OpenModula: Software for the simulation of immuno-enzymatic diagnostic sessions
This project was awarded to Indexpage for €12000 EUR.Get free quotes for a project like this
Project Budgetmin €5000 EUR
- A "LAMP" server running CentOS 6.x
- A client running a major OS (MS-Windows, Linux, Mac) with a widespread browser (Explorer, Firefox, Chrome)
1) Design and implementation of an EHR (Electronic Health Record) patient database with relevant interface.
1.1 Database design of EHR tables according to a provided scheme (possibly an accepted standard)
1.2 Proper insulation of privacy-critical data.
1.3 One-patient vs many-records scheme. Retrieval of previous diagnoses based on test type, test date, result, etc.
2) Design and implementation of a database of diagnostic assays with relevant interface. Diagnostic kits we deal with (ELISA) are all based on the same geometry and general way of operating, but can differ in some parameters, such as well layout, incubation times, amount of reagent, operation sequence, etc.
2.1 Design of a flexible database for diagnostic assays, based on a default template for each “class” of assays and sn “instance” for each specific test.
2.2 Design of a user interface for the point 2.1: input new assays and modify existing ones, possibly using a “wizard” (a step-by-step, guided interface).
3) Schematic simulation of underlying instrument.
3.1 Diagnostic instrument is simulated in terms of available “resources” (how many pipettes, how many incubators, how many wash stations, etc.).
3.2 Relation among resources: e.g.: if A is in use, B can't be used, while C and D can run simultaneously, etc.
3.3 User interface for 3.1 and 3.2 : allow modification of parameters.
4) Simulation of diagnostic procedure.
4.1 Sample input form: name, date of birth, what tests must undergo, etc. Data are stored in database designed in 1.1.
4.2 Calculation of necessary amounts of reagents, wells and instrument resources, using information gathered in 2.1 and 3.1.
4.3 Scheduling of next operations and relevant timings according to a standard time table for each operation, using data from 3.2 .
4.4 Self-updating, colour-coded scheme of ongoing procedure, with indication of elapsed time and remaining time.
5) Result acquisition and interpretation.
5.1 Reference curve calculation and relevant graphics: interactive cut-off line, regression line, interpolation spline.
5.2 Quality controls: checking control data against acceptability thresholds that have been input in 2.2.
6) Tidy printouts, nice looks, fine background images, eye-candy, etc.
* Implementation of a high security remote access (via username and password) to the data.
* Implementation of an exchange of data between a physical device (Arduino board attached to the client) and the remote LAMP server.
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