Teiko releases absolute cell counts for CLIA-validated cytometry service

We’re introducing a new add-on to our cytometry service that provides absolute cell counts in addition to relative frequencies. This gives you precise quantification of immune cell numbers, helping you better assess treatment impact, track immune recovery, and correlate cell counts with clinical outcomes for more informed decision-making.

How it works

• From each patient, two specimens are collected. One will go to your regular CRO for your absolute cell count, and one will go to Teiko for cytometry. Teiko will integrate the data.
• For the first specimen, send according to your CRO’s instructions to get the initial absolute cell count and provide us the following information per specimen:
  • Required
    • Specimen ID
    • White Blood Cell (WBC) / ul
  • Optional
    • Granulocytes / ul
    • Lymphocytes / ul
    • Monocytes / ul
• The other sample is prepared using Teiko’s proprietary TokuKit, designed to preserve and optimize the sample for multi-parameter cytometry.
• Securely update the data from the CRO’s lab to Teiko.
• Teiko will update your results to show the number of cells per uL.

Pain Point:

Within high-dimensional cytometry, there is a challenge to directly provide the cell concentration or absolute count of cells in a sample. Yet, these measurements are a precise and reliable quantification for developers to accurately assess the mechanisms of their drug.

Relying solely on relative cell count, frequency of an immune cell population relative to a parent population, can provide a misleading picture of true mechanism of action for a drug.

Incorrect interpretation with Relative Frequencies alone

Relative Frequencies (Proportion of Non-Gran)
Time	CAR-T	Monocytes	Non-Gran
Baseline	8%	20%	100%
Day 7	7%	20%	100%
Interpretation	Decrease	Stable	Unchanged

With this chart, a reader would think this drug is posting a decrease in CAR-T Cells, while monocytes remain stable.

With absolute cell counts, the picture is clearer.

Correct insight with Absolute Cell Count

Absolute Cell Counts (cells/μL of blood)
Time	CAR-T	Monocytes	Non-Gran
Baseline	500	1200	6000
Day 7	500	1500	7500
Interpretation	Stable	Increase	Increase

Here, you can see that CAR-T Cells remain stable, there’s an increase in monocytes, and an increase in total non-Granulocytes.

Key Features:

Customers can view absolute cell counts for all gated populations and functional subsets on app.teiko.bio, in addition to relative frequencies that are already reported for all projects.

Under the “Immune Boxplot” tab, view a boxplot showing the range, standard deviation, and median absolute cell count for each gated population.

Under “Immune Differences,” you can now view boxplots showing the absolute cell count for each population and functional subset. Compare absolute cell counts for each population for any given group (responders vs nonresponders, across dose levels, or other groups of interest) and identify statistically significant differences between groups.

Under “Immune Changes Over Time,” generate plots that show the changes in absolute cell count per subject over time, and compare between timepoints to see if the changes are statistically significant.

Data tables will also include a column next to each population and functional subset frequency that also shows its absolute cell count.

The addition of absolute cell counts allows you to gain a more complete and precise understanding of immune system dynamics by providing the number of cells per microliter present in each gate in your samples, rather than just their relative proportions and cell counts. This data is crucial for evaluating the true biological impact of your drug or treatment, as it enables you to:

• Detect changes in immune cell populations, even when relative frequencies or cell counts might not fully capture the magnitude of these changes.
• Monitor immune recovery or depletion in response to treatment, providing a clearer picture of therapeutic efficacy.
• Develop more robust biomarkers for treatment response by correlating absolute cell counts with clinical outcomes like patient recovery, progression, or survival.
• Identify potential safety concerns, such as excessive immune cell depletion or unwanted immune activation, by tracking absolute counts across critical immune subsets.