Further developments of SwarmCG may also target other classes of molecules, such as DNA, peptides and proteins, which are well suited to the application of automatic parametrization approaches leveraging the cross-sampling of building blocks. Although the computational burden may seem important, such approaches scale well on HPC resources (n.b. in this study we only used 64 CPU cores). Their current limits remain defined mostly by our ability to assemble rich training sets, including reliable experimental data to be used in concert with relevant CG representations, sufficiently descriptive of the degrees of freedom of the molecular systems of interest.