Choosing a scheduling software — factors to consider

July 28, 2021  |  Technology

Scheduling software is a must-have tool for automation in laboratories. From individual robots to integrated workstations, scheduling software issues the commands that let scientific processes happen without human intervention.

Scheduling software has been around for more than 30 years, with today’s sophisticated, AI-powered solutions offering a vast improvement over the more rudimentary tools that were first available to the lab community. There are plenty of options on the market. Here at Biosero, we offer Green Button Go® software for lab automation, including scheduling software that’s among the best in the business. But you shouldn’t take our word for that. So how do you go about choosing the scheduling software that’s right for your lab?

While there are many similarities across the commercially available scheduling tools now — including scripting capabilities and the ability to integrate data upstream and downstream of a workflow — one of the real differentiators is their abstraction level, which includes the user interface and the scheduler type that is used to automate workflow processes.

The abstraction level refers to how a workflow is defined with the scheduler. With very high abstraction levels, a user simply maps out the flow of labware and data to perform a specific workflow. With other software packages, the description of the workflow is defined at a much lower level, using pseudo-code where programming constructs such as loops and decision trees are utilized to automate the process. The level chosen is based on balancing flexibility and simplicity, and the best solution is often determined by the expertise available and how frequently a lab needs to change its workflows.

In addition, some schedulers are suited to specific assays. For an ELISA workflow, for instance, a static scheduler might be best for performing exact incubations after the addition of a substrate. This type of scheduler can ensure that resources are available ahead of time to avoid the scenario where an incubation step completes, but the robot is busy with another activity. But an event-driven, dynamic scheduler might be a better option for a workflow that uses data generated during the run to determine the next steps to perform.

Driver availability is another factor to consider. In addition to having readily available drivers for a lab’s current set of instrumentation, it’s important to know how long it will take the software provider to develop and distribute new drivers for instruments that may be added later.

Error correction should be evaluated as well. In any workflow, there will be errors, and how the software handles those events is critical to the lab’s success. Schedulers that use nimble, AI-powered tools to manage errors on the fly without having to shut down entire pipelines will be more productive than tools requiring human intervention to get underway again.

Flexibility and expandability are also two very important aspects of a good scheduling software, due to how quickly processes and projects change within the laboratory environment and the pace at which overall technology is advancing.  For this reason, a Scheduler should be designed with a modular, plug-in architecture, which provides the ability to seamlessly add or extend functionality beyond the core scheduling foundation.  These modular plug-ins, also known as Extensions, extend the capability of the core software by adding new scheduling paradigms, modes of operations, and application specific augmentation without modifying the base code.

For our Green Button Go Scheduler, we prioritize flexibility for our users. While our tool operates at a high abstraction level to make it easy to automate multi-plate processes with several incubation steps, it also provides a lower level of control for users who want the ability to implement specific functionality or do things a little differently. Unlike other scheduling tools, it can perform as a static scheduler or a dynamic scheduler depending on the lab’s needs. Our Scheduling Software is built with a modular architecture, which enables continuous evolution through the addition of our extensions. Green Button Go Scheduler was developed for a wide range of users, with great functionality for people who just want a simple tool, as well as much more sophisticated options for users who enjoy diving into the code.

Learn more about Green Button Go scheduling software or check out this short video.