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==Introduction==
==Introduction==
In the era of precision medicine, human biospecimens are an important resource for basic, [[Translational research|translational]], and clinical research and are increasingly needed to advance our understanding of human physiology, disease, treatment response, and outcomes. The field of [[Biobank|biobanking]] has undergone significant optimization efforts by national and international communities to improve and harmonize biospecimen curation to support this need.<ref name="vanOmmenBBMRI15">{{cite journal |title=BBMRI-ERIC as a Resource for Pharmaceutical and Life Science Industries: The Development of Biobank-Based Expert Centres |journal=European Journal of Human Genetics |author=van Ommen, G.-J.B.; Törnwall, O.; Bréchot, C. et al. |volume=23 |issue=7 |pages=893-900 |year=2015 |doi=10.1038/ejhg.2014.235 |pmid=25407005 |pmc=PMC4463510}}</ref><ref name="LanghofCurrent18">{{cite journal |title=Current Practices for Access, Compensation, and Prioritization in Biobanks. Results From an Interview Study |journal=European Journal of Human Genetics |author=Langhof, H.; Kahrass, H.; Illig, T. et al. |volume=26 |issue=11 |pages=1572–1581 |year=2018 |doi=10.1038/s41431-018-0228-x |pmid=30089824 |pmc=PMC6189200}}</ref> However, the operationalization and maintenance of biobanks is resource-intensive and often cost prohibitive for many institutions. In addition, long-term biobanking may be suboptimal for some types of testing, such as for studies that rely on [[Lability|labile]] analytes.<ref name="ShabhikhaniTheProc14">{{cite journal |title=The Procurement, Storage, and Quality Assurance of Frozen Blood and Tissue Biospecimens in Pathology, Biorepository, and Biobank Settings |journal=Clinical Biochemistry |author=Shabihkhani, M.; Lucey, G.M.; Wei, B. et al. |volume=47 |issue=4–5 |pages=258-66 |year=2014 |doi=10.1016/j.clinbiochem.2014.01.002 |pmid=24424103 |pmc=PMC3982909}}</ref><ref name="EllervikPreanal15">{{cite journal |title=Preanalytical Variables Affecting the Integrity of Human Biospecimens in Biobanking |journal=Clinical Chemistry |author=Ellervik, C.; Vaught, J. |volume=61 |issue=7 |pages=914-34 |year=2015 |doi=10.1373/clinchem.2014.228783 |pmid=25979952}}</ref> As a result, comprehensive access to human biospecimens remains limited, and there is a persistent need for efficient solutions that can provide access to high-quality and recently acquired human biospecimens.<ref name="MassettAss11">{{cite journal |title=Assessing the Need for a Standardized Cancer HUman Biobank (caHUB): Findings From a National Survey With Cancer Researchers |journal=Journal of the National Cancer Institute Monographs |author=Massett, H.A.; Atkinson, N.L.; Weber, D. et al. |volume=2011 |issue=42 |pages=8–15 |year=2011 |doi=10.1093/jncimonographs/lgr007 |pmid=21672890}}</ref>
In the era of precision medicine, human biospecimens are an important resource for basic, [[Translational research|translational]], and clinical research and are increasingly needed to advance our understanding of human physiology, disease, treatment response, and outcomes. The field of [[Biobank|biobanking]] has undergone significant optimization efforts by national and international communities to improve and harmonize biospecimen curation to support this need.<ref name="vanOmmenBBMRI15">{{cite journal |title=BBMRI-ERIC as a Resource for Pharmaceutical and Life Science Industries: The Development of Biobank-Based Expert Centres |journal=European Journal of Human Genetics |author=van Ommen, G.-J.B.; Törnwall, O.; Bréchot, C. et al. |volume=23 |issue=7 |pages=893-900 |year=2015 |doi=10.1038/ejhg.2014.235 |pmid=25407005 |pmc=PMC4463510}}</ref><ref name="LanghofCurrent18">{{cite journal |title=Current Practices for Access, Compensation, and Prioritization in Biobanks. Results From an Interview Study |journal=European Journal of Human Genetics |author=Langhof, H.; Kahrass, H.; Illig, T. et al. |volume=26 |issue=11 |pages=1572–1581 |year=2018 |doi=10.1038/s41431-018-0228-x |pmid=30089824 |pmc=PMC6189200}}</ref> However, the operationalization and maintenance of biobanks is resource-intensive and often cost prohibitive for many institutions. In addition, long-term biobanking may be suboptimal for some types of testing, such as for studies that rely on [[Lability|labile]] analytes.