A computer-implemented method is provided for monitoring and / or controlling a chemical and / or
biological process. The method comprises: obtaining (S10) a
time series dataset comprising observations, each one of the observations being collected with respect to the chemical and / or
biological process at a particular time point, wherein each one of the observations includes values of observed parameters obtained with a spectroscopic method at the particular time point and a value of an
analyte parameter obtained with a
reference measurement method at the particular time point; obtaining (S20) a prediction model for estimating a predicted value of the
analyte parameter in the chemical and / or
biological process, the prediction model being trained using at least part of the
time series dataset; validating (S30) the prediction model by assessing an ability of the prediction model to predict a difference between an actual value of the
analyte parameter which would be obtained with the
reference measurement method at a given time point and an expected value of the analyte parameter at the given time point, using a set of observations that is not included in the at least part of the
time series dataset used for training the prediction model; determining (S40) whether the prediction model is valid or invalid based on a result of the validating; and monitoring and / or controlling (S50) the chemical and / or biological process when the prediction model is determined to be valid.