TY - JOUR T1 - Towards a combinatorial approach for the prediction of immunoglobulin G half-life and clearance JF - Drug Metabolism and Disposition JO - Drug Metab Dispos DO - 10.1124/dmd.118.081893 SP - dmd.118.081893 AU - Dennis R. Goulet AU - Michael J. Watson AU - Susan H. Tam AU - Adam Zwolak AU - Mark L. Chiu AU - William M. Atkins AU - Abhinav Nath Y1 - 2018/01/01 UR - http://dmd.aspetjournals.org/content/early/2018/09/19/dmd.118.081893.abstract N2 - The serum half-life and clearance of therapeutic monoclonal antibodies (mAbs) are critical factors that impact their efficacy and optimal dosing regimen. The pH-dependent binding of a mAb to the neonatal Fc receptor (FcRn) has long been recognized as an important determinant of its pharmacokinetics. However, FcRn affinity alone is not a reliable predictor of mAb half-life, suggesting that other biological or biophysical mechanisms must be accounted for. mAb thermal stability, which reflects its unfolding and aggregation propensities, may also relate to its pharmacokinetic properties. However, no rigorous statistical regression methods have been used to identify combinations of physical parameters that best predict biological properties. In this work, a panel of eight mAbs with published human pharmacokinetic data was selected for biophysical analyses of FcRn binding and thermal stability. Biolayer interferometry was used to characterize FcRn/mAb binding at acidic and neutral pH, while differential scanning calorimetry was used to determine thermodynamic unfolding parameters. Individual binding or stability parameters were generally weakly correlated with half-life and clearance values. Least absolute shrinkage and selection operator (LASSO) regression was used to identify the combination of two parameters with the best correlation to half-life and clearance as being the FcRn binding response at pH 7.0 and the change in heat capacity, ΔCP. Leave-one-out subsampling yielded a root-mean-square difference between observed and predicted half-life of just 2.7 days (16%). Thus, incorporation of multiple biophysical parameters into a cohesive model may facilitate early-stage prediction of in vivo half-life and clearance based on simple in vitro experiments. ER -