TCID50 Calculator

Calculate viral titer using Reed-Muench, Spearman-Kärber, and Improved Kärber methods. Step-by-step audit trail with 95% confidence intervals. Data never leaves your browser.

3 Calculation MethodsStep-by-Step AuditConfidence Intervals

Try it out

Load example TCID50 data to see the full workflow

Assay Settings

Dilution Data

Paste from Excel: positive ⇥ total
DilutionPositive WellsTotal Wells% Positive
10-10.0%
10-20.0%
10-30.0%
10-40.0%
10-50.0%
10-60.0%
10-70.0%
10-80.0%
  • Determine viral titer from endpoint dilution assays
  • Compare Reed-Muench, Spearman-Kärber, and Improved Kärber methods
  • Convert TCID50 to PFU equivalents
  • Generate 95% confidence intervals for titer estimates
  • Document viral titer with publication-ready audit trail

Don't use for

  • Plaque assay data (report as PFU directly)
  • qPCR viral load (genome copies, not infectious units)
  • Hemagglutination assays (different endpoint)

What Is TCID50 and Why Does It Matter?

TCID50 (Tissue Culture Infectious Dose 50%) is the gold standard metric for quantifying viral infectivity in cell culture. It represents the dilution of a virus stock at which 50% of inoculated cell culture wells show cytopathic effect (CPE).

Unlike plaque assays (which measure PFU), TCID50 assays work for viruses that do not form distinct plaques — including many respiratory viruses, retroviruses, and some enteroviruses. This makes TCID50 the preferred method across virology, vaccinology, and gene therapy.

The TCID50 assay is simple to perform but surprisingly error-prone to calculate. Common errors include incorrect cumulative counting direction, using the wrong interpolation formula, and failing to account for non-standard dilution factors. This calculator eliminates these errors by showing every intermediate step.

How the Methods Work

This calculator implements three established methods for TCID50 estimation:

Reed-Muench (1938) builds a cumulative table of positive and negative observations across all dilutions, then uses linear interpolation to find the exact point where the cumulative positive rate crosses 50%. It is the most widely cited method and works even when the data does not include a complete endpoint (100% to 0% transition).
Spearman-Kärber is a distribution-free estimator that computes the log-mean of the infectivity distribution directly from the proportion of positive wells at each dilution. It requires complete endpoints (at least one dilution at 100% and one at 0%) but does not require interpolation.
Improved Kärber (Lei et al., 2021) extends Spearman-Kärber with a variance estimate, enabling 95% confidence intervals. This is particularly valuable for comparing titers across experiments or for regulatory submissions that require uncertainty quantification.
All three methods are deterministic — the same inputs always produce the same outputs. This is the foundation of reproducibility.

Frequently Asked Questions