Streamlining cell line development workflows with automation can be a significant timesaver, but some researchers are unsure of how to most effectively approach implementing automation. In an interview with Lab Manager, Molecular Devices’ Rebecca Kreipke, PhD, shares her insight as to which aspects of CLD are best suited for automation, how it affects scalability, how the role of lab personnel will evolve alongside automated CLD setups, and more. Note: These responses have been edited for style.
Q: What aspects are best suited for automation in CLD, and where is human intervention crucial?
A: Traditional cell line development methods have many steps that are tedious, repetitive, and laborious. From isolation of single cells via manual limiting dilution to daily growth plate checks to confirm monoclonality and verify growth, highly trained scientists must devote many hours per project to verifying the basic integrity of the protocols to ensure pure products. Due to the repetitive nature of these tasks and the number of steps of human intervention, there is also high risk of human error. This is where automation can be of great service to CLD scientists. Instrumentation, such as single cell dispensers and high-speed, high-resolution plate-based imagers (such as those in the Molecular Devices Clone Screening Portfolio) allow the laboratory scientists to offload many of these tedious, repetitive tasks to specialized workcells.
This allows human intervention to be minimized to places in the process where their specialized skill sets can make the most impact—e.g., experimental design and process optimization—rather than being squandered performing the same basic, laborious tasks.
Q: How does automation affect the scalability of cell line development?
A: Laboratory automation allows cell line development to scale in two main ways: the number of projects that can be completed within a certain timeframe and the scope of any individual project. Both provide unique advantages.
Being able to scale up the number of projects a certain group can complete within a specific timeframe is beneficial because it allows for a larger pipeline. Completing more projects allows for increased velocity of product and therapeutic development. This can ultimately result in more products that can serve a wider range of markets and therapeutic areas.
Increasing the scope of individual projects, on the other hand, increases your chances of identifying the optimal product. The ability to screen from a larger starting pool or greater library increases the chances that the “best” target identified is, in fact, the best that can be produced and not just the best that could be identified in the time available with the resources at hand.
Lastly, the data tracking and reporting features available on laboratory instrumentation allows scientists to be more confident in the decisions they make and the cell lines they move forward. The objective and automatically compiled data collected from laboratory instruments increases the integrity of the data packages and decreases the risk of user error.
Q: Are there any considerations researchers should keep in mind when transitioning from small-scale to large-scale production?
A: Laboratory automation is, ultimately, the result of active collaboration between biological and technological specialists. It is important to recognize the contribution of both halves of that equation, while also maintaining open communication so that expectations, needs, and capabilities can be appropriately scoped, designed, and implemented.
From a biological perspective, when introducing automation into a workflow for the first time, it is critical to have a well developed and reliable protocol. If you are still optimizing your biology, it can become difficult to properly design and/or troubleshoot a workcell, as you will be aiming for a moving target in terms of whether it’s “working properly" or not. Having a very clear and detailed protocol to share with your automation team will go a long way towards helping ensure that the system that is designed is able to meet both your biological and throughput needs.
Additionally, it is good to keep in mind that the way a protocol is executed may look quite different in an automated set up when compared to manual processes. Collaboration between biologists and engineers is a key part of the process of successful automation deployment. The Molecular Devices Automation Team includes a wide range of specialists, ranging from applications scientists to automation engineers and programmers. This allows us to fully understand a workflow from both a biological and technical perspective, so that we are providing solutions that are custom tailored to your exact needs.
Q: How do you see the role of lab personnel evolving in automated cell line development setups?
A: Researchers should be extremely excited about the advances that automated cell line development setups will bring to the lab. Rather than engaging in hours upon hours of tedious, labor-intensive, repetitive tasks, they will be able to harness the full extent of their scientific training, focusing instead on experimental design and data analysis.
Q: What new skillsets or expertise might be required for researchers to effectively work with automated systems?
A: It is inevitable that with technological shifts in the way science is conducted, that the skill sets required to engage in scientific inquiry would shift. I think it’s possible that we will see a bifurcation of the skills needed to run cell line development projects in highly automated environments. It will be critical for labs to invest in personnel who can maintain, update, and troubleshoot large and complex automated work cells. These individuals will be required in order to make sure that any deployed automated workcell can keep pace with the advances in research tools, altering the workflows as needed.
It will also require scientists to begin to think take a higher level, more systems approach to experimental designs. Rather than needing to specialize in both designing and running assays, the ability to take advantage of the robotics and the increased access to data will allow researchers to design more complex, combinatorial experiments, yielding more and higher quality results.
Rebecca Kreipke, PhD, is the western markets field applications scientist manager, biopharma, at Molecular Devices. She helps scientists automate and scale their workflows to quicken discovery and decrease development timelines. Kreipke has a PhD in neuroscience.