Biology is moving from benches to bots.
The Traditional Wet Lab Is Becoming Obsolete
Why manual lab work can’t keep up
For decades, biology meant hands-on work—pipettes, test tubes, hours of trial and error. But biology’s complexity has outpaced what human hands can reliably manage. Enter the biofoundry: a fully automated, cloud-connected system for designing, building, and testing biological systems.
This is the automation of biology, and it’s rewriting how science gets done.
What Biofoundries Automate
Beyond pipetting—full-cycle biological engineering
Biofoundries automate the full Design–Build–Test–Learn (DBTL) loop of synthetic biology:
- Design: AI-driven software generates genetic blueprints.
- Build: Robotics assemble DNA, edit organisms, and prepare cultures.
- Test: Sensors and assays capture detailed data from biological activity.
- Learn: Results loop back into algorithms for the next iteration.
Every step that used to require skilled technicians is now programmable and reproducible—at scale.
Why This Changes Everything
Speed, scale, and standardization
- Speed: Experiments run in parallel, around the clock.
- Scale: Thousands of designs can be built and tested simultaneously.
- Consistency: Fewer errors, tighter quality control, and better reproducibility.
- Remote access: Scientists can launch and monitor experiments from anywhere.
Wet labs are no longer the only option. In many cases, they’re no longer competitive.
The Cloud Lab Revolution
Biology as a service
Cloud labs—virtual platforms where users run physical experiments remotely—are becoming the new normal. Companies like Strateos and Emerald Cloud Lab allow researchers to:
- Upload experimental plans
- Schedule runs on robotic equipment
- Monitor results via dashboard
- Iterate designs without ever entering a lab
This model reduces costs and expands access, allowing small teams or under-resourced institutions to run cutting-edge experiments.
Who Benefits from Automation in Biology
Winners in the new ecosystem
- Startups and SMEs: Rapid prototyping without lab overhead
- Universities: Scalable platforms for research and student training
- Governments: Faster response to public health and security needs
- Investors: Predictable pipelines for biotech innovation
Automation makes biology faster to test, easier to scale, and more investment-ready.
What This Means for STEM Education
Goodbye glassware, hello cloud console
Educators must prepare students for automated, data-driven biology. That means:
- Teaching experimental design with computational tools
- Introducing students to cloud labs and digital workflows
- Prioritizing data analysis, modeling, and decision-making over manual technique
- Embedding ethics of automation and dual-use biotech early in curricula
Today’s learners need to know how to run a lab without being in one.
What Parents Should Know
Biotech jobs are shifting fast
As biology becomes more like engineering, future jobs in the field will require:
- Comfort with automation systems
- Fluency in both life sciences and code
- Understanding of biological manufacturing and real-time data loops
- Cross-functional thinking between science, tech, and policy
The job title “biologist” will soon imply a very different skillset than it did just a decade ago.
Final Insight
Automation isn’t replacing biology—it’s upgrading it
The automation of biology is not a loss. It’s a leap. Biofoundries allow us to design living systems with the same control and speed we expect from software. The scientists of tomorrow won’t just run experiments—they’ll orchestrate them, model them, and refine them continuously through machines.
