Teiko

???? Teiko is excited to release Yozakura, our solution for dynamic, top-level population selection within our web app. ???? When viewing immune composition boxplots or stacked bar charts of high-dimensional cytometry data, users can now display cell types as fractions of their chosen top-level population: T cells, B cells, monocytes, etc. Further, they can hover over individual samples to display the cell counts for each cell type and its top-level population. Before this release, users could only view cell types as a proportion of non-granulocytes. With Yozakura, users now have the flexibility to expand the scope of their data exploration in high-dimensional cytometry. The feature is now live on our demo web app - available at app.teiko.bio - go to the site to check it out or watch below for a quick overview. Yozakura | 夜桜 | Night Cherry Blossom ????

CyCombine for Dummies is live! Check it out now: https://lnkd.in/eMS3MwQV

If you enjoyed last week’s video, join us tomorrow for a webinar where we’ll break down CyCombine, a popular tool for batch normalizing high-dimensional cytometry data. CyCombine normalizes batched cytometry data by clustering cells with similar marker expression levels, allowing you to compare results between batches. Tune in for a review of: - How normalization removes technical noise.? - How self-organizing maps structure cytometry data into clusters. - How the COMBAT algorithm is implemented in CyCombine. We’ll cover the math behind the process so you don’t have to do the deep dive yourself. Check it out this Friday, 11/22, premiering at 4 PM PT. Subscribe here: youtube.com/@teikobio

Our team has been working hard to release updates to our web app over the past two months! Here’s what we’ve churned out: * Flexible baseline:?Choose any time point as the baseline for determining changes in cell population or subset frequencies; have access to these modified statistical comparisons with the click of a button. * Collapsible filtering:?Our filtering tabs have collapsible filters, allowing you to quickly navigate to the category you’re looking for. * Appending batches:?Data is added to the web app on a rolling basis as batches are processed. Get access to your data with less downtime. * Group comparisons with missing samples:?Subjects with missing samples are excluded from group comparisons, allowing you to compare the remaining ones. All of these?updates are live, so head to app.teiko.bio?to try them out with our demo dataset. For the full update, check out our announcement here:?https://lnkd.in/g8_3v4rd

Get ready ACR! Teiko is working on a 40+ marker, off-the-shelf, autoimmune cytometry panel for clinical trials. We want to hear directly from immunotherapy developers… what markers and cell types are you looking to profile? Our CEO + Cofounder, Ramji Srinivasan, and our VP of Business Development, Justin Jarrell, PhD, will be attending the American College of Rheumatology's Annual Convergence this weekend. They’d love to meet and hear more about your expert feedback. Teiko makes cytometry simple for drug developers. Our high-dimensional cytometry services are able to profile up to 840+ immune cell populations and subsets per PBMC or whole blood sample. We currently work with over nine active phase I and II clinical trials, helping them uncover biomarkers of safety and response with cytometry. Want to hear more? Book a meeting below! Book a Meeting: https://lnkd.in/eXrs7q8C #ACR2024 #Autoimmune #Cytometry #Immuneprofiling

Worried that having multiple batches of patient samples will inject technical variance into your cytometry dataset? This Friday’s YouTube video will highlight the value of using batch normalization in cytometry to reduce technical noise—also known as batch effects—that can arise from operator handling differences, machine-to-machine variability, or site-to-site variability.? These challenges are especially common in extended clinical trials, where patient samples arrive at lab sites on a rolling basis.? We’ll also give a light introduction to how common normalization algorithms, such as CytoNorm or CyCombine, normalize the cytometry datasets. How can batch normalization uncover the true biological changes in your cytometry dataset? Tune in this Friday at 8:30 AM PT to find out. Catch it here: https://lnkd.in/eg_Tmweh

In case you missed our posters at SITC, we’re bringing our presentations to you! Head to YouTube to watch our poster tours from this weekend. On day one, Kristina Magee presented results from our TokuKit on our spectral flow panel for fixed, whole blood. Notably, we found the following: - A strong correlation in cell population frequencies, (R = 0.97), between fixed and live samples. - Assay reproducibility for intra- and inter-run precision tests with coefficients of variation of 4.76% and 6.89%, respectively. - All markers achieved <1% positive signal in fluorescence-minus-multiple tests. Watch here: https://lnkd.in/eVj29Wkt On day two, Justin Jarrell presented the optimization for our mass cytometry panel. Notably, we found the following: - A strong correlation in cell population frequencies, (R > 0.99), between fixed and live samples. - Whole blood fixed with TokuKit is stable for 24 months, compared to three days for fresh. Watch here: https://lnkd.in/en4QsaGe The TokuKit solves the drug developer’s problem: missing granulocyte data with PBMCs or no data with fresh blood (owing to missed shipment deadlines).

Day two of #SITC2024 is here! Come visit Dr. Justin Jarrell’s poster on our optimization of the TokuKit - a fixed, whole blood kit - for our mass cytometry panel. See you at poster # 58!

Teiko is here at #SITC2024 booth # 441. Come chat with us to learn more about our high-dimensional cytometry services for your next clinical trial!

Day one of SITC is kicking off! Come visit Dr. Kristina Magee’s poster on our optimization of the TokuKit - a fixed, whole blood kit - for our 25-marker spectral flow panel. See you at poster #57!