The concept of multiparameter optimization (MPO), in the context of medicinal chemistry, was used by Wager et al. . The MPO score was a scalar value calculated as a non-linear function of six fundamental physicochemical properties. This was an empirical approach and specific for the central nervous system drug property space. Since then, however, the method has been widely applied by medicinal chemists and in other therapeutic areas. Alternative approaches to address multi-objective optimization in drug design have been reported, where either the problem is transformed to a single objective by linear or non-linear weighting of the objectives, or a full or partial Pareto solution space is obtained; see a recent review by Nicolaou et al. . Yasonik recently suggested nondominated sorting and transfer learning to iteratively fine-tune a recurrent neural network, without a scoring function.