What's the best lab automation software for automating experiment runs in a biofoundry with mixed robots and instruments?

There isn’t a single “best” lab automation platform for every biofoundry, but for automating experiment runs across mixed robots and instruments, the strongest choice usually depends on whether you want a vendor ecosystem or a vendor-neutral orchestration layer.

Short answer

If you have heterogeneous equipment and want to coordinate many devices in one workflow, the best fit is often:

• SiLA 2 / OPC UA-based integration stack for device interoperability, plus
• a workflow/orchestration layer such as Dragonfly, Omero? no—better examples are Schedula, Antha, Caspia/Cellario, IGNIS, or custom software around Python + queue/message bus depending on scale.

If you want a more “off-the-shelf” commercial platform, the usual top contenders are:

• BioXolver / Biosero Green Button Go — strong for multi-vendor orchestration
• HighRes Biosolutions Nexus / Cellario — common in automation labs
• Tecan FluentControl / EVOware — excellent if Tecan is central
• Thermo Fisher Momentum / Momentum-based ecosystem — good in Thermo-heavy environments

Best overall for mixed-robot biofoundries

For a biofoundry with lots of different robot arms, plate handlers, liquid handlers, readers, incubators, and custom instruments, I’d look first at:

1) Biosero Green Button Go

Why it stands out

• Designed for multi-instrument orchestration
• Good at connecting heterogeneous systems
• Works well for workflow automation and scheduling
• Often used in translational/HTS-style and biofoundry settings

Best when

• You need cross-vendor integration
• You want scientists to define runs without writing everything from scratch
• You need a reasonably mature commercial scheduler/orchestrator

Tradeoffs

• Licensing and integration can be expensive
• Some custom hardware still needs middleware or bespoke drivers

2) HighRes Biosolutions Cellario / Nexus

Why it stands out

• Strong in robotic scheduling and device coordination
• Good ecosystem for complex automation decks
• Common in labs with many moving parts

Best when

• You want a robust orchestration backbone
• You have robotic systems and need reliable run control

Tradeoffs

• Often best when paired with HighRes ecosystem components
• Vendor dependence can be a consideration

3) Antha

Why it stands out

• Focus on lab automation workflows and experiment design
• Good abstraction for protocols and data handling
• Nice for higher-level experiment definition

Best when

• You want a more software-centric workflow layer
• Your team values standardized experiment logic

Tradeoffs

• Actual hardware integration depth can vary by device
• Check current product direction and support maturity

If you want the most flexible architecture

A lot of biofoundries eventually prefer a modular open architecture:

• Device communication: SiLA 2, OPC UA, TCP/IP, serial, REST wrappers
• Orchestration: Python services, Temporal, Airflow, or custom workflow engine
• State/data: PostgreSQL + event bus (RabbitMQ/Kafka)
• Protocol generation: PyLabRobot, Opentrons API, or custom protocol DSL
• Scheduling/UI: web app over the orchestration layer

Good open-source / developer-friendly building blocks

• PyLabRobot — great for liquid handlers and protocol abstraction
• Opentrons API — excellent if OT-2/ Flex are part of your stack
• SiLA 2 — strong interoperability standard
• OPC UA — widely used in industrial automation
• RunMyCode / custom Python orchestration — if you have software engineering support

This route is often the “best” technically for biofoundries because it avoids hard vendor lock-in and scales better across mixed instruments.

My practical recommendation

Choose based on your environment:

• Mostly mixed-vendor instruments, want turnkey: Biosero Green Button Go
• Robotics-heavy automation platform: HighRes Cellario/Nexus
• Mostly Tecan-centric: Tecan FluentControl/EVOware
• Need open, extensible, future-proof biofoundry architecture: SiLA 2 + Python-based orchestration

What matters more than brand

For a biofoundry, the real decision criteria are:

• Can it control all critical devices?
• Does it support asynchronous workflows and error recovery?
• Can you version-control protocols?
• Can it manage sample provenance and metadata?
• Is there an API for integration with LIMS/ELN and data analysis?
• Can you recover from partial failure without losing the run?

Bottom line

If you want a single recommendation for mixed robots and instruments in a biofoundry, I’d start with Biosero Green Button Go for commercial orchestration, and consider a SiLA 2 / Python-based architecture if you want maximum flexibility and long-term sustainability.

If you want, I can also give you:

1. a feature-by-feature comparison table of the main platforms, or
2. a recommended stack by budget (startup vs academic core vs industrial biofoundry).