A novel semi‐mechanistic tumor growth fraction model for translation of preclinical efficacy of anti‐glypican 3 antibody drug conjugate to human

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Abstract
Growing fraction (GF) of tumor has been reported as one of the predictive markers of efficacy of chemotherapeutics. Therefore, we have developed a semi‐mechanistic model that describes tumor growth on the basis of cell cycle, allowing us to incorporate GF of the tumor in pharmacokinetic/Pharmacodynamic (PK/PD) modelling. Efficacy data of anti‐glypican 3 (GPC3) antibody drug conjugate (ADC) in hepatocellular carcinoma patient derived xenograft (PDX) model was used for evaluation of this proposed model. Our model was able to describe kinetics of growth inhibition of HCC PDX models following treatment with anti‐GPC3 ADC remarkably well. The estimated tumurostatic concentrations were used in tandem with human pharmacokinetics translated from cynomolgus monkey for prediction of efficacious dose. The projected efficacious human dose of anti‐GPC3 ADC ranged between 0.20 to 0.63 mg/kg for Q3W dosing regimen, with a median dose of 0.50 mg/kg. This publication is the first step in evaluating applicability of GF in PK/PD modelling of ADCs. Authors are hopeful that incorporation of GF will result in an improved translation of preclinical efficacy of ADCs to clinical settings and thereby better prediction of efficacious human dose.

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