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Interregional coordination for a fast and deep uptake of personalised health (Regions4Permed) – multidisciplinary consortium under the H2020 project.

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Abstract

Personalised medicine (PM) represents a paradigm shift away from the ‘one size fits all’ approach to the treatment and care of patients with a particular condition, to one which uses emergent technologies such as diagnostic tests, functional genomic technologies, and molecular pathway profiling to better manage patients’ health and employ target therapies. The current challenge for national and regional authorities is to facilitate the shift from a reactive healthcare system based on episodic and acute care models to a personalized health (PH) system that uses preventive and predictive measures, where at-risk individuals are stratified to intervene before the onset of symptoms or risk is predicted using cutting-edge technologies before symptoms appear. While PH is paving the way toward better and more efficient patient care, it still lacks the cooperation and coordination needed to organise the fragmented field, which is a severe drawback to its development and to the placement of effective financial investments. For this reason, it is crucial to direct major efforts towards coordinating and aligning relevant stakeholders across Europe and beyond, creating a participatory approach, building trust, enabling a multi-stakeholder process, and channeling investments towards PH. Thus, Regions4PerMed aims to coordinate regional policies and innovation programmes in PM and PH to accelerate the deployment of PH for patients.
Medical Science Pulse 2019 (13) 3
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Reviews DOI: 10.5604/01.3001.0013.5497
ABSTRACT
Personalised medicine (PM) represents a paradigm shift away from the ‘one size fits all’ approach to the treat-
ment and care of patients with a particular condition, to one which uses emergent technologies such as diagnostic
tests, functional genomic technologies, and molecular pathway profiling to better manage patients’ health and
employ target therapies. The current challenge for national and regional authorities is to facilitate the shift from
a reactive healthcare system based on episodic and acute care models to a personalized health (PH) system that
uses preventive and predictive measures, where at-risk individuals are stratified to intervene before the onset
of symptoms or risk is predicted using cutting-edge technologies before symptoms appear. While PH is paving
the way toward better and more efficient patient care, it still lacks the cooperation and coordination needed to
organise the fragmented field, which is a severe drawback to its development and to the placement of effective
financial investments. For this reason, it is crucial to direct major efforts towards coordinating and aligning
relevant stakeholders across Europe and beyond, creating a participatory approach, building trust, enabling a
multi-stakeholder process, and channeling investments towards PH. Thus, Regions4PerMed aims to coordinate
regional policies and innovation programmes in PM and PH to accelerate the deployment of PH for patients.
KEYWORDS: personalised medicine, personalised health, prevention, regional policies interregional cooperation
INTERREGIONAL COORDINATION FOR A FAST
AND DEEP UPTAKE OF PERSONALISED HEALTH
REGIONS4PERMED  MULTIDISCIPLINARY
CONSORTIUM UNDER THE H2020 PROJECT
G D’E1
P G C1
P B2
M D-S3
• ORCID: 0000-0003-1715-8958
A Z4
• ORCID: 0000-0002-1300-9229
D K4,5
• ORCID: 0000-0003-0255-7163
E-M S6
B A R7
J M R F7
D K8
• ORCID: 0000-0002-6996-8920
1 Fond azione Toscana Life Sciences, Siena, Italy
2 Fond azione Regionale per la Ricerca Biomedica, Milano, Italy
3 International Scientific Projects Section,
Wroclaw Medica l University, Poland
4 Lower Silesian Voivodeship Marshall Office, Wroclaw, Poland
5 Division of Medical Social Sciences,
Wroclaw Medica l University, Poland
6 Saxon State Ministry for Higher Education,
Research and the Arts, Dresden, Ger many
7 Galician Health Knowledge Agency ACIS,
Santiago de Compostela, Spain
8 Family Medicine Department,
Wroclaw Medica l University, Poland
A–study d esign, B–data c ollectio n, C–statistic al ana lysis, D–inter pretation of d ata, E–manusc ript prepa ration, F–liter ature rev iew, G–sourcing of funding
B
The Horizon 2020 Advisory Group has defined per-
sonalised medicine as “a medical model using charac-
terisation of individuals’ phenotypes and genotypes
(e.g. molecular profiling, medical imaging, lifestyle
data) for tailoring the right therapeutic strategy for
the right person at the right time, and /or to determine
the predisposition to disease and/or to deliver timely
and targeted prevention” [1].
Scientif ic evidence shows that a change in the model
from “high-risk population models” to a “whole pop-
ulation model” [2] would allow huge gains, both for
patients in term of health and for healthcare systems
in terms of cost reduction. In this context, personal-
ised medicine becomes a basic/translational research
approach. Moreover, as we develop a system that uses
data and technology to provide personalised care, the
concept of personalized medicine broadens and needs

Interregional coordination for a fast and deep uptake of personalised health (Regions4Permed)...
Medical Science Pulse 2019 (13) 3
to include variables such as polic y, regulation, industry,
technologies, and patient associations. A better use of
data and technology has the power to improve health
and to improve the quality of health and care services
while simultaneously reducing the cost.
