Seminars of Software and Services for the Information Society. RFID as a new ICT tool to monitor Specimen Life Cycle and Quality Control in a Biobank

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Rosemary Andrews
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1 DIPARTIMENTO DI INGEGNERIA INFORMATICA AUTOMATICA E GESTIONALE ANTONIO RUBERTI Master of Science in Engineering in Computer Science (MSE-CS) Seminars in Software and Services for the Information Society RFID as a new ICT tool to monitor Specimen Life Cycle and Quality Control in a Biobank 1

Seminars in Software and Services for the Information Society RFID as a

2 Biobanks and information systems An Information System can be regarded as a collection of information related to (a portion of) the real world. One can access a specific datum in the Information System in order to obtain knowledge about the corresponding entity (or entities) in the real world. A Biobank can be regarded as an Information System. Each biospecimen is a piece of information (a snapshot) about the real world: this information is implicit. A laboratory test has the goal of extracting information from a specimen, and storing it in an explicit form. Each physical specimen is paired with a data record representing the explicit information extracted from the specimen (by tests) as well as other information about the related entity (or entities) in the real world. 2

A Biobank can be regarded as an Information System. Each biospecimen is a piece of information (a snapshot) about the real world: this information is implicit.

3 (a note) Biobanks and information systems Among the tasks of the Guidelines of a Biobank: (collecting) to preserve to the maximum extent the correlation between the information stored in the specimen, and the corresponding entity in the real world (storage) to preserve along the time the information implicitly stored with each specimen Among the tasks of bio-sciences as a whole: to extract and make explicit from each specimen as much information as possible to understand such information; to derive general rules leading to a better understanding of each specimen and a deeper knowledge of the corresponding entity (or entities) in the real world to provide an overall view and understanding of correlated groups of specimens; to derive general rules leading to a better understanding of the real world 3

extract and make explicit from each specimen as much information as possible to understand such information; to derive general rules leading to a better understanding of each specimen and a deeper

4 Operational Units in a Biobank: requirements from... processes and phases - security - performances - economics infrastructures technology evolution of the biobank 4

5 Typical Operational Units in a Biobank Acquisition of biospecimens Pre-analytics Analytics ( Labs ) test lines genomics proteomics... (omics) Physical Storage of the biospecimens Information Management (BIS Biobank Information System) 5

6 What s in a Lab (e.g.: proteomics, genomics,...) - an informatics point of view LAB device-1 custom data device-2 device-3 custom application & dedicated workstation Custom software system: highly integrated with hardware devices typically equipped with a dedicated workstation with own Graphical User Interface (GUI) Custom Data own information products interesting per se, i.e., finalized output and report with a diagnosis, data to be analized You cannot skip this 6

workstation Custom software system: highly integrated with hardware devices typically equipped with a dedicated

7 Information management in the main operational units Acquisition of biospecimens mainly from corporate structures (hospital wards and clinical test centers) (planned) services for external outsourcers guideline issues: informed consent, collection of clinical data, handling and timing according the best practices,... Pre-analytics high-tech support (robotics) for guideline enforcement and quality assurance guideline issues: security, anonymized identification of specimens,... Analytics several laboratories, with several tests for each laboratory each lab has a custom software applications that comes with devices guideline issues: automated test lines and procedures,... Physical Storage of the biospecimens customized racks and freezers (enforcement of operator identification) static maintenance (inventory, monitored status, alert procedures) selection of specimens, search and access guideline issues: security and access policies, controlled status for all specimens, backup circuit with liquid nitrogen,... 7

.. Pre-analytics high-tech support (robotics) for guideline enforcement and quality assurance guideline issues: security, anonymized identification of specimens,.

8 Nested Integration functional unit custom sw applic functional unit custom sw applic functional unit functional unit functional unit custom sw applic custom sw applic custom sw applic subsystem (partial integr.) integrated system Sometimes you cannot skip this, too functional unit custom sw applic 8

custom sw applic custom sw applic subsystem (partial integr.

9 Biobanks and information systems - Services - 1 Integration(*) of all the internal functional units, tracing all the relevant data, processes and events unit integration (custom solutions in the labs, clinical records and anamneses collected locally) subsystem integration: some existing software system may encompass a subset of the functional units and, in turn, has to be integrated (nested integration) Accounting and support to services for external contract- or corporate outsourcers (e.g., hospital wards, clinical test centers) inward information flow and outward reporting service management and accounting (*) integration a challenging, uncertain and time-consuming effort 9

functional units and, in turn, has to be integr

10 quality control & active monitoring reporting OLAP data mining external services for outsourcers external system-1 external system-2 Datamart-1 Datamart-2 Datamart-3 Datawarehouse ETL data integration Lab-1 data Lab-2 data clinical data records patient data external system-a external system-b hospital sample dev1 dev2 dev3 deva devb devc ward collection 10

Datawarehouse ETL data integration Lab-1 data Lab-2 data clinical data records patient

11 The process to be controlled preanalytics manual processing load in rack (manual proc) Prean. check-out freezer check-in automated processing load in rack (automated proc.) Prean. check-out t P S manual handling > timestamp (Preanalytics Check-out) > timestamp (Storage Check-in) storage temp check-out freezer restore t a1,t a2,...,t ak manual handling > timestamp > timestamp freezer check-out AN check-in t S A manual handling > timestamp (Storage Check-out) > timestamp (Analytics Check-in) analytics time 11

check-out t P S manual handling > timestamp (Preanalytics Check-out) > timestamp (Storage Check-in).

12 Rack for specimens 12

13 Sample Retrieval operator identification (card RFID) freezer/check-out identification (external RFID) open door cryobox/rack identification (RFID on box/rack) sample retrieval cryobox/rack returns to position close door freezer/check-in identification (external RFID) operator identification (card RFID) 13

on box/rack) sample retrieval cryobox/rack returns to position close door

14 The end of the story 14

Introduction to Datawarehousing

Introduction to Datawarehousing DIPARTIMENTO DI INGEGNERIA INFORMATICA AUTOMATICA E GESTIONALE ANTONIO RUBERTI Master of Science in Engineering in Computer Science (MSE-CS) Seminars in Software and Services for the Information Society