<ref name="ShabhikhaniTheProc14">{{cite journal |title=The Procurement, Storage, and Quality Assurance of Frozen Blood and Tissue Biospecimens in Pathology, Biorepository, and Biobank Settings |journal=Clinical Biochemistry |author=Shabihkhani, M.; Lucey, G.M.; Wei, B. et al. |volume=47 |issue=4–5 |pages=258-66 |year=2014 |doi=10.1016/j.clinbiochem.2014.01.002 |pmid=24424103 |pmc=PMC3982909}}</ref><ref name="EllervikPreanal15">{{cite journal |title=Preanalytical Variables Affecting the Integrity of Human Biospecimens in Biobanking |journal=Clinical Chemistry |author=Ellervik, C.; Vaught, J. |volume=61 |issue=7 |pages=914-34 |year=2015 |doi=10.1373/clinchem.2014.228783 |pmid=25979952}}</ref> As a result, comprehensive access to human biospecimens remains limited, and there is a persistent need for efficient solutions that can provide access to high-quality and recently acquired human biospecimens.<ref name="MassettAss11">{{cite journal |title=Assessing the Need for a Standardized Cancer HUman Biobank (caHUB): Findings From a National Survey With Cancer Researchers |journal=Journal of the National Cancer Institute Monographs |author=Massett, H.A.; Atkinson, N.L.; Weber, D. et al. |volume=2011 |issue=42 |pages=8–15 |year=2011 |doi=10.1093/jncimonographs/lgr007 |pmid=21672890}}</ref>
Human biospecimens can always be found in [[Clinical laboratory|clinical laboratories]], but access for the research is complicated by a series of technical, logistic, regulatory, and ethical challenges. Beyond the demands of delivering clinical results, laboratories lack efficient processes for biospecimen identification, human resources for [[Sample (material)|specimen]] acquisition, and procedural infrastructure for biospecimen collection under the provisions of human interventional ethics committees. Despite these challenges, the clinical laboratory is a promising resource for the acquisition of biospecimens, and researchers are beginning to investigate curation methods that can integrate with existing clinical workflows and leverage [[electronic health record]] (EHR) [[metadata]] for biospecimen identification and annotation.<ref name="MooreBio13">{{cite journal |title=Biospecimen Reporting for Improved Study Quality (BRISQ) |journal=Transfusion |author=Moore, H,M.; Jelly, A.; McShane, L.M. et al. |volume=53 |issue=7 |at=e1 |year=2013 |doi=10.1111/trf.12281 |pmid=23844646}}</ref><ref name="Simeon-DubachQual12">{{cite journal |title=Quality Really Matters: The Need to Improve Specimen Quality in Biomedical Research |journal=Journal of Pathology |author=Simeon-Dubach, D.; Burt, A.D.; Hall, P.A. |volume=228 |issue=4 |pages=431–3 |year=2012 |doi=10.1002/path.4117 |pmid=23023660}}</ref>
One of the first automated biospecimen identification systems was Crimson, an application used to identify the discarded blood samples accessioned into the clinical laboratory by querying the [[laboratory information system]] (LIS). Specimens, which met predetermined inclusion criteria, were electronically reaccessioned into a deidentified research database that could be accessed by researchers with institutional review board (IRB) approval.<ref name="MurphyInstrum09">{{cite journal |title=Instrumenting the Health Care Enterprise for Discovery Research in the Genomic Era |journal=Genome Research |author=Murphy, S.; Churchill, S.; Bry, L. et al. |volume=19 |issue=9 |pages=1675–81 |year=2009 |doi=10.1101/gr.094615.109 |pmid=19602638 |pmc=PMC2752136}}</ref> While biobanks routinely link health information between specimen and participant postenrollment, such solutions demonstrate how EHR integration and associated metadata can be used for targeted and automated biospecimen selection. However, examples of this framework remain limited, both in the literature and in practice, which typically focus on retrospective specimen identification for long-term biobanking. With the increased digitization of healthcare and modern data architectures that allow for real-time analysis of clinical data, biospecimens can be identified as samples that are processed through the clinical laboratory. This approach offers the benefit of increasing access to specimens of interest, including those with labile analytes, while not disrupting routine clinical [[workflow]]s.<ref name="EllervikPreanal15" />
In this report, we present Prism, a new tool built on open-source technology that can efficiently identify and notify the investigators of biospecimen availability in near real time. We describe the pipeline architecture and our experience with two IRB-approved pilot projects within our department (IRB Protocol IDs: Babesia – 2000023123; Diabetic biomarkers – 2000022266).
==Methods==




