Plate maps

What are plate maps in Benchling?

Plate maps provide scientists with easier ways to capture data and draw insights from plate-based experiments. The interactive interface allows users to visually annotate wells with experimental metadata, and fill plates with contents tracked in Benchling. This release helps scientists by:

• Reducing manual data entry - the previous product solution involved having to re-enter data into structured tables, and append custom columns to capture additional well metadata
• Surfacing insights faster - visualizing relevant layers of metadata on a plate makes it faster to identify errors and draw insights about research programs
• Preserving quality data - an immutable record of the actions taken on the plate is saved to the Notebook for data provenance and traceability

With over $3.75 million in lost ARR tied to this product gap since 2022, this release is crucial for scientists working in cell therapy, gene therapy, and antibody discovery across academic, mid-market, and enterprise customers.

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Experimental design and execution as the core problem

Lab work is commonly carried out in plates, yet Benchling (previously) did not provide users with sufficient tools for modeling and capturing data in plate-based work. While the concept of a plate entity in Benchling did exist, it lacked the ability to communicate content information, and capture rich metadata that ultimately aids in experimental analysis. Scientists rarely modeled plates in Benchling despite their ubiquity in the lab. Instead they relied on point solution tools, Excel, or simple tables to achieve their goals.

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Plate layouts have two primary use cases:

Visualizing experimental design - scientists need to plan in advance how a plate will be filled. This planning involves: arranging the contents, setting the volume, and capturing concentration values so that come time of execution (pipetting liquid into wells) the likelihood of error is reduced.

Capture metadata for experimental analysis - during downstream analysis, scientists rely on well-level metadata such as sample identity, conditions, and additional context to interpret results and understand how different variables may have influenced the outcome.

A chronic pain(point)

Documents capturing customer complaints and user research anecdotes regarding plates date all the way back to 2018. As a result, both users and internal customer success teams have developed various workarounds that result in duplicated data and fragmented workflows.

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An interactive plate map to visually plan experiments and capture data

The plate map tool allows scientists to visually plan plate-based experiments and annotate metadata on a plate. The key considerations that influenced the designs were: 

• Cross-app integration - the tool needed to be accessible across apps, specifically Inventory: where lab items are tracked, and Notebook: where experiment context is recorded.
• Build to scale - we optimized the experience for the most commonly used 96-well plates (12x8), but had to consider other varying dimensions from 8 wells (4x2) up to 384 wells(24x16)
• Visual satisfaction - the tool should match the user’s mental model of what a plate looks like when planning experiments (vs. a tabular view, which is more helpful when analyzing an experiment)

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Annotating metadata

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Adding contents to wells by pattern

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Setting volume and concentration for contents

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Visually compare what was planned versus what actually happened in the lab

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Annotating well roles with AI