Regiona l ecosystems are increasingly characterised
by strong leadership, a culture of openness and learn-
ing, and commitment to being ‘data-driven’. This is a
critical observation because in countries where health
policies are shaped and applied at the federal level,
regions are the focal point in the process of transform-
ing European health and care policies towards sustain-
able and resilient systems.
Scientif ic and technological advancements need ade-
quate, communit y-tailored polic y frameworks that ena-
ble uptake of personalised medicines and health. Deep
knowledge of the demographic, epidemiological, aca-
demic and industrial context of the healthcare system,
together with its financial capacities, allows regions to
plan and implement strategic investments to adapt and
modernise key enabling health infrastructures. The
possibility to establish joint collaborations with other
EU regions reinforces their capacities and multiplies
impacts while minimising risks. In addition, these col-
laborations can pave the way to the setting of transna-
tional a nd transregional models for healthcare that can
be replicated in less developed regions and countries thus
empowering citizens and patients. At a regulatory level,
cross-reg ional collaborations are the key to increase data
interoperability and to multiply the impact of health
investments while ensu ring adequate levels of training
for health professiona ls. This effor t will eventu ally result
in a reduced burden from chronic disease, enhanced
capacity for disease prevention, and it will support
the development of new medicines and treatments.
Taken together, then, the real challenge for national
and regional authorities is to tackle the shift from a
reactive healthcare system based on episodic and acute
care models to a preventive and predictive health care
system. The preventative and predictive health care
system is one that stratifies at-risk individuals and
ensures that preventive action is taken to intervene
well before the onset of symptoms and one that lever-
ages and integrates cutting-edge technologies to not
only stratify r isk but to predict risk and intervene even
before symptoms appear.
In the face of this potential huge leap forward,
personalized health (PH) lacks the cooperation at the
regional, interreg ional, and intergovernmental level to
coordinate and to organise an adequate level of policy
and investments. This represents a severe drawback
to effective PH development. For this reason, major
efforts need to be directed toward coordinating and
alig ning regional stakeholders like public institutions,
governments, industry, civil society, and patient organ-
isations into action across Europe and beyond in order
to create a participatory approach, build trust, ena-
ble a multi-stakeholder process, and channel invest-
ments towards PH.
The administrative structure of countries, i.e. the
competencies and the autonomy of the regions, accounts
for the diversity of the regional innovation strateg y for
smart specialization (RIS3s). For example, regions that
have responsibi lities in the hea lthc are system can add ress
PH more globally, linking research and health policies.
One recognised added va lue of RIS3 is the association of
policy makers, industries, public stakeholders and the
breaking up of data si los through top-dow n strategies.
These considerations are taken into account by
European policy makers. In order to assess the status
of interregional coordination in PM, a workshop was
organised in Brussels on May 4, 2017, by the European
Commission w ith the aim to compare the regiona l strat-
egies on PM and to:
Disseminate information on the role of personal-
ised medicine in regional R&I Smart Specialisa-
tion Strategies (RIS3) on European PM activities
and on the International Consortium for Person-
alised Medicine (ICPerMed).
Excha nge information a nd views on how PM is pri-
oritised at the regiona l level and on how R&I act iv-
ities are being implemented at a regional level.
Identify needs and possibilities for interregional
cooperation and synergies for PM R&I.
Identify information gaps and needs for further
data collection/analysis.
Within the workshop, some main challenges have
been identified which Regions4PerMed will address:
Establish a platform and initiative to facilitate
interregional cooperation in PM.
Organise and employ infrastructures, pro-
grammes and financial instruments in a way
that brings together all relevant stakeholders
(public authorities, SMEs-Small and Medium-
sized Enter prises, universities, healthcare provid-
ers, etc.) and that creates a favourable ecosystem
for the development and the implementation of
personalised medicine.
Support the ICPerMed network (the Internationa l
Consortium for Personalised Medicine) in facili-
tating a fruitful d ialogue between regions, hea lth
ministries and research funders.
Implement reflection and actions to organise
the flow of information, share experience, iden-
tify barr iers, spread good practice, and facilitate
dialogue and cooperation between regions. This
should include the organisation of simi lar events
that involve more regions.
Seek tighter contacts between the regions and
the Programme Committee for the specific pro-
gramme implementing H2020 (Configuration
‘Health , demographic chan ge and well-being ’) [3].
O   P
Regions4PerMed s overarching goal is to set up the
first interregional cooperation on PM, alig n strategies
and financial instruments, identify key investment
 G D’E, P G C, P B, M D-S, A Z,  .
www.medicalsciencepulse.com
medical big data and health medical records, connected
health in terms of better system integration and patient
management, health industry in the context of health-
care innovations, facilitation of the innovation flow in
the healthcare and socio-economic aspects rationa le.
Regions4PerMed establishes a continuous dialogue
among the European PM community. It brings together
regional authorities that primari ly take decisions, aca-
demics and stakeholders within organised cross-secto-
ral and cross-regional workshops and conferences on
the five key thematic areas.
This dialogue is organised into five steps:
1. Elaboration of a preparation paper which anal-
yses the state-of-the-art aspects and highlights
the challenges of each Key Strategic Area.
2.
