Introducing a New Strain Screening Paradigm

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How empowering strain engineering groups with Culture's cloud bioreactor capacity can accelerate R&D

If you work on developing and improving new strains of microorganisms at a large biotech company, you've likely been in a situation where you need the bioreactor data from your last strain screening experiment to inform your next set of strain edits, but you don’t have the data in time. You often end up receiving the strain screening results after you've already built the next set of strains to be screened. You might think to yourself "if only I knew these learnings a week ago, I would have built this next set of strains differently," and now you have to wait until the next cycle to incorporate those insights.

Can you relate to this frustration? 

There are a few reasons that your strain data might be getting delayed...


3 ways strain data gets delayed

1. Not enough bioreactor capacity

At established biotech companies, there are often a dozen programs running at once, meaning multiple groups are competing for limited bioreactor capacity. In this scenario, you can’t test your new strains because internal capacity is already reserved, and there might not be an opening for a few weeks.

2. Not enough staff

Even in a perfect world where you have enough capacity, there’s often a delay in receiving strain data because of a lack of staffing resources. The process development team who screens your strains may be swamped running experiments, so they haven’t gotten a chance to gather results and send you the data. After all, they can only do so much in between running reactors. In this case, your experiments may have been performed, but you don’t have access to the data report you need to make critical decisions. 

3. Not running enough replicates

Running an inadequate number of replicates can have serious consequences for your strain development programs and overall progress. If your sample size is too small, you may be getting false-positive results, meaning you’re promoting strains that are no better than the control strain. Or, you may be getting false negatives and missing the strain that could be your new production strain. Either way, you’re wasting time and resources, slowing progress, and potentially missing milestones. For example, if you have a 25% false-positive rate and you’re not accounting for that, you’re effectively adding 25% more time to your process because you’re promoting strains that are not in fact improved. You could have had statistically significant data weeks or months before if you had run enough replicates the first time.

Did any of those scenarios sound familiar?


The new strain screening paradigm

Now imagine you could get statistically significant strain screening data, instantly. With Culture’s cloud lab, you can. Instead of competing for internal capacity and resources, reserve dedicated bioreactors in our lab and use our online portal, Console, to view your strain data in real time, right from your laptop. You can have the infrastructure you need for your strain development work rather than competing with other groups for it, meaning no more lag in bioreactor data (Figure 1). Plus, dedicated capacity allows you to generate fermentation data for a wide range of strains at the outset, a crucial but often missed step in building a predictive plate-to-tank model. Once you improve your plate model, you can send better strains to fermentation. Conversely, if you fail to get that fermentation data upfront, your plate model will perpetually be in development.


Culture Model BPG2

Figure 1: In the legacy model, the strain development team has to send their strains to the process development team to be screened and then wait until the data is ready. In Culture's model (above), strain engineers can use dedicated bioreactor capacity at Culture to screen their strains and receive bioreactor data in real time. This way, they accelerate their DBTL cycle and send only the best-performing strains to fermentation without the back-and-forth.


Additional capacity through Culture means you can screen as many strains as you have and run as many replicates as you need to get statistically significant results; you no longer have to choose between the throughput of strains and statistical significance - between quantity and quality. Most importantly, you can avoid promoting the wrong strains - and wasting time and money - by running the right number of replicates from the start. In doing so, you can complete more Design-Build-Test-Learn cycles in a shorter period of time (Figure 2). And with Culture’s high success rates and low variation, you can be confident you’re getting reproducible results.


Accelerate strain development by running enough replicates for a statistically powered experiment:


Figure 2: Culture's cloud bioreactor capacity enables you to run all your strains at once with the right number of replicates the first time so that you can complete 3x more DBTL cycles in the time you could normally complete one cycle.


How do you know if you’re running enough replicates for a statistically powered experiment?

You'll need to conduct a power analysis to determine the correct number of replicates for your experiment. Learn how in our Guide for Running Statistically Powered Strain-Screening Experiments. Or even easier, use our replicate calculator to determine your sample size for a statistically powered strain-screening experiment.

Read the Guide


Everyone in your R&D department benefits from the new strain screening model

This new model doesn’t just make strain engineers’ lives easier. It also helps…

Process development groups

By outsourcing strain screening to Culture, your fermentation team can avoid the operational inefficiencies of switching back and forth between process development and strain screening. It also lightens the workload for process engineers and allows them to re-focus their efforts; instead of spending time on the execution of strain screening, process engineers can spend time on what they really want to and should be doing - developing and improving processes. Additionally, strain screening requires a lot of internal capacity, taking reactors away from other programs. Leveraging Culture for strain screening frees up internal capacity for the process development work that needs the PD group's expertise and attention.

VPs or directors managing a portfolio

As a portfolio manager, do you spend time every month or quarter going through prioritization assessments only to sacrifice one project for another? What if you could regain that time spent re-shuffling projects and run all your programs instead of making cuts? Partnering with Culture would give you the capacity and resources you need to advance current programs and greenlight new ones. And, rather than juggling multiple projects internally and constantly pivoting, your teams could stay on course and make more progress toward milestones.


You might be thinking…The new model seems better, but we’ve always done strain screening this way. Why should we change now?

Aren’t you tired of the constant stress from scrambling to meet project milestones? Or missing them altogether? This could be the change that saves you six months - the change that helps you get your new production strain well ahead of your deadline. With Culture, get access to high-throughput reactors to accelerate your strain development and accomplish more internally.

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