In-Vitro NSCLC Tumor Growth Data with Drug and CAF Conditions

A dataset of 5.5 KB presents in-vitro data tracking drug-sensitive and drug-resistant non-small cell lung cancer cells under varying environmental conditions. The data, originally from Kaznatcheev et al., includes conditions with and without the drug Alectinib and cancer-associated fibroblasts. Hasti Garjani published the dataset on figshare in June 2026.

Use Cases

• Fitting and comparing mathematical growth models (logistic, Gompertz, von Bertalanffy) based on the described model family.
• Estimating inter-type competition coefficients in co-cultures based on the described methodology.
• Analyzing shifts in competition and drug efficacy parameters under different environmental conditions (CAFs, Alectinib) as described.
• Mechanistic interpretation of tumor cell interactions based on the described incorporation of density dependence and frequency-dependent competition.

Strengths

• Data is explicitly licensed under CC-BY-4.0 for open use.
• Dataset size is 5.5 KB, indicating a focused and likely manageable scope.
• The description provides a detailed methodological context for model fitting and biological interpretation.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (5.5 KB), indicating limited scope and likely a small number of observations or summary statistics.

Provenance

Source

figshare, authored by Hasti Garjani.

Collection Method

In-vitro data originally presented by Kaznatcheev et al., used to fit two-population models of tumor growth.

Freshness

Last updated 2026-06-01 18:04:19; freshness should be verified.