Journal:adLIMS: A customized open source software that allows bridging clinical and basic molecular research studies

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Full article title adLIMS: A customized open source software that allows bridging clinical and basic molecular research studies
Journal BMC Bioinformatics
Author(s) Calabria, Andrea; Spinozzi, Giulio; Benedicenti, Fabrizio; Tenderini, Erika; Montini, Eugenio
Author affiliation(s) San Raffaele Telethon Institute for Gene Therapy; University of Milano-Bicocca
Primary contact Email: montini.eugenio@hsr.it
Year published 2015
Volume and issue 16 (Suppl 9)
Page(s) S5
DOI 10.1186/1471-2105-16-S9-S5
ISSN 1471-2105
Distribution license Creative Commons Attribution 4.0 International
Website http://www.biomedcentral.com/1471-2105/16/S9/S5
Download http://www.biomedcentral.com/content/pdf/1471-2105-16-S9-S5.pdf (PDF)
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Abstract

Background: Many biological laboratories that deal with genomic samples are facing the problem of sample tracking, both for pure laboratory management and for efficiency. Our laboratory exploits PCR techniques and Next Generation Sequencing (NGS) methods to perform high-throughput integration site monitoring in different clinical trials and scientific projects. Because of the huge amount of samples that we process every year, which result in hundreds of millions of sequencing reads, we need to standardize data management and tracking systems, building up a scalable and flexible structure with web-based interfaces, which are usually called Laboratory Information Management System (LIMS).

Methods: We started collecting end-users' requirements, composed of desired functionalities of the system and Graphical User Interfaces (GUI), and then we evaluated available tools that could address our requirements, spanning from pure LIMS to Content Management Systems (CMS) up to enterprise information systems. Our analysis identified ADempiere ERP, an open source Enterprise Resource Planning written in Java J2EE, as the best software that also natively implements some highly desirable technological advances, such as the high usability and modularity that grants high use-case flexibility and software scalability for custom solutions.

Results: We extended and customized ADempiere ERP to fulfil LIMS requirements and we developed adLIMS. It has been validated by our end-users verifying functionalities and GUIs through test cases for PCRs samples and pre-sequencing data and it is currently in use in our laboratories. adLIMS implements authorization and authentication policies, allowing multiple users management and roles definition that enables specific permissions, operations and data views to each user. For example, adLIMS allows creating sample sheets from stored data using available exporting operations. This simplicity and process standardization may avoid manual errors and information backtracking, features that are not granted using track recording on files or spreadsheets.

Conclusions: adLIMS aims to combine sample tracking and data reporting features with higher accessibility and usability of GUIs, thus allowing time to be saved on doing repetitive laboratory tasks, and reducing errors with respect to manual data collection methods. Moreover, adLIMS implements automated data entry, exploiting sample data multiplexing and parallel/transactional processing. adLIMS is natively extensible to cope with laboratory automation through platform-dependent API interfaces, and could be extended to genomic facilities due to the ERP functionalities.

Keywords: LIMS; Open Source Software; Information Systems; ADempiere ERP; Sample Tracking

Background

In many biological laboratories, sample tracking is an outstanding issue and often represents a bottleneck for the correct handling and interpretation of experimental data. This issue is becoming particularly critical when automation and high-throughput technologies are introduced in the laboratory practice. Our laboratory performs high-throughput characterization of vector-genomic integration sites in the context of gene therapy applications based on the delivery of therapeutic genes by viral vectors that stably integrate into the genome of targeted cells, as well as gene therapy preclinical models and insertional mutagenesis research projects.[1][2][3][4][5][6][7][8][9]

References

  1. ↑ Ranzani, M.; Annunziato, S.; Calabria, A.; Brasca, S.; Benedicenti, F.; Gallina, P.; Naldini, L.; Montini, E. (2014). "Lentiviral vector-based insertional mutagenesis identifies genes involved in the resistance to targeted anticancer therapies". Molecular Therapy 22 (12): 2056-2068. doi:10.1038/mt.2014.174. PMC PMC4429698. PMID 25195596. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4429698. 
  2. ↑ Aiuti, A.; Biasco, L.; Scaramuzza, S.; Ferrua, F.; Cicalese, M.P.; Baricordi, C. et al. (2013). "Lentiviral hematopoietic stem cell gene therapy in patients with Wiskott-Aldrich syndrome". Science 341 (6148): 1233151. doi:10.1126/science.1233151. PMC PMC4375961. PMID 23845947. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4375961. 
  3. ↑ Biffi, A.; Montini, E.; Lorioli, L.; Cesani, M.; Fumagalli, F.; Plati, T. et al. (2013). "Lentiviral hematopoietic stem cell gene therapy benefits metachromatic leukodystrophy". Science 341 (6148): 1233158. doi:10.1126/science.1233158. PMID 23845948. 
  4. ↑ Aiuti, A.; Cassani, B.; Andolfi, G.; Mirolo, M.; Biasco, L.; Recchia, A. et al. (2007). "Multilineage hematopoietic reconstitution without clonal selection in ADA-SCID patients treated with stem cell gene therapy". Journal of Clinical Investigation 117 (8): 2233-40. doi:10.1172/JCI31666. PMC PMC1934603. PMID 17671653. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1934603. 
  5. ↑ Braun, C.J.; Boztug, K.; Paruzynski, A.; Witzel, M.; Schwarzer, A.; Rothe, M. et al. (2014). "Gene therapy for Wiskott-Aldrich syndrome: Long-term efficacy and genotoxicity". Science Translational Medicine 6 (227): 227–33. doi:10.1126/scitranslmed.3007280. PMID 24622513. 
  6. ↑ Deichmann, A.; Hacein-Bey-Abina, S.; Schmidt, M.; Garrigue, A.; Brugman, M.H.; Hu, J.; Glimm, H.; Gyapay, G.; Prum, B.; Fraser, C.C. et al. (2007). "Vector integration is nonrandom and clustered and influences the fate of lymphopoiesis in SCID-X1 gene therapy". Journal of Clinical Investigation 117 (8): 2225–2232. doi:10.1172/JCI31659. PMC PMC1934585. PMID 17671652. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1934585. 
  7. ↑ Ott, M.G; Schmidt, M.; Schwarzwaelder, K.; Stein, S.; Siler, U.; Koehl, U. et al. (2006). "Correction of X-linked chronic granulomatous disease by gene therapy, augmented by insertional activation of MDS1-EVI1, PRDM16 or SETBP1". Nature Medicine 12 (4): 401-409. doi:10.1038/nm1393. PMID 16582916. 
  8. ↑ Schwarzwaelder, K.; Howe, S.J.; Schmidt, M.; Brugman, M.H.; Deichmann, A.; Glimm, H. et al. (2007). "Gammaretrovirus-mediated correction of SCID-X1 is associated with skewed vector integration site distribution in vivo". Journal of Clinical Investigation 117 (8): 2241-9. doi:10.1172/JCI31661. PMC PMC1934556. PMID 17671654. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1934556. 
  9. ↑ Stein, S.; Ott, M.G.; Schultze-Strasser, S.; Jauch, A.; Burwinkel, B.; Kinner, A. et al. (2010). "Genomic instability and myelodysplasia with monosomy 7 consequent to EVI1 activation after gene therapy for chronic granulomatous disease". Nature Medicine 16 (2): 198-204. doi:10.1038/nm.2088. PMID 20098431. 

Notes

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

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