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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.

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Validated2026-03-16
CitableMethods and citation included

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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%

When to use

  • 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

Do not use for

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

Use enough replicates per dilution

Four wells per dilution is the practical minimum; 6–8 wells substantially narrow the confidence interval. With only 2–3 wells, the proportional distance calculation is coarse and small pipetting errors dominate the result.

Read endpoints consistently

Cytopathic effect (CPE) scoring is subjective. Define CPE criteria before reading plates and have the same person read all plates in a study. Ambiguous wells at borderline dilutions can shift the TCID50 by a full log.

Bracket the endpoint with your dilution range

Spearman-Kärber requires at least one dilution at 100% positive and one at 0% positive. If your highest dilution still shows 100% CPE, extend the series — otherwise only Reed-Muench is available, and even that result is an extrapolation.

Check for monotonicity

Infection rates should decrease monotonically with increasing dilution. If a higher dilution shows more positives than a lower one, investigate: well contamination, cross-talk between wells, or a transcription error. Non-monotonic data produces unreliable titer estimates.

PFU conversion is an approximation

The TCID50-to-PFU conversion (PFU \approx 0.693 ×\times TCID50) assumes one infectious unit per cytopathic event and Poisson-distributed infection. This holds well for lytic viruses but can overestimate PFU for viruses that spread cell-to-cell or cause bystander CPE.

1

Method

Implements Reed-Muench cumulative method, Spearman-Kärber proportional distance, and Kärber improved estimator with 95% confidence intervals via the Hamilton method. TCID50-to-PFU conversion uses the Poisson relationship: PFU = TCID50 ×\times ln(2).

2

Validated

Last validated 2026-03-16. Calculations are designed for planning and documentation support; verify procurement decisions against manufacturer specifications or institutional SOPs.

3

How to cite

How to Cite

ConductScience TCID50 Calculator (v1.0). ConductScience, Inc. 2026. Available at: https://conductscience.com/tools/tcid50-calculator

Reed LJ, Muench H. A simple method of estimating fifty per cent endpoints. Am J Epidemiol. 1938;27(3):493-497.

Spearman C. The method of "right and wrong cases" (constant stimuli) without Gauss's formulae. Br J Psychol. 1908;2:227-242.

Kärber G. Beitrag zur kollektiven Behandlung pharmakologischer Reihenversuche. Arch Exp Pathol Pharmakol. 1931;162:480-483.

Lei C, et al. On the Calculation of TCID50 for Quantitation of Virus Infectivity. Virologica Sinica. 2021;36:141-144.

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.

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