Organise a thematic interregional workshop
around the topic. Carry out five capacity-build-
ing workshops for regional author ities in order to
build up expertise and skills within the regional
authorities about the use and ex ploitation of the
knowledge created within Regions4PerMed.
3.
Organise five conferences in different regions and
cities in order to have a wider geographical out-
reach, plus the kick-off and the final conference.
4. Carry out two in situ visits for each Key Strate-
gic Area to highly innovative labs, institutes or
companies and gather innovative models and
best practice examples.
5.
Issue a workshop report containing, among others:
a.
Policy recommendations for European, national
and regional policy makers.
b. R&D investment recommendations.
c. Innovation models and best practices.
The methodology sought in order to achieve the
project objectives is based on the organised technical
dialogue with relevant stakeholders [4].
K   
   
1. Medical Big Data, Electronic Health
Records and Health Governance
Technological innovation has triggered an explo-
sion in data production that will soon reach exabyte
proportions. There is great potential for “big data” to
improve health, but at the same time, “big data” also
engenders new challenges. One emerging challenge is
the issue of capacity, where the amount of data gener-
ated wil l strain the infrastr ucture of an individual hos-
pital or institute. Integrated solutions for data sharing
and analysis will need to allow for the combination of
data coming from multiple sources and potentially dif-
ferent research disciplines. At the European level, one
of the main hurdles is the construction and sharing of
a common data storage platform for research pur poses.
Service models need to be developed in order to deliver
better health care and strengthen the health industry.
areas and release a European regional agenda in order
to foster the delivery of PH services to patients and cit-
izens. The consortium was established to:
Support the coordination of regional policies
and innovation programmes in PM in order to
accelerate the employment of PM for citizens
and patients.
Strengthen cooperation between Horizon 2020
and ESIF on PM aspects.
Ensure complementarity bet ween RIS3 diagnos-
tics priority and R IS3 personalised medicine pri-
ority mappings.
Establish a permanent dialogue between Euro-
pean regions regarding a fast and full implemen-
tation of PM.
Strengthen industrial specialisation areas in
Europe and allow PM to flourish as an emerg-
ing industry.
Enable interregional joint investment on PM
including a stable link with the Vanguard Initia-
tive and with the European Innovation Council.
Provide guidance to the EC for the next Multi-
annual Financial Framework (MFF) as well as
Research Framework Programme.
Provide guidance to EC, Member States and
regional authorities on the next European Struc-
tural and Investment Funds (ESIF) Operational
Programme.
The other specific objectives of the project are:
Organise the technical dialogue among regions
around five Key Strategic Areas (KA) and through
five thematic workshops.
Provide a final action plan of strategic areas of
investments.
Establish a HUB of European initiatives and
partnerships on personalised medicine (PerMed
HUB).
Contribute to the realisation of the IC PerMed
action plan.
Provide guidelines in the form of a report to
regional authorities on how PM can boost local
economies and keep the EU competitive.
Provide guidelines in the form of a report on how
to address PM within the Smart Specialisation
Strategies (RIS3).
Build and mainta in a database of PH research and
innovation and monitor programmes and pro-
jects that can be easily replicated elsewhere [4].
M
At the core of the project are five regional authori-
ties and organisations representing European regions
strongly committed to PM and the Wroclaw Medical
University as an academic partner of the consortium.
These authorities act as the Executive Board for the
interregional coordination and are mainly responsi-
ble for the implementation of the project act ivities con-
centrated around the five key strategic thematic areas:

Interregional coordination for a fast and deep uptake of personalised health (Regions4Permed)...
Medical Science Pulse 2019 (13) 3
Big data technology has many appl ications in health-
care, such as predictive modelling, clinical decision
support, disease or safety surveillance, public health,
and research. Big data analytics frequently exploit
analytic methods developed in data mining like clas-
sification, clustering, and regression. Technologies
that can extract large quantities of data from sam-
ples or biopsies are permitting discovery of previously
unknown disease factors, which may be utilised as
drug targets or disease biomarkers. Data is also able
to expose the complexity of a disease, especially can-
cer, and it can highlight the fact that there will never
be one drug or treatment option that works for every
patient. Through the “datafication” of patient tissue
samples and genomic fingerprints, clinicians can sys-
tematica lly extract more information from each patient
without requiring multiple rounds of testing. By having
all available information at the same time while deter-
mining diagnosis and the patient prognosis, the best
treatment decisions can be made on an ind ividual basis
at a faster rate. National health systems are heteroge-
neous in terms of the level of government influence,
main source of financing, and main levels of organiza-
tion. Some systems, for example, are self-gover ned as in
Germany, some have regional autonomy, while others
are national systems. Moreover, some systems are tax-
financed and some deduct a fee from monthly income.
Hence, solutions and fundamental approaches differ
between European member states and are not entirely
portable and scalable.
