Multiparametric optimization

Our Medicinal Chemistry team is highly experienced in the design of IP-free drug-like compounds considering, from the beginning, the whole set of properties needed to achieve the desired candidate profile, using a Multiparametric Optimization paradigm. Working within the molecular descriptors that conform the highest probability space, we achieve compliance with the relevant tests that predict good absorption, distribution, metabolism and excretion (ADME) in humans.
A profound knowledge in structure-activity relationships (SAR) and structure-property relationships (SPR) combined with proprietary SAR/SPR visualization tools help in fast iteration and project progression to allow rapid identification of suitable compounds in each Drug Discovery phase to end up with adequate clinical candidates.

We consider from the beginning the whole set of calculated molecular descriptors (MW, HBD, HBA, CLogP/cLogD, pKa, PSA, RB, planarity measures; grey), which are then related to the experimentally obtained physicochemical measures (solubility, lipophilicity, ionization constants, without forgetting stability; lavender) that influence many of the ADMET properties (lavender arrows). Early correlation with experimental ADMET values (permeability, metabolic & renal clearance, off-target promiscuity, such as hERG inhibition, drug-drug interactions, via CYP inhibition; orange) allow to achieve the required in vivo pharmacokinetics (good absorption and bioavailability) and in vivo efficacy and safety profiles (magenta), that combined with the desired in vitro affinity for the primary target (green) provide drugs with adequate efficacy-safety ratios (blue).