Category: Announcements

Komorebi | 木漏れ日
“Sunlight filtering through leaves” [1]

Can’t stand hunting through a cytometry dashboard to find the exact filters to be able to do statistically valid comparisons? Neither can we. 

Out of that frustration, we’ve just released “Automatic search for valid statistics”, now on your app.teiko.bio dashboard.

The Challenge: Clinical datasets have missing values. It’s a reality of running clinical trials: patients miss a dose, something doesn’t get measured, etc. The show must still go on. 

However, finding exactly which sets of samples you can even do a statistical comparison on is still too tough. 

For example, your favorite graphing software stumbles on a deceptively simple dataset like this:

To make valid paired statistical comparisons for responders, you have to hunt for all 17 subjects that have both a Baseline and On-treatment samples, set the filter and run the test. This is both error-prone, time-consuming and difficult, because you would have to find the 10 samples (i.e. 27 Baseline – 17 on-treatment) that don’t have a corresponding pair.

The Solution: Our new automatic search tool scans our statistical test database for “tallies” – complete records based on a specified endpoint and cell types. We then auto-apply the right filters so you can see valid statistical comparisons.

In the case above, the result of the automatic filtering, you would see only the 17 baseline samples that had a corresponding non-responder pair. Compare this to trying to find all 10 samples that don’t have a corresponding pair. Huge time saver.

Available now at app.teiko.bio, this feature simplifies high-dimensional cytometry analysis for clinical trial teams. Check out the demo at app.teiko.bio.

If there are no statistics showing on the dashboard, this button becomes enabled, allowing you to do this automatic search.

[1] Literally “sunlight filtering through leaves,” this term encapsulates the natural, transient interplay of light and shadow, evoking a sense of wonder and subtle beauty.

Yokozuna | 横綱 | Champion Sumo Wrestler

We’re excited to announce an update to our CLIA-validated cytometry service, enhancing your ability to analyze immune cell dynamics with greater precision and clarity. This update is now available for customers using our TokuKit fixed whole blood samples.

Key Updates

1. Expanded Data Visualization: Absolute Cell Counts, Relative Cell Frequencies, and Event Counts
   Our dashboard now includes three measurements: absolute cell counts (measured in cells per uL), relative cell frequencies (measured in percentages, i.e. % of Leukocytes), and event counts recorded by the instrument.
   • You can now:
     • View absolute cell counts for all gated populations and functional subsets on app.teiko.bio.
     • Access boxplots, stacked bars, and other visualizations showing absolute cell counts, to assess treatment response, track immune recovery, and correlate cell numbers with clinical outcomes more accurately.
     • Identify statistically significant differences in absolute cell counts between groups or over time, offering deeper insights into your drug’s mechanism of action.
   • This feature is currently exclusive to customers using Teiko’s TokuKit on fixed whole blood samples. To access these enhancements, ensure your samples are prepared using TokuKit, and securely integrate your CRO’s absolute cell count data with our dashboard. Stay tuned for future development of this feature on PBMCs.
   • Why even bother to look at absolute cell counts?
     • Absolute cell counts provide precise quantification of immune cell numbers per microliter of blood, addressing the limitations of relying solely on relative frequencies. This update helps you detect subtle changes in immune populations, monitor therapeutic efficacy, develop robust biomarkers, and identify safety concerns with greater confidence.

2. Unified Immune Changes Tab: We’ve simplified our Dashboard by consolidating the “Immune Changes Over Time” and “Immune Differences” tabs into a single, intuitive “Immune Changes” tab. Under one tab, you can compare changes in immune cell populations over time and across groups (e.g., responders vs. non-responders), streamlining workflow and data interpretation. When you click an endpoint that has time, you’ll see a drop-down showing specific time-series toggles, like “Connect Timepoints by Subject.” When you click an endpoint that’s not time-based, these will disappear.

3. Smarter Memory: Now, if you select a set of cells, i.e. “Switched B Memory” in Population Frequencies, and switch tabs to Population Counts, we’ll remember the settings you picked. This saves you time so you don’t have to hunt and click through menus to get your desired results.

We’re excited to present our latest research at the first-ever American Association for Cancer Research in Immuno-oncology (AACR IO), highlighting findings that challenge traditional assumptions about fresh blood processing in cytometry. We’ll be at the conference from February 23rd to 26th, sharing insights from our newest study.

🔬 Introducing the “Fresh-Hour” ⏰🩸
Our research looks to see how delays in processing, measured in hours after blood draw (or “Fresh-Hours”), reflective of processing whole blood live within a 72-hour window of collection like in a clinical trial, impact cytometry results.

Here’s what we discovered:

Blood processed within 5 hours (“Fresh-5”) maintained stable immune cell population frequencies.
By 72 hours (“Fresh-72”), there was a 48% percent drop in immune cell counts from t = 0, highlighting the need for new approaches to profile blood by cytometry to ensure the results reflect the true biology of patients.

Come visit us at AACR IO and reach out to set up a meeting—we’d love to connect!

Title: Are fresh specimens really all that fresh? An examination of cell loss over time in high-parameter cytometry.
Presentation Time: Poster Session A, February 24, 2025, 1:45-4:45 p.m. PT
Presenting Author: @Carly Lancaster
Poster Number: A072

TokuFocus: Announcing “focused” panels for spectral flow and mass cytometry.