As recalled in the EC Communication on digital
health, health care systems in Europe face serious chal-
lenges [5] such as ageing, chronic disease, multi-mor-
bidity, health workforce shortages, the rising burden
of preventable, non-communicable diseases caused by
risk factors such as tobacco, alcohol, and obesity, as well
as other neuro -degenerative or rare diseases [6]. Public
spending on health and long-term care is steadily ris-
ing in EU Member States and is expected to continue
to do so. In 2014, the EU-28’s total healthcare expend-
iture was €1.39 trillion (10% of the EU’s GDP). This
is expected to increase to 30% by 2060. These trends
pose significant problems for the sustainability of EU
Member State health care systems.
Even though the health sector is data intensive,
the data has been underutilized for enhancing pub-
lic interests.
While health data is available in various forms
and formats, it is not managed in the same way by all
EU Member States, nonetheless within an individual
national health system. Furthermore, health data is
often difficult to access by patients themselves or by
medical staff or researchers that develop and deliver
better diagnoses, t reatments or personalised care. Even
where it exists, health data often depends on technol-
ogies that are not interoperable, thus hindering its
wide-spread use [5].
Big data is also becoming a crucial tool for leading
companies to outperform their peers. T his is especially
true in the health sector where the quality, availabil-
ity, and accessibility of health-related data is vital to
maintain a competitive stake in the European health
industry, in which medical technologies can boost the
economy, employment and efficiency of health care
system as a whole.
Among the technical challenges to be solved is the
lack of standards applicable to collecting, analysing
and storing data. Additionally, the potentia l for health
funding agencies to promote standardisation is still
untapped even though standardisation also affects the
technological developments and the industr ial compet-
itiveness of the health industry.
Big data and digita lisation can support measures to
promote health and prevent disease, as well as to reform
health systems, ease the transition to new patient-
centred care models, and to integrate new care struc-
tures [7,8].
The aim of this Work Package is to explore all the
potential, the risks and the roles that regions can play in
the governance process of health data, focusing on Elec-
tronic Health Records (EHR) and health research data.
Data can be a key enabler of digital transformation
and development of new forms of technology, to ben-
efit patients and healthcare staff, and to aid medical
research and health technologies industries. Nonet he-
less, the increasing amount of data and the collection,
storage, access and protection of the data have created
numerous legal, economic and ethical issues. Current
national legislations struggle to manage these issues
and are tr ying to find a common ground for regulating
IT technology and its impact on citizens.
Big data technology has a variety of healthcare
applications, such as the creation of electronic med-
ical records (EMRs), predictive modelling and clin-
ical decision support, disease or safety surveillance
and research. Big data analytics frequently exploit
analytic methods developed in data mining, includ-
ing classification, clustering, and regression [9]. A
recent article published in Science
[10] highlighted
the potential healthcare applications of big data. The
UK Biobank recently made a systematic analysis of
the full genotyping data of 500,000 people available
to 7000 registered researchers. The UKB data is being
used for 1400 projects and has resulted in nearly 600
published papers, focusing on the link between gene
variants to a disease or trait such as arthritis, type 2
diabetes, depression, neuroticism, and heart disease,
for example.
If PH is to be realised, tremendous amounts of data
specif ic to an individual must be captured, synthesised
and presented in an analysed form to clinicians when
care decisions are needed. This can only be accom-
plished by using sophisticated EHR systems that are
designed to support this function. By having all avail-
able information at the same time while determining
diagnosis and patient prognosis, it would be possible
to ensure the best and most timely treatment decisions
on an individual basis.
 G D’E, P G C, P B, M D-S, A Z,  .
www.medicalsciencepulse.com
On a larger scale, a joint declaration on artificial
intelligence was recently signed to create a cloud infra-
structure for data sharing to ensure Europe’s compet-
itiveness in the research and deployment of AI and to
deal with the associated social, economic, ethical and
legal questions. On the heels of this declaration, the
new General Data Protection Regulation (GDPR) was
initiated and it influences the exploitation of big data
in healthcare. Among others, some big data challenges
to be addressed are 1) how to enable cross-border data
exchange, 2) how to promote legal, organisational,
semantic and technical interoperability, 3) alignment
of the OECD counci l recommendations and EU privacy
regulations, 4) creation and dissemination of codes of
conduct on how to handle secondar y data use and how
to de-identify patient data for secondary use [4]. Other
challenges that emerged throughout the year of new
big data initiatives were the need to invest in staff and
not just infrastructure and the need to demonstrate
the benefits of big data.
2. Connected health: Better system
integration and patient management
With many personal human genome map initiatives
launched worldwide (Personalised Medicine Initiative
in the USA, 100.000 Genomes Initiative in the UK and
the Mil lion European Genomes Alliance in Europe), it is
possible to envision a future where treatments are tai-
lored to individuals’ genetic structures, prescriptions
are analysed in advance for likely effectiveness, and
researchers study clinical data in real-time to deter-
mine success. The implementation of these regimens
will create a situation where treatments are better tar-
geted, health systems save money by identifying ther-
apies not likely to be effective for a particular patient,
and researchers have a better understanding of com-
parative effectiveness [11].
Yet, despite these benefits, consumer and system-
wide gains remain limited due to an outdated policy
regime. With scientific innovation running far ahead
of public policy, physicians, researchers, and patients
are not receiving the full benefits of the latest develop-
ments. Current policies need to leverage new advances
in genomics and PM in order to individualise diagno-
sis and treatment. Similarly, policies creating incen-
tives for the adoption of health information technolog y
should ensure that the invested infrastructure is one
that supports new-care paradigms as opposed to auto-
mating yesterday’s health care practices.
