BioRails DM

Screening to in vivo

All your data - safe, secure and searchable

BioRails DM is a comprehensive laboratory information management system designed to address a range of workflow driven research activities including

  • Screening
  • ADME/DMPK
  • In vivo Pharmacology
  • Safety toxicology
  • Translational research
  • Bioanalytical testing

It can be used to design flexible processes and workflows for capturing experimental data. This defines the procedures used to reliably capture high quality information. By separating design from execution BioRails DM provides separation between the plan and reality. This allows scientists to use the system across the full range of scientific investigations from routine activities such as ADME to more exploratory research such as in vivo behavioural studies. BioRails LIMS offers a much higher degree of flexibility than traditional LIMS or Data management solutions.

Workflow - processes can be sequenced into a default workflow for an experiment allowing scientists to pre-plan and execute an experiment based on the default workflow.

Processes - every process has a default form associated with it for capturing both the data and the relationships between data. These can be completed directly in the web interface, uploaded from file or templated in Morphit for faster more accurate working.

SOP deployment - standard operating procedures, safety documentation and even processing templates are managed in the system and automatically deployed with the experiment to the scientists.

HTS Dose response resuilts can be stored and reported. Complex protocols can be distilled into simple re-usable process definitions used across many different assays.

The recipe defines the workflow for experiments allowing a whole experiment to be defined from a single method definition in one step.

Flexibility

The separation of the assay definition from its execution in an experiment means that the experiment workflow can deviate from the intended 'blue-print'. In addition tasks can be modified from the process template to include more rows of data or new parameters.  This unique flexibility allows the system to be applied to a wide range of research activities.
 
This flexibility extends to the deployment of BioRails within an organisation
  • "Breadth first - simple process definitions can be defined using only a few high level parameters; the experiment folders are used to store files and documents containing information relevant to the activity
  • "Depth first - parameters can be defined to capture all the information generated during a study, from the conditions used to the results generated, in a series of processes combined into an assay definition; raw data can be archived in the experiment and task folders together with analysis and reports; this can be supported by analysis templates used to automate activities and increase efficiency
A breadth first approach facilitates rapid rollout with the advantage of bringing all groups into an electronic environment, providing centralised access to data and reports. The use of simple process definitions reduces the number of tasks required to capture data and simplifies training. 
 
In contrast the depth first approach requires more planning and time to design the experiment workflow and all processes used to capture and analyse data. The advantage of this approach is that it facilitates capture of more structured data, and enables a higher degree of automation to be applied to the experiment, reducing the number of manual tasks and increasing efficiency. Data captured using process definitions is immediately available for analysis and open to analytical queries. This facilitates data mining and makes it easier and more direct to ask and answer questions from the data, such as, what was the historical performance of my control? Data quality is improved since the system enforces the validity and dimensionality of data entered.

Freedom

Fortunately BioRails does not mandate either approach but allows scientists the freedom to choose the best approach for their needs. This is always a pragmatic decision based on effort and reward. In summary the system can be used as a generic ELN using simple generic process definitions and the content module to capture unstructured data related to the experiment. Alternatively it can be used as a structured data capture system by specialising the assay definition to include more detail and making use of processing and workflow templates to automate tasks. This flexibility is unique to BioRails.
 




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