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Page 1: Quality Management System: A Key Performance Indicator of … · 2020-04-24 · Quality Management System: A Key Performance Indicator of BioBank Operations Sangita Paul, Venkata

Background Discussion

Conclusion

Methods

Liquid biospecimens (blood and urine) are physically evaluated based on several parameters,including location of specimens within the cryostorage inventory, available volume, condition ofstorage vials, as well as the accuracy of the label.

QA results are then compared with the specimen inventory database for accuracy and used as keyperformance indicators for the overall effectiveness of the quality management program. Duringthe QA process, MGB SOPs such as specimen inventory quality assurance, temperaturemaintenance, specimen retrieval are practiced to maintain specimen quality and integritythroughout the QA process.

Freezer maintenance is performed daily and several parameters including the temperature, in °C,at the top of the freezer (A), temperature at the bottom of the freezer (B), liquid usage (in/day),and liquid level (in) are monitored to ensure they are within optimal range. Furthermore, amanual dipstick is performed on a weekly basis for all freezers in order to ensure the actual levelcompares to the level that is displayed on the monitor.

Results

Effective Quality Management System in Biobanks can promote reliability on biospecimens andclinical data which are key contributors to cutting edge translational research. The next step ofMGB QMS will be to focus on Quality Control (QC) of biospecimens. The aim of Quality Controlsystem is to determine pre-analytical variables by investigating several parameters and theirimpact on specimen quality. MGB also conducts a client satisfaction survey to obtain feedback onoverall sample request and distribution process. We have received positive feedback on overallsample quality and on fitness of purpose in downstream analysis from our academic andindustrial collaborators

Acknowledgements

Figure 3: Total accuracy for various collection protocols that quality assurance had been performed on. The 3 criteria shown are labelling, storage location and volume accuracy

Figure 4a: Total number of specimens assessed in QA from all studies by specimen type from 2018-2019

Figure 4b: Total amount of specimens assessed in QA for various collection protocols from 2018-2019

Figure2: McCain GU BioBank Specimen Inventory Quality Assurance System Workflow

MGB program is supported by Princess Margaret Cancer Research Foundation. Special thanks to all members of MGB program for their continued support and contributions to the program.

Figure 5a: Proportion of specimen types with volume discrepancies in QA from 2018-2019

Figure 5b: CAPA implemented as part of the Quality Management System

We have performed quality assurance on various specimen types such as plasma, serum, buffycoat and urine specimens banked under various collection protocols. The specimens are assessedfor correct storage locations in cryostorage inventory, specimen availability, available volume, andlabeling accuracy.

100% of the specimens assessed as part of QMS are found to be in their correct storage locationswith 100% labeling accuracy. Specimens are also checked for volume accuracy across variousstudy cohorts and the overall accuracy has been found to be over 90%. 8 out of 14 studies have atotal volume accuracy of 100% (See figure 3). Majority of the volume discrepancies found throughQA were from the PCPC study. PCPC is an archived sub-study, the specimens were processedexternally and stored in non-standard cryovials which are not graduated. Due to this the volumeestimates tend to be inaccurate which leads to lower volume accuracy compared to other sub-studies. LS2 is also a sub-study where only buffy coats are banked. The viscosity of buffy coatscould be the reason for lower volume accuracies in LS2 study.

Since the beginning of the program, a total number of 19,280 specimens have been assessedthrough the Quality Management System. GUB being the biggest cohort of MGB has the highestnumber of samples assessed. Figures 4a and 4b show the biospecimens broken down into specificspecimen types as well as different study cohorts.

Any deviations are documented and reported via the Incident Reporting Form (IRF) whereby suchsituations can be investigated and Corrective and Preventive Actions (CAPA) can be employed ifnecessary. Plasma specimens were found to have the most volume discrepancies, followed byserums, buffy coats, urine supernatant and urine pellet (see Figure 5a). Plasma has the highestamount of volume discrepancies as most of the PCPC samples are plasma. Serum also contributesfor 29% of volume discrepancies which is mainly due to human error. The volume of serum bankedfor most protocols is 0.5 ml, but the smallest graduation on the standard cryovials used is 0.8ml.This causes estimation errors in volume which likely contributed to higher volume discrepanciesfor serum samples. Figure 5b depicts the amount of specimens that required CAPA. The volumes ofthe samples that required CAPA were changed on the online specimen inventory database usingbulk volume templates. CAPA was also performed on specimens that were found missing byvirtually disposing the sample to reflect the correct status of the specimens on the onlinespecimen inventory database.January 2020 to February 2020 was a busy time in terms of freezer usage due to increased sampleretrieval, hence, the sample data was chosen from that time period. When accessing the freezer, itis ensured that the temperature (°C) is within optimal range and that the freezer is only exposed toroom temperature for the minimal amount necessary. As seen as in Figure 6a, the trend observedwas that the temperature is well maintained in an optimal range and remains under the glasstransition temperature (Tg). Figure 6b shows the level display (in) compared to the liquid usage(in/day) of the freezers. There is a spike in the liquid usage for Freezer LN6 during early Februarywhich is due to an increase in freezer access due to sample retrieval. The freezer temperature wasnot affected by the increase in usage and it remained within the optimal temperature range (seeFigure 6a).

Banking of high-quality appropriately consented human bio-specimens is crucial for theunderstanding of disease pathogenesis and translation of such knowledge into improvements inpatient care. McCain GU Biobank Quality Management System (MGB-QMS) ensures that abiospecimen meets accepted quality standards which will aid in minimizing biospecimenvariability that could affect the interpretation of scientific results. Biospecimens are banked for avariety of study cohorts which mainly includes the GUB study. MGB QMS encompasses SOP andbest practices, equipment calibration and maintenance, specimen inventory & clinical QA data aswell as client satisfaction survey on overall Biobank service.

Quality Management System: A Key Performance Indicator of BioBankOperations

Sangita Paul, Venkata Praveen Sakhamuri, Manpreet Jagdev, Nouman Zulfiqar, Heidi Wagner & Neil FleshnerMcCain GU BioBank (MGB), Surgical Oncology, University Health Network, Toronto

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Figure 6b: Liquid nitrogen level display (in) and liquid usage (in/day) for all liquid nitrogen 1500 ECO series freezers from Jan 2020 to Feb 2020

Figure 6a: Temperature A (°C) and Temperature B (°C) for all liquid nitrogen 1500 ECO series freezers from Jan 2020 to Feb 2020

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Figure 1: McCain GU BioBank Quality Management System Organization

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Contact Information:

Sangita Paul– [email protected]

Heidi Wagner- [email protected]

www.gubiobank.com