European health systems require a seamless and
rapid flow of digital information, including genomic,
clinical outcome, and claims data. Research derived
from clinical care must feed back into assessment in
order to advance care quality for patients. Currently,
there is discrete data on diagnosis, treatment, medi-
cal claims, and health outcomes that exists in parts of
the system, but it is hard to deter mine what works and
how treatments differ across subgroups. As more infor-
mation on treatment, lab tests, genomics, and costs
is integrated into healthcare, it is hard to incorporate
data from medical history, vital signs, genetic back-
ground, and lab testing into diagnosis and treatment.
Predictive modelling represents a way for physicians
to move towards systematic and evidence-based deci-
sion-mak ing. While the first step toward enabling per-
sonalised medicine is to ensure clinicians have access
to what is known about patient gene variants, com-
puter models can go beyond this approach and predict
which treatments are likely to be most effective given
observed symptoms. Public policy should incorporate
rapid learning and predictive modelling to gain the
full benefits of PM.
Concerning the emergence of Artificial Intelligence
(AI), it is necessary to deal with its effects on the trans-
formation of the market in an appropriate and contem-
porary way. An environment of trust and accountability
including analysis of new lega l and ethical questions will
permit healthcare systems to benefits fully from AI.
Finally, the combined intellect of the leading Euro-
pean experts in e-health and m-hea lth (mobile hea lth)
is required to identify future approaches to e-health/
m-health that can redefine ways of interaction within
the healthcare system. All mentioned connecting sys-
tematic approaches and platforms require consented,
open and interoperable connections that follow inter-
national standards. This does not only apply to exist-
ing aspects, e.g. IHE profiling, but also to defining new
standards on topics like cross-platform authentication
and data exchange. Standardisation in healthcare ser-
vices is a major requirement for improv ing patient treat-
ment by way of modern technology.
All this considered, the second phase of the pro-
ject will address:
m-/e-health technologies for continuous moni-
toring and self-empowerment;
m-/e-health technologies for data integration;
AI for predictive models;
Personal data management;
Remote monitoring and tele-assistance.
One of the main goals of this phase is the employ-
ment of medical data registered systems. Addition-
ally, this phase aims to increase big data capacity to
solve such problems as the poor quality of collected
medical data, like weak or insufficient, incomplete,
or incorrect data, or data saved in various formats,
for example. Big data could also improve medical pro-
fessional and patient awareness regarding medical
event documentation and could provide diagnostic
support and therapy personalisation through the use
of AI. It could also support the creation of informa-
tion and communication technology (ICT) systems for
data collection and their enhancement for PM in Euro-
pean regions, enabling a persona lised approach to inte-
grated care for the elderly based on the use of intelligent
ICT solutions.
The other goal considered in this phase is to increase
knowledge and to strengthen the involvement of citi-

Interregional coordination for a fast and deep uptake of personalised health (Regions4Permed)...
Medical Science Pulse 2019 (13) 3
zens and communities in the monitoring system; meas-
urable /inadequate use of ICT is the result of inadequate
access to medical data and lack of trust in its quality.
Also, integrated care for patients with multiple dis-
eases is going to be discussed in this phase using Multi-
Criteria Decision Ana lysis (MCDA). MCDA will account
for understanding care-focused people, improv ing the
health and well-being of citizens through integrated
health care, implementation of integrated care systems,
innovative models of integrated care and systems, and
assessment and improvement of monitoring quality.
Implementation of this new model of integrated care
needs to occur quickly to meet the increasing demand
for such care due to the aging of the European pop-
ulation and the increase in vulnerability, cognitive
impairment and chronic diseases associated with the
aging process [4].
3. Health industry: Driving healthcare
innovations
Currently, a diagnosis is made using tests and inves-
tigations of a patient’s symptoms. However, while two
patients might share the same symptoms, the underly-
ing cause could be dif ferent. Knowledge of an individu-
al’s complex molecular and cellu lar processes, informed
by other clinical and diagnostic information, will help
to more fully determine the true cause of the symp-
toms. Precision diagnoses can be further optimised
when coupled with new technologies such as those that
provide rapid and real-time results and those that can
be used at the point of care.
These technological developments have the poten-
tial to significantly change the way that the health
industry operates to the benefit of the patient. Due to
an ageing population and the current increase of life-
style-related diseases, the cost of healthcare is ex pected
to increase significantly. The healthcare industry is
among the fastest growing industries and it is expected
to continue its significant growth. The further devel-
opment of PM and especially of PH has the potential to
cause a quantum leap in respect to the efficienc y of the
healthcare system and to ensure its long-term sustain-
ability. The developments in PM and PH may change
the entire way the healthcare industry operates, shift-
ing toward pred iction and prevention of disease instead
of curative treatments.
To enable this drastic change in how the hea lthcare
industry operates, several steps need to be taken. First,
there is a need to distinguish health research from clin-
ical practice. Mechanisms to connect data from multi-
ple sources into databases for secondary research use
and population cohort ana lysis need to be established.
