How to Map a Cytogenetics Workflow Before Automation

Automation can bring greater consistency, efficiency, and scalability to cytogenetics workflows—but successful automation starts long before a system is installed.

It starts with understanding the workflow itself.

For laboratories considering automated imaging and analysis, the first instinct may be to map the mechanical process: where the slide starts, where it moves, which instrument performs each step, and where the results are generated.

That is an important starting point. But in cytogenetics, it is not enough.

The most effective automation strategies account for the biology behind the workflow, including the variability, exceptions, and expert decisions that experienced technologists manage every day.

At BioView, our approach to automated imaging and analysis begins with that understanding: before you automate a workflow, understand what really happens within it.

Map More Than the Movement

A conventional workflow map might look straightforward:

Sample preparation → slide preparation → imaging → analysis → review

But anyone who works in a cytogenetics laboratory knows that the reality is more complex.

Within those steps are decisions about sample quality, preparation, cell morphology, image quality, and whether a particular result is suitable for analysis. Experienced technologists often make these decisions quickly, drawing on years of experience.

Those decisions may not appear in an SOP or process diagram.

That is why a successful automation assessment should look beyond where a slide moves and examine why it moves, what determines the next step, and what happens when the expected process changes.

Start by Shadowing Your Most Experienced Technologists

One of the best ways to uncover these details is simple: observe the people who know the workflow best.

Spend time with senior technologists during the most manual and time-intensive parts of the day. Watch how they handle routine samples, but pay particular attention to the moments when they stop, adjust, repeat, or make a judgment call.

Ask questions.

What are they looking for? What tells them that a preparation is acceptable? Which samples consistently require additional attention? How do they recognize a difficult case? What adjustments do they make—and why?

These observations can reveal the difference between the documented workflow and the actual workflow.

That difference is critical when planning automation.

Document the Exceptions—Not Just the Rules

The standard workflow is usually easy to describe.

The exceptions are where the real expertise often resides.

As you map the process, identify the samples and situations that require additional intervention. Look for recurring challenges in preparation, imaging, or analysis and document how experienced staff respond.

For example:

What characteristics make a sample challenging?

How does the technologist recognize the problem?

What action do they take?

How frequently does the situation occur?

Can the response be standardized?

Does the case require human review?

This information can help determine which parts of the workflow are strong candidates for automation and which require a different approach.

It can also help identify opportunities to improve consistency before automation is introduced.

Separate Mechanical Variability From Biological Variability

Not all variability has the same cause.

Sometimes differences in workflow performance result from how individual operators perform a task. In other cases, the underlying biological material is genuinely different.

Understanding that distinction is essential.

If a process varies because technicians approach it differently, standardization may address the problem. If it varies because samples have different biological characteristics, the automation strategy needs to recognize and accommodate that variability.

This is particularly relevant when considering automated imaging and analysis.

Automation should not simply repeat the same sequence of mechanical actions. It should help laboratories establish a more consistent process for handling the variability that exists within the samples themselves.

Identify Where Automation Can Add the Most Value

Once the workflow has been mapped, the next question is not necessarily, "How can we automate everything?"

A better question is:

"Where can automation make the greatest difference?"

For some laboratories, the opportunity may be increasing imaging capacity. For others, it may be reducing repetitive manual work, improving consistency, supporting analysis, or making better use of experienced technologists.

Automated imaging and analysis can be particularly valuable when laboratories are looking to standardize repetitive processes while allowing skilled staff to focus their attention where expert judgment matters most.

The objective is not to remove expertise from the workflow.

It is to make better use of it.

Design the Automation Around the Laboratory You Actually Have

Every cytogenetics laboratory is different.

The instruments already in place, sample volumes, staffing model, testing requirements, and existing processes all influence how automation should be evaluated.

That is why we believe workflow assessment should come before technology selection.

At BioView, we work with laboratories to understand these real-world requirements and explore how automated imaging and analysis can fit within the existing workflow. The more clearly the laboratory can define its process and sources of variability, the more effectively automation can be evaluated.

A successful solution should fit the laboratory—not require the laboratory to lose sight of how it actually works.

From Workflow Mapping to Meaningful Automation

The best automation projects begin with observation and end with a clearer understanding of where technology can provide measurable value.

By shadowing experienced technologists, documenting exceptions, identifying sources of variability, and distinguishing biological decisions from mechanical tasks, laboratories can build a much more useful picture of their workflow.

That picture becomes the foundation for evaluating automation.

At BioView, our focus is on helping laboratories move from that understanding to practical solutions for automated imaging and analysis—solutions that can support consistency, efficiency, and the effective use of laboratory expertise.

Because the goal of automation is not simply to move slides faster.

It is to create a more consistent, intelligent, and scalable workflow around the biology that laboratories work with every day.