The Silent Innovation Killer: Old school ELN & LIMS

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The Silent Innovation Killer: Old school ELN & LIMS

I was speaking with a customer who said something that struck me:

“You have built something that defines its own category. It is like an alternative to redundant ELN and LIMS. This alternative is needed for my evolving biotech workflows especially with my focus on AI and data science”

This inspired me to write this article. I believe ELN and LIMS are redundant. Their adoption rate in biotech companies is so poor that it warrants us to re-define this category. 

Why?

  • Back in early 2000s when ELN & LIMS started to get popular, our core goal as Biotech companies were digital transformation
  • Biotech companies wanted to stitch together their inventory with experiments and sample management workflows

However,

The trend has massively shifted towards data infrastructure. Here are a few trends that are causing biotech leaders to think beyond ELN and LIMS

  • Data usability and data accessibility is a core problem to make data F.A.I.R.
  • Dry labs are sprouting all across the world
  • Wet lab scientists are empowered with no-code tools
  • There is a massive chasm between computational biologists (CLI) and wet lab folks (GUI)
  • Data science is at the core of Biotech innovation
CRO management, CRO data

And, we don't have a single ELN or LIMS that caters to data science workflows. That stitches wet lab and computational workflows. That empowers wet lab scientists to write SQL or python without knowing these programming languages.

Often, I see leaders in Biotech companies trying to retro fit their evolving needs into old school ELN and LIMS. It doesn't work and even if it does the adoption is appalling.

ELN & LIMS are not data infrastructure - they solve a data management problem we had a decade ago. We need alt-ELN and alt-LIMS that are built as API-first data infrastructure

This is why we are so excited about what we have built at Scispot. I like to call it alt-ELN, alt-LIMS data infrastructure. It's like we have genetically engineered the dinosaur for this day and age of LLMs.

  • Data usability and accessibility is solved by building ontologies as graphical databases
  • Dry labs can easily connect using API-first infrastructure (docs.scispot.com)
  • Wet lab scientist are empowered with GUI and AI to write queries and python code using natural language
  • Computation biologists can easily push or pull their results as protocols are like JSON structure accessible by Jupyter Hub or API

The Biotech industry needs an upgrade. It is time to build or buy an alt ELN and alt LIMS that provides you the data infrastructure mapped to modern workflows. 

Time to genetically modify the old school dinosaur into a genetically modified modern dino that helps us build AI-first Biotech companies. Whether you buy or build an alt-ELN & alt-LIMS, make sure you think of the following:

  1. It is API-first - easily connect with disparate systems
  2. I can configure it for my evolving workflows in a secure and compliant way. For example - Can I build my own data dictionary and chain of custody without breaking my data lineage?
  3. Can I evolve my data ontologies without taking zillion of years. I mean that is an exaggeration, but can you build and configure on top of alt-ELN and alt-LIMS

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