Codename: Daiki | 大喜 | Champion Sumo Wrestler

Teiko’s cytometry services allow you to measure 146 – 840 of populations, a 6-17X increase compared to conventional 13-marker flow cytometry panels.

However, many immunotherapy developers are worried about the cost and need of measuring the extra populations. Drug developers sometimes say, “I just need to measure TBNK by flow first. If the drug shows activity in the TBNK populations, then, and only then, would I care about the other populations.”

The TokuFocus is designed with this drug developer in mind. You can start with a TBNK panel subset, covering 10 markers at $1,000 per specimen. You can then upgrade to the full panel at any time within a year for an additional $900 per specimen. In short, you get the option to see the rest of the immune tree when you want (and only when you want).

What problem TokuFocus solves:

• Drug developers who need a quick analysis of TBNK populations but who don’t want to lose the option of detailed immune population analysis. These developers want to focus on TBNK populations first and analyze the rest of the immune tree after achieving successful readings.

How it works:

• Each sample will be run on a full, 25-marker or 41-marker panel.
• For $1,000 per specimen, customers can access the data for a basic 10-marker TBNK panel. 
• With the software-based upgrade, customers can unlock access to the data for the full panel for $900 per specimen, without having to run additional samples. 
• Required minimum specimens by cohort
  • Mass Cytometry: 20 specimen
  • Spectral Flow Cytometry: 50 specimen

What do I get after I upgrade?

• Gated Data
• FCS and GatingML Files
• Dashboard: Immune Cell Composition, Box and Time Series Plots
• 2 Consulting Hours

Key Features: 

With the 10-marker panel, customers can access features included in our core analysis tier. This includes data tables, sample and gating QC, and manually gated statistical analysis. Raw data files, like FCS and GatingML are only available after unlocking the remaining channels. These features will be available on Teiko’s dashboard, at app.teiko.bio. 

Within a year, customers can upgrade to unlock the data for the full panel. After upgrading, the analyzed data will be available within the dashboard, assuming a 50 specimen order.

FAQ:

• Can I do this on a custom panel?
  • Not yet. This is built for our off-the-shelf panel.
• Can I pick the subset?
  • Not yet. Here are the markers included in our basic TBNK panels:

• What if I want to run multiple cohorts?
  • We can support this, however spectral flow requires 50 specimens per cohort, and mass cytometry requires 20 specimens per cohort.
• Is the full gating tree available?
  • Yes, you will get the full gating tree on the dashboard. You’ll see the unavailable populations greyed out.
• Can I cherry pick which samples to upgrade? That is, if I send you 50 samples, can I upgrade 30?
  • Not yet, you cannot select which samples to upgrade. That is, the upgrades are “all or nothing.”
• How do you do unsupervised analysis?
  • We don’t do unsupervised analysis on the focused panel. If you’re interested in that, you have to unlock the remainder of the panel. Once you unlock the panel, you have the option to upgrade for an additional fee.

Normalization Baseline Selection Feature For Data Export

We’ve added a new feature in the data export tab, enabling you to select a normalization baseline for your data. Now, you can choose any time point as the baseline, and the data will be normalized accordingly. The default option is set to “no normalization,” allowing for complete flexibility based on your analysis needs.

Enhanced Navigation with New Collapsible Filter

We’ve upgraded our filtering interface with a new collapsible design. This accordion-style filter allows for easier navigation and quicker access to the metadata you need, streamlining the process of selecting filters and viewing data.

The previous layout required extensive scrolling to reach different filter options. With the collapsible filter, all options are now neatly organized and accessible, enabling you to focus on analysis without distractions.

Append: add new samples to your web app as the samples get processed

Customers who send us samples in rolling cohorts can see their samples updated as new samples come in. Imagine you have a 250 specimen trial. 100 specimens arrive in Cohort 1, and 150 specimens arrive in Cohort 2.

Previously, the addition of new samples led to a short period of downtime for the user’s web app as the new samples were added to the project. Now, samples are added to the web app without any downtime, and all statistics are recomputed for all samples. This update provides a more seamless experience for the customer.

“No samples left behind”: Missing a baseline sample, no sweat!

Previously, if a sample was missing in a certain group comparison, that group comparison would not yield statistical results. For example, assume you have a set of five patients.

If you want to compare B cells across two on-treatment timepoints (i.e. C1D2 and C1D15) normalized to the baseline, but one subject is missing the baseline sample, previously our statistical testing implementation would skip the comparison due to the incomplete data.

Let’s see this in action. If Patient two in the table below were missing a baseline sample, we wouldn’t be able to calculate statistical results. Now, by dynamically constructing the statistical test to remove the one patient with no baseline sample, we are able to calculate all statistical tests for the remaining four samples.

Now, say a subject is missing any timepoint (as in the table below). And assume the goal is to calculate paired statistics. Previously, if you tried comparing the means of these two groups at two different timepoints, no statistics would be shown. Our algorithm was strict and simply did not perform the comparison. Now, we filter out the subject with the missing sample and show statistics for the remaining patients.