Linear regression clearly seems not to fit the datapoints well due to non-linear pH response, but it was conducted as a reference. It requires a high number of iterations for systems containing many polyprotic components, e.g., citrate, see Figure . Overall, most of the systems could be adjusted within 3-4 iterations using three datapoints to initialize the optimization, thus giving a total of 6-7 required steps. On average, RF required 3.4 ± 0.3 iterations, ANN required 5.6 ± 1.0 iterations and GP required 3.1 ± 0.6. Here and in the following the reported values refer to the mean and the error of the mean value of 10 single iterations, see SI Eqn. S2. Our analysis shows that using the GP model gives the best results