Difference between Active learning and Optimal experimental design?

During my research in the active learning field, I found a similar concept that has the same idea that is the optimal experimental design (OED) for machine learning which is based on finding new data points to do experiments on in order to improve the performance of our model. This made me wonder if OED is a subfield from active learning or it is completely different. Any information will be useful and appreciated. Thank you.