It is nearly impossible to evaluate treatment effective-
ness without being able to agg regate data and compare
results, thus big data needs to be accessible and usable.
Faster knowledge management could enable physicians
and public health officials to employ “rapid learning
models and evidence-based decision-making. Funda-
mental innovations often flow from basic research to
clinical studies to different scaling-up stages; it is the
task of policy makers to facilitate this process by pro-
viding the necessary framework for successful transla-
tion especially where innovations may have a disruptive
character on current healthcare processes. This holds
true for several relevant aspects:
Exchange of research data, including data inter-
operability and access to databases.
Intellectual property rights, its tangibility and
exchange.
Transfer of relevant information between neu-
tral market actors like net working agencies, non-
governmental organizations (NGOs), and public
or governmental consulting bodies.
Entrepreneurial activities, foundation of SMEs,
exit strategies.
Private venture capital, public sources of capi-
tal to ease market access or change of market.
Reimbursement policies regarding innovative
technologies or processes and their introduction
to state-paid or self-governed systems.
It is furthermore necessary to broaden the widely
accepted, but narrow view on the costs and benefits of
introducing e-health/m-health and of implementing a
PH approach. Healthcare industry partners, SMEs and
research institutes would greatly benefit from a coor-
dinated European approach to include quality of life
and systemic outcome measurements in the cost-ben-
efit analysis. Ultimately, the value of preventive and
predicative approaches needs to be assessed in light of
possible reimbursement policies for these approaches
to make them financially more attractive when com-
pared to the current primarily curative approaches.
Also, even discounting spin-offs, a major share of
innovation is created by SME’s. SMEs are therefore cru-
cial for the fur ther development of the health industr y.
They have a significant role in the following fields:
a. Diagnostics such as in vitro diagnostic devices
(IVDs), genomic diagnostics, biomarkers, medi-
cal devices, and imaging.
b. Technological transfer.
c. Disease management innovative tools.
d.
New business models for a wider health mar-
ket uptake.
e. Payment models.
This key strategic area will be elaborated in the
third workshop and will impact clinical studies, joint
research, standardisation, Living Labs, training, tech-
nology transfer and demonstration activities [4].
4. Facilitate the innovation flow in
healthcare
PM must play a decisive role in the long-term sus-
tain ability of health s ystems. The one-treatment-ser ves-
all-patients traditional approach seems unsustainable,
inefficient, and it offers low-value interventions to
patients. Implementation of PM has the potential to
 G D’E, P G C, P B, M D-S, A Z,  .
www.medicalsciencepulse.com
reduce financial and time expenditures and to increase
quality of life and extend the lives of patients. This
next technological revolution – the technology rede-
fining the healthcare industry of the future – com-
bines highly powerf ul biotechnologies like biomarkers,
genetics or proteomics with vast amounts of available
data, cloud computing ser vices, machine learning, ar ti-
ficial intelligence (AI)-based or similar ICT solutions.
Together, these provide expert insights and highly va l-
uable information to support clinical decision at a rel-
atively low cost. Presently, connected medical devices
and highly innovative diag nostics together with strati-
fication technologies are already transforming the way
the healthcare industry works. The widespread adop-
tion of technology-enabled care will ensure that the
concept of the “Smart Hospital” becomes a reality. The
industr y appears ready to deploy these technologies in
large healthcare settings, but open-minded healthcare
organisations are also needed in order to pave the way
for the future. Some regional and national systems
have already created innovation tools like Innovative
Procurement and screening programmes to facilitate
the adoption of these technologies in routine hospi-
tal practices. Other healthcare organisations are cre-
ating and refining systems to increase and accelerate
the innovation flow around PM in their facilities. Hos-
pitals are also favouring links with industry through
their research and innovation infrastructures. Impor-
tant lessons lea rned from all these experiences w ill help
to accelerate the adoption of PM technologies across
Europe. They should also contribute to the definition
of new policies and investment decisions at European,
national and regional level. The fourth workshop will
invite leading organisations and experts with success-
ful programmes and experience in the adoption of PM
technologies by healthcare organisations, and it will be
organised around five sub-areas:
a.
Research & Innovation infrastructures exploi-
tation models to boost innovation
b. Innovative Procurement Tools (PCP & PPI)
c. Screening and prevention programmes
d.
Procurement based on clinical outcomes from
PM technologies
e. Smart and future hospitals [4].
5. Socio-Economic Aspects Rationale
From an economic point of v iew, persona lised health,
intended as a paradigm shift from a reactive to a pre-
ventive and predictive hea lthcare, poses some concerns.
Massive financial investments are required to mod-
ernise the European health systems and personalised
health needs to become a new driver for the economy as
building and automotive sectors have been in the past
century. Investment policies should facilitate the inte-
gration of different industrial sectors. The transition
to personalized health will also help to achieve hea lth-
care sustainably, which is currently a major chal lenge.