Revision as of 16:11, 2 June 2020

Full article title Bridging the collaboration gap: Real-time identification of clinical specimens for biomedical research
Journal Journal of Pathology Informatics
Author(s) Durant, Thomas J.S.; Gong, Guannan; Price, Nathan; Schilz, Wade L.
Author affiliation(s) Yale New Haven Hospital, Yale New Haven Health
Primary contact Email: Log in required
Year published 2020
Volume and issue 11
Article # 14
DOI 10.4103/jpi.jpi_15_20
ISSN 2153-3539
Distribution license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License
Website http://www.jpathinformatics.org/article.asp
Download http://www.jpathinformatics.org/temp/JPatholInform11114-7412119_203521.pdf
Emblem-important-yellow.svg This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed.

Abstract

Introduction: Biomedical and translational research often relies on the evaluation of patients or specimens that meet specific clinical or laboratory criteria. The typical approach used to identify biospecimens is a manual, retrospective process that exists outside the clinical workflow. This often makes biospecimen collection cost prohibitive and prevents the collection of analytes with short stability times. Emerging data architectures offer novel approaches to enhance specimen-identification practices. To this end, we present a new tool that can be deployed in a real-time environment to automate the identification and notification of available biospecimens for biomedical research.

Methods: Real-time clinical and laboratory data from Cloverleaf (Infor, NY, NY) were acquired within our computational health platform, which is built on open-source applications. Study-specific filters were developed in NiFi (Apache Software Foundation, Wakefield, MA, USA) to identify the study-appropriate specimens in real time. Specimen metadata were stored in Elasticsearch (Elastic N. V., Mountain View, CA, USA) for visualization and automated alerting.

Results: Between June 2018 and December 2018, we identified 2,992 unique specimens belonging to 2,815 unique patients, split between two different use cases. Based on laboratory policy for specimen retention and study-specific stability requirements, secure e-mail notifications were sent to investigators to automatically notify them of availability. The assessment of throughput on commodity hardware demonstrates the ability to scale to approximately 2,000 results per second.

Conclusion: This work demonstrates that real-world clinical data can be analyzed in real-time to increase the efficiency of biospecimen identification with minimal overhead for the clinical laboratory. Future work will integrate additional data types, including the analysis of unstructured data, to enable more complex cases and biospecimen identification.

Keywords: biobanking, biomedical research, biospecimen science, clinical specimens, real-time identification, translational research

Introduction

In the era of precision medicine, human biospecimens are an important resource for basic, translational, and clinical research and are increasingly needed to advance our understanding of human physiology, disease, treatment response, and outcomes. The field of biobanking has undergone significant optimization efforts by national and international communities to improve and harmonize biospecimen curation to support this need.[1][2] However, the operationalization and maintenance of biobanks is resource-intensive and often cost prohibitive for many institutions. In addition, long-term biobanking may be suboptimal for some types of testing, such as for studies that rely on labile analytes.[3][4] As a result, comprehensive access to human biospecimens remains limited, and there is a persistent need for efficient solutions that can provide access to high-quality and recently acquired human biospecimens.[5]

Human biospecimens can always be found in clinical laboratories, but access for the research is complicated by a series of technical, logistic, regulatory, and ethical challenges. Beyond the demands of delivering clinical results, laboratories lack efficient processes for biospecimen identification, human resources for specimen acquisition, and procedural infrastructure for biospecimen collection under the provisions of human interventional ethics committees. Despite these challenges, the clinical laboratory is a promising resource for the acquisition of biospecimens, and researchers are beginning to investigate curation methods that can integrate with existing clinical workflows and leverage electronic health record (EHR) metadata for biospecimen identification and annotation.[6][7]

