Limits...
LimsPortal and BonsaiLIMS: development of a lab information management system for translational medicine.

Bath TG, Bozdag S, Afzal V, Crowther D - Source Code Biol Med (2011)

Bottom Line: The transition away from using local, uncontrolled records in spreadsheet and paper formats to a centrally held, secured and backed-up database brings the immediate benefits of improved data visibility, audit and overall data quality.The open-source availability of this software allows others to rapidly implement a LIMS which in itself might sufficiently address user requirements.In situations where this software does not meet requirements, it can serve to elicit more accurate specifications from end-users for a more heavyweight LIMS by acting as a demonstrable prototype.

View Article: PubMed Central - HTML - PubMed

Affiliation: Translational Medicine Research Collaboration Institute, Pfizer Inc, Ninewells Hospital, Dundee, DD1 9SY, UK. d.crowther@dundee.ac.uk.

ABSTRACT

Background: Laboratory Information Management Systems (LIMS) are an increasingly important part of modern laboratory infrastructure. As typically very sophisticated software products, LIMS often require considerable resources to select, deploy and maintain. Larger organisations may have access to specialist IT support to assist with requirements elicitation and software customisation, however smaller groups will often have limited IT support to perform the kind of iterative development that can resolve the difficulties that biologists often have when specifying requirements. Translational medicine aims to accelerate the process of treatment discovery by bringing together multiple disciplines to discover new approaches to treating disease, or novel applications of existing treatments. The diverse set of disciplines and complexity of processing procedures involved, especially with the use of high throughput technologies, bring difficulties in customizing a generic LIMS to provide a single system for managing sample related data within a translational medicine research setting, especially where limited IT support is available.

Results: We have designed and developed a LIMS, BonsaiLIMS, around a very simple data model that can be easily implemented using a variety of technologies, and can be easily extended as specific requirements dictate. A reference implementation using Oracle 11 g database and the Python framework, Django is presented.

Conclusions: By focusing on a minimal feature set and a modular design we have been able to deploy the BonsaiLIMS system very quickly. The benefits to our institute have been the avoidance of the prolonged implementation timescales, budget overruns, scope creep, off-specifications and user fatigue issues that typify many enterprise software implementations. The transition away from using local, uncontrolled records in spreadsheet and paper formats to a centrally held, secured and backed-up database brings the immediate benefits of improved data visibility, audit and overall data quality. The open-source availability of this software allows others to rapidly implement a LIMS which in itself might sufficiently address user requirements. In situations where this software does not meet requirements, it can serve to elicit more accurate specifications from end-users for a more heavyweight LIMS by acting as a demonstrable prototype.

No MeSH data available.


Related in: MedlinePlus

BonsaiLIMS object model Project://collection of related samples Subject://donor/source of each sample Sample://material obtained from subject Analysis://operation or process performed on a sample
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Related In: Results  -  Collection

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Figure 2: BonsaiLIMS object model Project://collection of related samples Subject://donor/source of each sample Sample://material obtained from subject Analysis://operation or process performed on a sample

Mentions: Figure 1 shows the BonsaiLIMS module within the host LIMSPortal application. LIMSPortal, as part of a Django framework will easily integrate with other 3rd party Django applications and can be deployed wherever there is an available python environment. LIMSportal is a web based solution which is fully HTML and CSS standards compliant and has been tested on Internet Explorer 6/7/8 and Mozilla Firefox 3.x. The basic implementation is built on four object models: Project, Subject, Sample and Analysis. Figure 2 shows the objects and the 1..n relationships between a project and its subjects, a subject and their samples and a sample and its analyses. The data model used by BonsaiLIMS is a relational schema that reflects the object model, with flexible data handling coming from the use of name-value pairs at the analysis level. This removes the need to specify in advance the types of analysis and results that may be entered during a particular workflow.


LimsPortal and BonsaiLIMS: development of a lab information management system for translational medicine.

Bath TG, Bozdag S, Afzal V, Crowther D - Source Code Biol Med (2011)

BonsaiLIMS object model Project://collection of related samples Subject://donor/source of each sample Sample://material obtained from subject Analysis://operation or process performed on a sample
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3113716&req=5

Figure 2: BonsaiLIMS object model Project://collection of related samples Subject://donor/source of each sample Sample://material obtained from subject Analysis://operation or process performed on a sample
Mentions: Figure 1 shows the BonsaiLIMS module within the host LIMSPortal application. LIMSPortal, as part of a Django framework will easily integrate with other 3rd party Django applications and can be deployed wherever there is an available python environment. LIMSportal is a web based solution which is fully HTML and CSS standards compliant and has been tested on Internet Explorer 6/7/8 and Mozilla Firefox 3.x. The basic implementation is built on four object models: Project, Subject, Sample and Analysis. Figure 2 shows the objects and the 1..n relationships between a project and its subjects, a subject and their samples and a sample and its analyses. The data model used by BonsaiLIMS is a relational schema that reflects the object model, with flexible data handling coming from the use of name-value pairs at the analysis level. This removes the need to specify in advance the types of analysis and results that may be entered during a particular workflow.

Bottom Line: The transition away from using local, uncontrolled records in spreadsheet and paper formats to a centrally held, secured and backed-up database brings the immediate benefits of improved data visibility, audit and overall data quality.The open-source availability of this software allows others to rapidly implement a LIMS which in itself might sufficiently address user requirements.In situations where this software does not meet requirements, it can serve to elicit more accurate specifications from end-users for a more heavyweight LIMS by acting as a demonstrable prototype.

View Article: PubMed Central - HTML - PubMed

Affiliation: Translational Medicine Research Collaboration Institute, Pfizer Inc, Ninewells Hospital, Dundee, DD1 9SY, UK. d.crowther@dundee.ac.uk.

ABSTRACT

Background: Laboratory Information Management Systems (LIMS) are an increasingly important part of modern laboratory infrastructure. As typically very sophisticated software products, LIMS often require considerable resources to select, deploy and maintain. Larger organisations may have access to specialist IT support to assist with requirements elicitation and software customisation, however smaller groups will often have limited IT support to perform the kind of iterative development that can resolve the difficulties that biologists often have when specifying requirements. Translational medicine aims to accelerate the process of treatment discovery by bringing together multiple disciplines to discover new approaches to treating disease, or novel applications of existing treatments. The diverse set of disciplines and complexity of processing procedures involved, especially with the use of high throughput technologies, bring difficulties in customizing a generic LIMS to provide a single system for managing sample related data within a translational medicine research setting, especially where limited IT support is available.

Results: We have designed and developed a LIMS, BonsaiLIMS, around a very simple data model that can be easily implemented using a variety of technologies, and can be easily extended as specific requirements dictate. A reference implementation using Oracle 11 g database and the Python framework, Django is presented.

Conclusions: By focusing on a minimal feature set and a modular design we have been able to deploy the BonsaiLIMS system very quickly. The benefits to our institute have been the avoidance of the prolonged implementation timescales, budget overruns, scope creep, off-specifications and user fatigue issues that typify many enterprise software implementations. The transition away from using local, uncontrolled records in spreadsheet and paper formats to a centrally held, secured and backed-up database brings the immediate benefits of improved data visibility, audit and overall data quality. The open-source availability of this software allows others to rapidly implement a LIMS which in itself might sufficiently address user requirements. In situations where this software does not meet requirements, it can serve to elicit more accurate specifications from end-users for a more heavyweight LIMS by acting as a demonstrable prototype.

No MeSH data available.


Related in: MedlinePlus