Another major concern is the possible inner dis-
crimination of personalised health and the necessary
mitigation by policy interventions. In fact, as PH poten-
tially offers 1-to-1 services, the costs tend to increase
and the access to the best care available might be ham-
pered. Therefore, in order to guarantee the social and
economic sustainability of healthcare, according to
Prof. Borgonovi [12], PH needs to produce changes in
A) training/education, in training new managers and
professional figures; B) vertical integration between
basic, translational research, technological development
and innovation processes; C) empowering patients and
citizens; 4) guaranteeing interdisciplinary approaches.
In the last ten years, as the technology and promise of
personalised medicine developed, bioethics scholars
began to contemplate the ethical, legal, economic and
social implications of the applications of this approach
to medicine, forming the field of investigation known
as ‘ELSI’ scholarship. Some of the foundational issues
considered were safety and efficiency, informed con-
sent, access to PH and reimbursement. In recent years,
technologies such as next-generation sequencers and
gene expression assays have become less expensive and
more suitable for clinical application, and as a result,
personalised medicine has become established in a
growing number of clinical areas. With these clinical
applications, however, the implications of personalised
medicine have expanded in scope and complexity. This
trend is likely to continue in the coming years, with
wider adoption throughout the hea lthcare system cre-
ating a need to broaden the focus of ELSI scholarship.
Finally, PH needs to guarantee that the criteria of the
so-called Responsible Research and Innovation are met
regarding public engagement, gender, ethics, and open
science. Additional ly, principles l ike social justice/inclu-
sion, sustainability, privacy, transparency etc. are to
be respected. According to the 1st Interregional Work-
shop on personalised hea lth in Milan on April 11, 2018,
personalised health in terms of RRI needs to guaran-
tee data access and control, avoid excessive claims and
promises from research findings and avoid genetic dis-
crimination and misuse of genetic profiling. This Key
Strategic Areas will explore regional challenges from
the following points of view:
a. Regulatory
b. Economics
c. Cultural
d. Responsible Research and Innovation
e. Gender discrimination [4].
E 
The most important impact of Regions4PerMed will
be a strengthening of links between European regions
setting up or planning persona lised medicine healthcare
approaches. This will be achieved by ensuring regional
representatives interact directly with each other, shar-
ing activities, plans and strategies on PM, exchanging
views and concerns, finding fields of cooperation, and
finally, committing themselves to concrete joint coop-
eration actions in the short-medium term.

Interregional coordination for a fast and deep uptake of personalised health (Regions4Permed)...
Medical Science Pulse 2019 (13) 3
R
1.
Backg round, conference report s, publications and lin ks related
to person alise medi cine [cit. 20.08. 2019]. Ava ilable from UR L:
https://ec.europa.eu/research/health/index.cfm?pg=policy&
policyname=personalised.
2.
Tamang S, Milstein A, Sørensen HT, Pedersen L, Mackey L,
Bette rton JR, et a l. Predict ing patient ‘cost bloom s’ in Denmar k:
a longitudinal population-based studyBMJ Open 2017; 7:
e011580.
3. Health, demographic change and wellbeing [cit. 20.08.2019].
Available from URL: https://ec.europa.eu/programmes/
horizon2020/en/h2020-section/health-demographic-change-
and-wellbeing.
4.
Regions4PerMed – Interregional coordination for a fast and
deep upt ake of persona lised hea lth [cit. 20.08.2019]. Ava ilable
from URL: https://www.regions4permed.eu/.
5.
Communication from the Commission to the European
Parliament, the Council, the European Economic and Social
Commit tee and the Commit tee of the Region s on enabling the
digital transformation of health and care in the Digital Single
Market; empowering c itizens and bu ilding a hea lthier societ y,
COM(2018) 233 final [cit. 20.08.2019]. Available from URL:
https://ec.europa.eu/transparency/regdoc/rep/1/2018/EN/
COM-2018-233-F1-EN-MAIN-PART-1.PDF.
6.
Global d isease outbrea ks [cit. 20.08. 2019]. Available f rom URL:
http://reports.weforum.org/global-risks-2016/global-disease-
outbreaks/?doing_wp_cron=1516386480.46225190162658
69140625.
7. Ministerial Statement: the next generation of hea lth reforms.
OECD Health Ministerial Meeting 17 January 2017 [cit.
20.08. 2019]. Available f rom URL: htt ps://ww w.oecd.org /health /
ministerial-statement-2017.pdf.
8. World Health Organisation. WHO global strategy on people-
centred a nd integrated hea lth services, 2015 [cit. 20 .08.2019].
Available from URL: https://apps.who.int/iris/bitstream/
handle/10665/155002/WHO_HIS_SDS_2015.6_eng.pdf.
9.
Lee Ch, Yoon HJ. Medical big data: promise and challenges.
Kidney Res Clin Pract 2017; 36(1): 3–11.
10. Kaiser J, Gibbon s A. Huge trove of Br itish biodat a is unlock ing
secret s of depression, se xual or ientation, and more , Jan. 3, 2019
[cit. 20.08. 2019]. Available f rom URL: htt ps://w ww.sciencem ag.
org/news/2019/01/huge-trove-british-biodata-unlocking-
secrets-depression-sexual-orientation-and-more.
11.
