have you looked at Phoenix WinNonlin https://support.certara.com/forums/topic/1041-qa-from-lesson-13-modeling-tumor-growthkill/

The modified Gompertz growth model is used to model growth that exhibits an initial exponential phase followed by a decelerating growth phase. The model has the form:

y = A * exp[-exp(B-C*t)]

where:

y is the dependent variable (e.g. population, weight)

A is the asymptotic maximum value that y approaches

B and C are parameters that determine the shape of the curve

t is the independent variable (usually time)

To model data using this model, you need to:

Collect data points (y, t) of the growth process you want to model.

Estimate the parameters A, B and C by fitting the model to the data using a nonlinear regression or curve fitting algorithm. There are various optimization algorithms you can use, like least squares or gradient descent.

Evaluate how well the model fits the data by calculating metrics like the coefficient of determination (R2). The closer R2 is to 1, the better the fit.

Plot the data points and model curve to visually inspect the fit.

Use the fitted model to predict y values for new t values of interest. Calculate confidence intervals to quantify uncertainty in the predictions.

The modified Gompertz model is widely used for modeling biological growth processes like plant and animal growth, tumor growth, yeast fermentation, etc. The key is choosing an appropriate optimization algorithm and hyperparameters to get a good fit of the model to your specific dataset.

thanks a lot. do you have a preferred software for fitting/modeling?