TABLE 2.

Examples of models that have been validated for cross-species or crosspopulation predictability of TPs’ PK

Model Reference	Model Characteristics	Model Description/Application
Dong et al., 2011	Two-compartment model, allometric scaling	Prediction of linear plasma PK of mAbs following subcutaneous and subcutaneous administration in humans based on monkey PK data
Zhao et al., 2015	mPBPK, FcRn binding not included	Prediction of linear plasma PK of mAbs following subcutaneous administration in mice, rats, monkeys, and humans
Chen and Balthasar, 2012 Glassman et al., 2015 Glassman and Balthasar, 2016b	PBPK, TMDD (equilibrium binding), catenary endosomal model	Prediction of nonlinear plasma PK of mAbs in the presence of therapeutic targets across doses in mice, monkeys, and humans
Offman and Edginton, 2015 Offman et al., 2016	PBPK, one-pore	Prediction of subcutaneous PK of a pegylated peptide across dose levels in humans based on PK data following subcutaneous and subcutaneous administration in monkeys and one dose level of subcutaneous administration in humans
Chang et al., 2019	PBPK, kinetic FcRn binding, brain distribution submodel	Prediction of nontargeting mAb disposition in whole brain and CSF in mice, rats, monkeys, and humans
Shah and Betts, 2012 Chang et al., 2021a	PBPK, kinetic FcRn binding, age-dependent physiologic parameter values	Prediction of plasma PK of mAbs following intravenous administration in mice, rats, monkeys, human adults, and pediatric patients
Pan et al., 2020	PBPK, TMDD, two-pore, semimechanistic or first-order absorption model, age-dependent physiologic parameter values	Prediction of plasma PK of different-size TPs following intravenous or subcutaneous administration in full-term neonates, infants, children, adolescents, and adults
Khot et al., 2017	PBPK, tumor disposition model, allometric scaling	Prediction of plasma PK of different analytes of an ADC based on rat PK data