One of the first automated biospecimen identification systems was Crimson, an application used to identify the discarded blood samples accessioned into the clinical laboratory by querying the laboratory information system (LIS). Specimens, which met predetermined inclusion criteria, were electronically reaccessioned into a deidentified research database that could be accessed by researchers with institutional review board (IRB) approval.[8] While biobanks routinely link health information between specimen and participant postenrollment, such solutions demonstrate how EHR integration and associated metadata can be used for targeted and automated biospecimen selection. However, examples of this framework remain limited, both in the literature and in practice, which typically focus on retrospective specimen identification for long-term biobanking. With the increased digitization of healthcare and modern data architectures that allow for real-time analysis of clinical data, biospecimens can be identified as samples that are processed through the clinical laboratory. This approach offers the benefit of increasing access to specimens of interest, including those with labile analytes, while not disrupting routine clinical workflows.[4]

In this report, we present Prism, a new tool built on open-source technology that can efficiently identify and notify the investigators of biospecimen availability in near real time. We describe the pipeline architecture and our experience with two IRB-approved pilot projects within our department (IRB Protocol IDs: Babesia – 2000023123; Diabetic biomarkers – 2000022266).

Methods

References

  1. ↑ van Ommen, G.-J.B.; Törnwall, O.; Bréchot, C. et al. (2015). "BBMRI-ERIC as a Resource for Pharmaceutical and Life Science Industries: The Development of Biobank-Based Expert Centres". European Journal of Human Genetics 23 (7): 893-900. doi:10.1038/ejhg.2014.235. PMC PMC4463510. PMID 25407005. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4463510. 
  2. ↑ Langhof, H.; Kahrass, H.; Illig, T. et al. (2018). "Current Practices for Access, Compensation, and Prioritization in Biobanks. Results From an Interview Study". European Journal of Human Genetics 26 (11): 1572–1581. doi:10.1038/s41431-018-0228-x. PMC PMC6189200. PMID 30089824. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6189200. 
  3. ↑ Shabihkhani, M.; Lucey, G.M.; Wei, B. et al. (2014). "The Procurement, Storage, and Quality Assurance of Frozen Blood and Tissue Biospecimens in Pathology, Biorepository, and Biobank Settings". Clinical Biochemistry 47 (4–5): 258-66. doi:10.1016/j.clinbiochem.2014.01.002. PMC PMC3982909. PMID 24424103. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3982909. 
  4. ↑ 4.0 4.1 Ellervik, C.; Vaught, J. (2015). "Preanalytical Variables Affecting the Integrity of Human Biospecimens in Biobanking". Clinical Chemistry 61 (7): 914-34. doi:10.1373/clinchem.2014.228783. PMID 25979952. 
  5. ↑ Massett, H.A.; Atkinson, N.L.; Weber, D. et al. (2011). "Assessing the Need for a Standardized Cancer HUman Biobank (caHUB): Findings From a National Survey With Cancer Researchers". Journal of the National Cancer Institute Monographs 2011 (42): 8–15. doi:10.1093/jncimonographs/lgr007. PMID 21672890. 
  6. ↑ Moore, H,M.; Jelly, A.; McShane, L.M. et al. (2013). "Biospecimen Reporting for Improved Study Quality (BRISQ)". Transfusion 53 (7): e1. doi:10.1111/trf.12281. PMID 23844646. 
  7. ↑ Simeon-Dubach, D.; Burt, A.D.; Hall, P.A. (2012). "Quality Really Matters: The Need to Improve Specimen Quality in Biomedical Research". Journal of Pathology 228 (4): 431–3. doi:10.1002/path.4117. PMID 23023660. 
  8. ↑ Murphy, S.; Churchill, S.; Bry, L. et al. (2009). "Instrumenting the Health Care Enterprise for Discovery Research in the Genomic Era". Genome Research 19 (9): 1675–81. doi:10.1101/gr.094615.109. PMC PMC2752136. PMID 19602638. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2752136. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. Grammar was cleaned up for smoother reading. In some cases important information was missing from the references, and that information was added.

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