN gain from each other to allow the conduct of personalized clinical trials? We suggest a business model, in which personalized medicine infrastructures and clinical trials networks exchange their services to gain jointly from each other. An integration of networks by reciprocal exchange of services may be the solution. Not only software as a service will be exchanged, but also knowledge, personnel and staff trainings.

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