Modeling Pre-clinical Diagnostics Test Using System Dynamics Leeza Osipenko PhD Colloquium 22 nd System Dynamics Conference Oxford, UK July 25, 2004. Outline. Introduction Research Topic Pre-clinical Diagnostics ELIP test Previous Work in the Field Research Methodology
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Modeling Pre-clinical Diagnostics Test Using System DynamicsLeeza OsipenkoPhD Colloquium22nd System Dynamics ConferenceOxford, UK July 25, 2004
Stage 1Stage 2Stage 3
Quiet period – a person thinks he’s healthy-no signs of sickness, but anover- or under-production of auto-Abs starts to occur to cause a disease in the near future
Sickness is determined – a person might still feel fine, but the doctors are capable of detecting an illnessusing conventional methods
A Sick Person – A patient complains
about an illness, doctors make a
diagnosis and begin the treatment
5 years worth of data
2 pools of the ELIP test results during pregnancy
2 pools of the results of the test given before pregnancy and then during (to the same women)
Relationships between the antigens
Relationships between treatments and auto-Abs production
The rest of the elements in the model are mathematically defined
Casual loop diagrams
Building a Model by parts
“What if” scenarios
Model results summary
Simple Model Example
in Stella: outer shell
Simple Model Example: inner shell
supervised patients at one
of the Moscow clinics. 1999 data.
Expected Simulation Results - After using ELIP test as a diagnostic technology and necessary treatments
Primary contributions of this work:
– Treatment of children with pathologies decreases
– Savings for insurance companies
– Productive population increases
Secondary contributions of this work:
Modeling Pre-clinical Diagnostics Test Using System DynamicsWorkshopLeeza OsipenkoPhD Colloquium22nd System Dynamics ConferenceOxford, UK July 25, 2004
Few models exist due to complexity and validity concerns
How can these and other difficulties be addressed?
To what degree can computer simulations replace in vivo testing?
What can we do to promote further interest in the field?
Qualified specialists who can bridge the gap between medical doctors and engineers
More theoretical research
Refinement of the models
Tests, examples, trials, etc.