Buying an Electronic Lab Notebook | Sapio Sciences Blog

02/15/2022

Buying the Right Electronic Lab Notebook is Hard

Today there are likely 50+ Electronic Lab Notebooks (ELN) on the market.  Given that, how is one to find the right one for their needs?  Well, it’s not easy is the truth.  Therefore it’s important to not be hasty in your selection or to simply buy the low cost option that “looks OK.”

ELN’s have Evolved from their Chemistry Roots

If you go back 20 years or so almost all Electronic Lab Notebooks were chemistry focused.  They would help you design molecules, the primary drug type at the time, and inventory them, search for them etc.  If you were a chemist, these were great tools to assist you in your day to day scientific work.  But they really were not intended or designed to be general lab notebooks, or able to deal with new treatment modalities with the introduction of large molecules in more recent times.

The ELN Evolution continues, but now with a heavy focus on Large Molecule

History has repeated itself now with ELN’s now being introduced that target large molecule work with tools like plasmid editors, but also some more general lab notebook capabilities like a registry and general note taking capabilities.   The chem ELN vendors are also trying, usually via acquisition or partnerships, to address their shortcomings in the large molecule space, and the large molecule ELN vendors are trying to incorporate small molecule support as well.

The problem with both ELN approaches is three-fold:

  • They still primarily focus on either small or large molecules and are not general ELN platforms that do equally well in either domain
  • They do not sufficiently address LIMS system needs as this is still viewed as a separate application domain
  • Buying a bunch of different solutions, even with prebuilt integrations, still creates a discontinuity of workflow, user and administrative experience

A Digital Transformation Perspective

Instead of looking to buy an ELN or a LIMS, you should look for an informatics platform that unites both LIMS and ELN features into a single, low-code, no-code solution.  The ideal electronic lab notebook should also be the ideal LIMS system, no matter what types of drugs you are creating or processes you are modeling.  It should also include science aware tools for designing molecules, reactions, plasmids, or CRISPR even.  But it should also include powerful searching, data visualizations, and informatics so you can search, visualize and analyse data across your enterprise that has been digitally transformed.  It should be quickly adaptable, the hallmark of a platform, even if it lacks something you need.

What to watch out for

Some vendors perform excellent packaged demos, and/or instead of selling their solution sell you on who else they have sold to.  Also watch out for vendors whose organization is largely comprised of sales people.  If you are getting calls from multiple sales people from the same company, run the other way!

It’s critical to perform your own, detailed evaluation!  Make the vendor do a deep dive into their product…get them outside their comfort zone by presenting challenges to them that go beyond their well crafted demo.  If they don’t step up to the plate and show they can do it then its likely their solution is not really a platform and will be hard to implement or even get to do what you need at all no matter the amount of money and time you throw at it.

We will close with a comment from Kevin, our CEO and Chief Scientist, “Increasingly biotech and pharma R&D organizations are looking for our unified low-code, no-code informatics platform on which all our applications are built and tightly integrated.  This enables our customers to digitally transform their organizations to streamline their operations, reduce costs and accelerate discovery which is our driving mission.  We aim to support design of molecules, both small and large…to make data collection and searching easy, and then to enable powerful data visualizations and assistive data interpretation using advanced analytics and machine learning to facilitate scientists R&D efforts.”