Preside nt’s Council of Adv isors on Scienc e and Technology, 2010
[cit. 20.08. 2019]. Available f rom URL: htt ps://obamawh itehouse.
archives.gov/the-press-office/2015/11/23/presidents-council-
advisors-science-and-technology-releases-report.
12. Adi nolfi P, Borgonovi E, e d. The myth s of health care. Towa rds
new model s of leadership a nd manageme nt in the healt hcare sec-
tor. Mila no, Italy: Univ ersity Luig i Bocconi Dept of Pol icy Ana ly-
sis & Public Mgmt (Springer International Publishing); 2018.
Commitment is crucial for any real and lasting
impact. Therefore, the Consortium will maximise its
efforts and leverage already established projects and
initiatives.
Stakeholders relevant to PM in each region and
Europe-w ide will come together in the frame of Regions-
4PerMed and exchange best practice as wel l as highlight
the key challenges ahead. The continuous technical
dialogue through preparatory papers, thematic work-
shops, and on-site visits will thus ensure policy mak-
ers receive the best possible information and advice,
and in consequence, will minimise risks to PM employ-
ment on the political level. Regional representatives
will have the opportunity to understand how other
EU regions are tackling relevant challenges, get state-
of-the-art analyses from relevant stakeholders, share
views and update policies, contribute to shaping a com-
mon agenda, and identify common investment areas.
Overall, this will result in a coherent, science-
founded basis for decision-making [4].
Word count: 5142 • Tables: – • Figures: – • References: 12
Sources of funding:
The Coordination and Support Action Regions4PerMed has received funding from the European
Union’s Horizon 2020 research and innovation programme under grant agreement No 825812.
Conflicts of interests: The authors report that there were no conflicts of interest.
Cite this article as:
D’Errico G, Cormio PG, Bello P, Duda-Sikuła M, Zwief ka A, Krzyżanowski D,
Stegemann E-M, Allegue Requeijo B, Romero Fidalgo JM, Kurpas D.
Interregional coordination for a fast and deep uptake of personalised health
(Regions4Permed) – multidisciplinary consortium under the H2020 project.
MSP 2019; 13, 3: 60–67.
Correspondence address:
Donata Kurpas, MD, PhD, Assoc Prof.
Wroclaw Medical University
ul. Syrokomli 1, 51-141 Wrocław, Poland
Phone: (+48) 606 323-449
E-mail: dkurpas@hotmail.com
Received: 30.08.2019
Reviewed: 18.09.2019
Accepted: 30.09.2019
... The Interregional Coordination for a fast and Deep uptake of Personalised Health (Regions4PerMed [6,7]) main goal is to increase the involvement of relevant stakeholders (regional authorities, researchers, policy makers, and cluster organisations) for the implementation of personalised health. another predominant goal is to set up the first interregional cooperation on PM, align strategies and financial instruments, identify key investment areas, and release a european regional agenda in order to foster the delivery of PM services to patients and citizens. ...
... at the core of the project are five regional authorities and organisations representing european regions strongly committed to PM and the Wroclaw Medical university as an academic partner of the consortium. These authorities act as the executive board for the interregional coordination and are mainly responsible for the implementation of the project activities concentrated around the five key strategic thematic areas [6]. ...
... Technological innovation has triggered an explosion in data production that will soon reach exabyte proportions. There is great potential for "big data" to improve health, but at the same time, "big data" also prompts new challenges [6]. The main barriers in this strategic area are that the technologies to store and analyse big data and the ability to model them are not fully developed yet. ...
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Personalised medicine (PM) is the adaptation of medical treatment to an individual patient. More importantly, PM offers the potential to detect disease earlier when it is easier to treat effectively. PM is beginning to overcome the limitations of traditional medicine. In PM there are many potential benefits and facilitators but also many barriers. The goals of the Regions4PerMed project are to set up the first interregional cooperation on PM, align strategies and financial instruments, and most importantly, identify primary barriers in personal medicine adoption in the health care system and systematic actions to remove as many of them as possible to create a future where PM is fully integrated into real life settings. Each key action activity will be followed by a focus group or semi-structured qualitative interview. The questions asked during the research will concern barriers and facilitators of PM implementation in the country of a subject and will concern: medical big data and electronic medical records; health technology in connected and integrated care; the health industry; facilitate the innovation flow in health care; socio-economic aspects. The qualitative study outcomes are supposed to bring more qualitative data to the discussion. They could be implemented to the daily practice of the health care system’s stakeholders through the best practices transferred to all five key strategic areas of the Regions4PerMed project.
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Communication from the Commission to the european Parliament, the Council, the european economic and Social Committee and the Committee of the Regions on enabling the digital transformation of health and care in the Digital Single Market; empowering citizens and building a healthier society
Communication from the Commission to the european Parliament, the Council, the european economic and Social Committee and the Committee of the Regions on enabling the digital transformation of health and care in the Digital Single Market; empowering citizens and building a healthier society, CoM(2018) 233 final [cit. 20.08.2019]. available from URl: https://ec.europa.eu/transparency/regdoc/rep/1/2018/en/ CoM-2018-233-f1-en-MaIn-PaRT-1.PDf.