Development%20of%20Specialized%20ICT%20Infrastructure%20and%20Services%20Oriented%20to%20Emerging%20Problems%20Typical%20for%20Synergistic%20Interaction%20of%20Multiple%20Diseases

1
Development of Specialized ICT Infrastructure
and Services Oriented to Emerging Problems
Typical for Synergistic Interaction of Multiple
Diseases

• M. Rakic, S. Nektarijevic, I. Milinkovic, G.
  Rakocevic, M. Bumbasirevic, V. Milutinovic, V.
  Lekovic (SRB)
• with
• L. Luic (CRO) M. Rudolf (SLO)

2

• Our Research Focus 5.3.b (iiii)
•  
• Development of ICT tools, services and
  specialized infrastructure for the bio- medical
  researchers to support at least two of the
  following three activities i) to share data and
  knowledge needed for a new integrative research
  approach in medicine (biomedical informatics),
  ii) to share or jointly develop multiscale models
  and simulators, iii) to create collaborative
  environments supporting this highly
  multidisciplinary field. When necessary,
  computing power and data management could be
  sought through access to existing advanced grid
  infrastructures as well as high performance
  computing resources such as the emerging
  petascale computing facilities. New tools,
  services and applications will also be evaluated
  on their effectiveness and their ability to
  interface with existing medical research
  infrastructures. Their targeted services will
  facilitate the clinical use of computer based
  organ and disease models as well as biomedical
  data. These tools and services will complement
  and be compatible with existing methods and
  standards (terminologies, ontologies, mark-up
  languages) like those used by the Network of
  Excellence VPH NoE (FP7-ICT-call 2).
  International Cooperation in this field is
  encouraged. The objective is to support at least
  one IP to be funded under b).
•  
• Our Competitive Advantage Data Mining
  Infrastructure On Top of All Above
• Our approach concentrates on all issues
  underlined above, plus an added value of crucial
  importance The infrastructure for data mining
  which enables a set of hypotheses to be defined
  and verified. Appropriate PoC implementations
  with contents from dentistry (with special
  emphasis on periodontal medicine) and orthopedics
  (with special emphasis on biomedics). Special
  emphasis research methodology oriented to rich
  statistical analyses.

3
Development of ICT Tools, Services, and
Specialized Infrastructurefor the Bio-Medical
Researchers to Support at Least Two of the
Suggested Three Activities

• i (integrative)
• iii (collaborative)
• Nota Benne
• ii (interface)
• ii (interaction)

4
Sharing Data and Knowledge Needed For a New
Integrative Research Approach in Medicine
(Biomedical Informatics)

• Sharing dataInfrastructure for institutional
  networking
• Sharing knowledgeDataMining SemanticWeb
  ConceptModeling

5
Create Collaborative Environments Supporting
This Highly Multidisciplinary Field, with Stress
on Synergistic Interaction

• Example 1 Interaction of periodontitis
  diabetes mellitus multiple sclerosis
• Example 2 Interaction of orthopedics risk
  factors impact therapy success rates

6
Interface With Existing Medical Research
Infrastructures

• Special emphasis on reusing of infrastructure
  developed through former FP projects
• Special emphasis on eliminating the trapsof
  reusing (six different trap scenaria)

7
Compatible with Existing Methods and Standards
(Terminologies, Ontologies, Mark-up Languages)
Like Those Used By the VPH Network of Excellence

• Tentative list of core participants

8
Our Competitive Advantage Data Mining
InfrastructureOn Top of 5.3.b (Added Value)

• Digital libraries include hidden knowledge
• Digital contents enable hypothesis testing

9
Enables a Set of Hypotheses to Be Defined and
Verified (Example)

• Defining risk factors common to periodontitis and
  investigated diseases. Using the parameters which
  are according to contemporary science found to be
  significant for investigated diseases, we will
  screen and link observed data including risk
  factors, characteristics, and findings related to
  patients.
• Investigating and defining the influence of
  periodontitis on the course of diseaseand on
  therapy success. By including systemic healthy
  patients with periodontitis, we will compare the
  clinical, immunological, microbiological and
  biochemical and other defined parameters between
  these systemic healthy and patients with MS and
  DM. Furthermore, by treating periodontitis of one
  part of ill patients, and by collecting post
  treatment specimens, we will determine the
  correlation between periodontal inflammation and
  systemic status.
• Using obtained findings for better understanding
  still insufficiently explained pathogenesis and
  in improving the therapy plan.
• Contributing to advancing and resolving the
  problem of three multifactor diseases,which are
  extremely wide spread and present in young
  population thus with great socioeconomic
  significance, by observing entire group of
  potential risk factors and indicators of disease.
• Providing new perspective and ideas to scientists
  and physicians fighting against these diseases.
• Creating a software trained on data, using most
  sophisticated contemporary techniques and chosen
  based on most recent and modern scientific
  achievements.
• Implementing software for determining the risk of
  diseases and deterioration worsening of disease
  conditions.
• Facilitating decisions relating treatment
• Helping in forecasting
• Improving knowledge

10
PoC

• Implementation
• Dissemination
• Analysis
• Beyond

11
Dentistry - PerioDontics

• Collecting and tracking of risk factors for
  about 100 different use cases
• Implementing the system and the procedures in 10
  different medical institutions
• Data sharing
• Knowledge mining (added value)

12
Medicine - Orthopedics

• TBD

13
Methodology Objectives (SC)

• Objective 1 To generate use cases for hypotases
  testing (patient groups and
  problem types), based on previous
  medical research experiences of the
  entire consortium
• Objective 2 To specify contents and parameters
  to be tracked
• Objective 3 To design infrastructure with
  elements of both computig and
  communications
• Objective 4 To develop a PoC and digital content
  for one specific field,
  applicable to a statistically large enough test
  base
• Objective 5 To select the datamining algorithms
  for analysis of test
  results.
• Objective 6 To test the demo system in a number
  of specific clinical
  scenaria, in one country (e.g., SRB).
• Objective 7 Same as above, in another country
  (e.g., CRO).
• Objective 8 Same as above, in a third country.
  (e.g., SLO)
• Objective 9 Final analysis and creation of
  recommendations for clinical
  practice all over Europe.
• Objective 10 Dissemination to centers all over
  Europe.

14
Methodology WPs (MS) Ts Ds

• The project can be organized in 11 work packages
  
•  
• WP0 Project management, RR
• WP1 Definition of use case scenarios, X
• WP2 Development of digital content, FRI
• WP3 Development of system infrastructure, OPTILAB
• WP4 Development of testing procedures, ETF
• WP5 Development of datamining algorithms
  for analysis of testing results, FHG
• WP6 Testing in environment A, SALERNO
• WP7 Testing in environment B, FERRARA
• WP8 Testing in environment C, KARLSTAD
• WP9 Final analysis and preparation of
  recommendations for clinical practice all
  over Europe, BSC
• WP10 Dissemination, MAXELER
• Specified work package leaders are tentative

15

• IP

16
Rich and Holistic Statistical Analysis

• WANTED
• Creative Partners From the Region to perform
  biomedical research to prove the concept, so we
  can perform a huge statistical analysis,
• andcover a large plethora of medical fields
• in financially competitive environments