The optimization protocol proposed in SwarmCG allows to obtain CG FF parameters for lipid models by simultaneously exploiting experimental data (top-down: area per lipid & Dʜʜ thickness) and AA MD simulations (bottom-up: bond & angle distributions), respectively informing on the supra-molecular structure of the systems and on their sub-molecular dynamics (Fig. ). CG models are tested iteratively in a set of simulations of small patches of homogenous lamellar bilayers, used to measure the discrepancies observed between the simulated and reference data (128 lipids and 200 ns of equilibrium CG MD simulation each). The software allows to modulate selected parameters of the CG FF, that are iteratively optimized within pre-defined boundaries using FST-PSO (Fuzzy Self-Tuning Particle Swarm Optimization, one of the most efficient PSO variant to date ) for minimizing a loss function designed to improve FF accuracy.