Defining and executing laboratory workflows is an essential feature of modern laboratory information management systems. GenoFAB was designed from the ground up to support complex workflows. It’s a little like Google Maps for labs, a tool to navigate a network of interconnected data.
The value of workflows is recognized across all industries. Processes ensure consistent outcomes of business operations. They also support a rational approach to improving operations. They allow businesses to run more efficiently by helping team members work together.
Workflows and processes are generally described in Standard Operating Procedures (SOPs) that provide step-by-step instructions on how to complete a job. When writing a standard operating procedure, there is always a tension between the desire to standardize processes and the need to be agile enough to adapt to ever changing market conditions.
LIMS applications support laboratory personnel with different roles and responsibilities. Many LIMS applications now include some workflow solution that has been developed on top of their data management solution to help write SOPs as a series of tasks assigned to different lab members.
Rather than being an add-on feature to a data management application, workflows are built in GenoFAB DNA.
Are you looking for a better way to manage your laboratory processes, book a demonstration to learn how GenoFAB can help your team run more efficient workflows.
Laboratory Processes as data flows
Every record in GenoFAB is associated with a task that can be assigned to a lab member. Every data point in GenoFAB is a task and every task is associated with data.
The task and the record go through success successives stages. First they are requested. Requested tasks can be assigned to lab members. Tasks that are being worked on are in progress. Tasks that have been completed make their associated samples or data available to use by other tasks. Finally, tasks that did not complete successfully can be cancelled.Records that once were available for use by other tasks can be archived when they are no longer available.
For example, the purchase of a laboratory supply can be requested when the lab inventory is getting low. The record corresponding to the supply order will then be assigned to the person in charge of purchasing. The record and tasks will be in progress when waiting for delivery. The supply will be available after the task of ordering it has been completed. Finally, the supply will be archived when this supply order has been exhausted.
Every data and operation can go through the same sequences of statuses requested, assigned, in progress, available, and archived. Sample preparation, sequencing runs, cell cultures, flow cytometry assays.
Understanding the relationship between tasks, data records, and storage locations helps configure new LIMS accounts so that they can properly represent the lab workflows.
3 rules to identify steps in lab processes
PCR-tests used in many clinical laboratories are an example of a complex laboratory workflow composed of a sequence of steps. Subject samples are received. DNA or RNA is extracted from the samples. DNA solutions may be normalized and mixed with enzymes, primers and probes in the reaction buffer. The PCR reaction is run on PCR instruments to produce data that are analyzed to make a diagnostic.
Even though the overall process is well understood, there is no single way to break down the entire workflow into steps corresponding to individual LIMS records. When creating an SOP composed of a sequence of hierarchical steps, one needs to consider several factors.
1-Job assignment policies
The assignment of tasks is another factor to consider when creating the document. In GenoFAB the execution of each record can be assigned to a single lab member. A sequence of steps that are assigned to a single lab member can be lumped into a single LIMS record. Whenever there can be a change of assignment, two different records can be created.
The design of LIMS records go hand in hand with the workflow execution policy. The lab manager can organize the work as an assembly line in which each of the technicians specializes in the execution of very small tasks and the processing goes from one technician to another. Alternatively, the lab can be organized as a job shop, in which the complete analysis of a sample is assigned to a single technician. The complexity of the workflow, composition of the team, and intermediate quality control points in the process are factors that will influence job assignment policies.
2-Storage and rework policies
Storage policies can also influence the design of LIMS record types. Storage policies can be determined by the need to conserve some samples in the long term. For example, a diagnostic lab may want to keep incoming patient tissue samples to reserve the possibility of performing additional tests that were not requested when the sample was submitted. A synthetic biology lab will probably want to conserve all the finished plasmids they have assembled in order to be able to distribute them to other users or reused fragments of existing DNA molecules.
Rework policies will also determine the storage need. Rework policies handle the possibility that a workflow may fail to pass a QC test. This situation can be handled in different ways. The easiest way is to abort the process and not redo the work. In other cases, the process may need to start from the beginning again. Or the process may restart from the last successful control step.
For example a sequencing lab will perform a quality of control of the library prior to sequencing the sample. If the library preparation fails QC, they may simply abort the process. This could be the case if there is not enough material left to perform the protocol again. Or they may start from the DNA extraction steps, or simply redo the library preparation step.
Whenever a process may restart from an intermediate point, this point needs to be identified as record type so that samples reaching that point can be stored to be used in the future.
While it may be tempting to keep every intermediate step, lab managers should keep in mind that complex rework policies will create a lot of overhead in their processes. They will have to proactively manage additional storage areas. They may also need to validate protocols using intermediate samples used after a period of storage.
The process stability, the value of the samples, and the cost of each of the sample processing steps should be considered when developing rework policies.
Some steps produce data. Others don’t. For example, taking a fraction of an incoming sample may require weighing the sample fraction. The weight is a data point generated by the step. On the other hand, changing a solution from one tube to another does not produce data.
It is generally recommended to avoid defining new record types corresponding to steps not associated with data sources. Since a LIMS is a data store, there is little value in creating LIMS records without data.
Workflow decision points need their own record. Whenever a sample can go into different branches of a workflow, it is necessary to create records that will be connected to different downstream processes.
Example: PCR Testing Workflow
A PCR Test workflow is a representative business process that illustrates all these issues.
A diagnostic lab receives tissues from an external entity. They use only a small fraction of the tissue to perform the analysis. The rest of the tissue samples are stored to be able to redo the test or perform additional tests at a later date.
The tissue fraction is processed to extract the RNA. The fraction goes through different stages of the nucleic acid purification process. It is flash frozen, ground, and lyzed before the RNA is extracted. Then the RNA solution is used to perform the PCR reaction.
In this process, the tissue sample submitted by the client needs to have its own record because it has data associated with it, it will be stored for future use, and it can be reused in follow-up nucleic acid purification.
The PCR reaction needs its own records as well because it has data associated with it.
However, not every stage of the RNA purification process needs its own record. They can all be lumped into a single RNA solution record because they are likely to be performed by the same operator, it is a linear segment of the workflow with no decision points, there is no need for long term storage, and rework policies would probably specify that in case RNA purification fails, the process needs to restart from the sample supplied by the client rather than from an intermediate point.
However, the RNA solution cannot be lumped with the record corresponding with PCR test because a failed PCR test could use the RNA solution as a starting point (rework) and multiple PCR tests can be performed from the same RNA solution (decision point).
GenoFAB can save your lab time and unecessary expenses by allowing your team to streamline their experimental workflows. Book a demo today.