The general objective of the project is to create an intelligent information system to support clinical analysis laboratories that is more advanced than the existing smart LIMS (Laboratory Information Management Systems). It envisions two intelligent systems currently unavailable on the market::
- SELCA Expert System: Capable of limiting measurement errors, ensuring reliable clinical tests, supporting clinical diagnostics, and enabling accurate assessments of laboratory activity.
- A data mining system for predictive diagnostics based on genetic markers, considering hypotheses advanced by scientific literature (SELCA miner).
The project was carried out in the following phases:
- Study of standardized interfacing through physical-cybernetic components of: automatic analyzers for clinical tests; a genetic sequencer for predictive diagnostics; IoT systems alongside instruments and the environment to activate the quality support control flow
- Activation of the IT infrastructure to implement: the advanced smart LIMS equipped with the expert system (SELCA); the LIMS to provide predictive medical diagnostics starting from genetic data (SELCAminer); the version, named SELCAnet, capable of interacting with software applications from other medical centers in the network (interoperable and in the Cloud).
- Design, development, and testing of the following modules:
- Support system for clinical analysis reporting through the integration of historical information on patient analyses and information from the IoT flow monitoring the operational conditions of the analyzers.
- Support system for reporting analysis from genomic sequencers (named Selca Genetics), which assists particularly in reporting Variants of Uncertain Significance (VUS). The system includes an in-silico tool based on Artificial Intelligence (AI) specifically developed to predict the pathogenicity of genetic variants and AI modules for literature mining.
- Selca miner, including a model to classify blood disorders (7 classes of diseases), and designed to collect data on a nutritional status assessment scenario for cancer patients (acquired from certified smart scales and physical measurements and cross-correlated with hematological analysis data).
- Two mobile applications to streamline certain sample tracking and quality assurance procedures, in particular: 1) Cold Chain Control during the transport of biological samples and 2) Sample tracking with RFID techniques and expired sample and reagent control.
Verifica dell’interoperabilità e realizzazione dei dimostratori.
The project developed a flexible and powerful infrastructure (Selca and SelcaNet) in which various vertical modules offering advanced functionalities are integrated. The individual modules are independent and can, in turn, integrate with LIMS already available in various laboratories.
The modules are: Selca miner, Selca Genetics, Cold Chain Control, Sample and Reagent Tracking with RFID.
The Selca Genetics module was tested in collaboration with COES (Experimental Hematology Oncology Center at the University of Catania) for variants related to BRCA1 and BRCA2 genes. The SELCA platform integrates all modules and allows the analysis laboratory to perform quality controls related to analyses and laboratory conditions. For external interoperability, the demonstrator supports the following use cases: Patient access to their own analyses (general); Access to analyses of their patients by family doctors/specialists, including access to historical series for analytes per patient and access to predictive model results provided by the SELCA system applicable to the type of analysis performed.
