No matter the underlying philosophy, both traditional and PCM QSPR models can be obtained by combining various algorithms and methodologies, which often need to be benchmarked against one another in a systematic and comprehensive manner. While there is still an ongoing debate on whether and under what conditions a meaningful comparison of QSPR methodologies is possible , benchmarking and systematic comparison have become an integral part of the QSPR field. Whether it is the comparison of new algorithms , molecular representations , model development strategies , model validation , the nature of data , or to provide usage guidelines , one common denominator of such studies is that they base their conclusions on a systematic comparison using a standardized subset of data.