Based on these new conformer-aggregated similarity metrics, we conducted a comparative analysis involving five distinct runs, each allocated a budget of 1500 fitness calls, of both the GB-BI and GB-EPI algorithms for the USRCAT and Zernike-based rediscovery tasks of Troglitazone. To facilitate this evaluation, we repurposed the initial dataset of molecules, along with the struc- tural filters and ADMET requirements, originally employed in the GuacaMol rediscovery benchmarks. Similarly, both algorithms were initialised with the archive configuration previously used by GB-BI in the GuacaMol rediscovery benchmark. The archive thus encompasses 150 niches and is spanned along four physicochemical properties: molecular mass (ranging from 225 u. to 555 u.), lipophilicity (log P ranging from -0.4 to 5.6), TPSA (ranging from 0 Å 2 to 140 Å 2 ), and Wildman-Crippen molar refractivity (ranging between 40 and 130). For the surrogate fitness model, we choose to make use of the ECFP4 fingerprint as molecular representation and decided on the posterior mean as acquisition function.