Three Elements to Consider When Digitalizing Your Lab

By Paul Berning

By Paul Berning

In the last five years, we’ve seen a massive movement towards digitalization in life science labs. Whether this was brought on by the challenges we saw during COVID-19 or by the success of the emerging Electronic Lab Notebook (ELN) market (powered by Benching’s efforts), the movement is real. Major biotech and pharma companies are launching digitalization departments to help bridge the technical gaps that labs and companies face. But there are still many questions to be answered: How do you digitalize a lab? What elements should you consider to ensure you do not have technical gaps?  

From a high level, it is important to understand the company’s ultimate goal, which is scientific success. When looking at the scientific process, particularly from an R&D perspective, there is a standard flow to the madness. It is best described in a Design, Build, Test, Learn (DBTL) model. This model can be simplified to Design, Execute, and Analyze when speaking about digitalization and the software stack needed to accomplish this.

Digitalization with Genie

Below, I’ve broken down these three elements and their role in the movement towards digitalization. I’ve also included a rating for each element on a scale of 1-10 in three areas: 

  1. General Product Effectiveness for Customer Goals: How well does this element contribute to the ultimate goal in life sciences, which is to achieve scientific success?
  2. Importance of Products for Digitalization: To what extent will this element close technical gaps as you digitalize your lab?
  3. Value Added to the Scientist for Scientific Success: How much day-to-day value will this element provide in a DBTL environment?

Design (ELN/LIMS)

In order to digitalize your lab, you will need a platform that enables you to organize the chaos or, depending on how you look at it, the creativity. Documentation and collaboration have been a major part of the scientific community for many years, and having ELNs as a part of your build-out is a great start to the process. These platforms allow you to kick off your efforts using their pre-built tools for your specific applications and easily share interfaces. It is also useful for upper management to have visibility into your lab’s efforts. Companies leading in this space include Benchling, LabGuru, and eLabNext.

  • General Product Effectiveness for Customer Goals: 7.5 out of 10
  • Importance of Products for Digitalization: 9 out of 10
  • Value Added to the Scientist for Scientific Success: 3 out of 10

Lab Execution (Schedulers or Orchestrators)

Higher-level automation solutions, such as schedulers and orchestrators, provide a platform for labs to seamlessly automate their scientific workflows (read more about their differences here). Digitization of execution allows you to have common, shared instrument workflows and the ability to digitally abstract physical instruments. Data is generated and stored during the experiment and can be used for instrument usage reports, scientific analysis, and more.

When it comes to developing products that enable labs to digitalize their workflows, lab execution is still in its infancy. We have seen new companies coming to the market with products that aim to fill this gap. While schedulers have dominated the space for many years, their on-premise options offer little to no value to digitalization. As you can imagine, this creates a major challenge. On the one hand, you have great design tools in the cloud that facilitate collaboration, but when it comes to execution in the lab, there are major gaps and open loops on what actually happens in a sample prep or analysis workflow. Admittedly, vendors in the industry need to catch up. Notable scheduler vendors include ThermoFisher Scientific, HighRes Biosolutions, Biosero, and Retisoft. Notable orchestrator vendors include Genie Life Sciences, Unite Labs, and Automata.  

  • General Product Effectiveness for Customer Goals: 2.5 out of 10
  • Importance of Products for Digitalization: 9 out of 10
  • Value Added to the Scientist for Scientific Success: 9 out of 10

Analysis

The analysis component is specific to the scientific application, with many different vendors that could lead the charge. During the analysis stage, data generated during the execution stage is analyzed to increase scientific efficacy. An example of this would be the DBTL cycle we discussed earlier. It is important for scientists to drive this process as quickly, accurately, and efficiently as possible. The value in the analysis stage includes the ability to analyze information and quickly make decisions (new designs). 

For you as the reader, it is hard to generalize this section in terms of digitalization. The status of the current landscape involves massive amounts of time spent by the scientist doing any or all of the following:

  • Copying and pasting information into an ELN or LIMS
  • Creating PowerPoint presentations for group meetings
  • Publishing

Notable vendors in this space include Illumina, Sartorius, and ThermoFisher Scientific.

  • General Product Effectiveness for Customer Goals: 5 out of 10
  •  Importance of Products for Digitalization: 9 out of 10
  •  Value Added to the Scientist for Scientific Success: 9 out of 10

Key Takeaways When Digitalizing Your Lab

When looking at the design and analysis elements, it is clear that these areas in the life sciences digitalization landscape are far ahead of the execution space. This could be for many reasons, but from my perspective, a big reason for this is that many sample prep instruments are decades old. They do not have the ability to integrate and provide sufficient information for the digital world. It will take many more years for them to catch up. Having said that, I encourage individuals looking at vendors to keep this in mind when selecting products. While scientific success is the ultimate goal, having digital-friendly equipment and closed-loop systems will go a long way in scaling your efforts.  

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