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Prediction of human pharmacokinetics (PK) based on preclinical information for antibody–drug conjugates (ADCs) provide important insight into first‐in‐human (FIH) study design. This retrospective analysis was conducted to identify an appropriate scaling method to predict human PK for ADCs from animal PK data in the linear range. Different methods for projecting human clearance (CL) from animal PK data for 11 ADCs exhibiting linear PK over the tested dose ranges were examined: multiple species allometric scaling (CL vs. body weight), allometric scaling with correction factors, allometric scaling based on rule of exponent, and scaling from only cynomolgus monkey PK data. Two analytes of interest for ADCs, namely total antibody and conjugate (measured as conjugated drug or conjugated antibody), were assessed. Percentage prediction errors (PEs) and residual sum of squares (RSS) were compared across methods. Human CL was best estimated using cynomolgus monkey PK data alone and an allometric scaling exponent of 1.0 for CL. This was consistently observed for both conjugate and total antibody analytes. Other scaling methods either underestimated or overestimated human CL, or produced larger average absolute PEs and RSS. Human concentration‐time profiles were also reasonably predicted from the cynomolgus monkey data using species‐invariant time method with a fixed exponent of 1.0 for CL and 1.0 for volume of distribution. In conclusion, results from this retrospective analysis of 11 ADCs indicate that allometric scaling of CL with an exponent of 1.0 using cynomolgus monkey PK data alone can successfully project human PK profiles of an ADC within linear range. [ABSTRACT FROM AUTHOR]

Peripheral neuropathy (PN) is a common long‐term debilitating toxicity of antimicrotubule agents. PN was the most frequent adverse event resulting in dose modifications and/or discontinuation of treatment for valine‐citrulline‐monomethylauristatin E antibody–drug conjugates (ADCs) developed at Genentech. A pooled time‐to‐event analysis across eight ADCs (~700 patients) was performed to evaluate the relationship between the ADC exposure and the risk for developing a clinically significant (grade ≥ 2) PN. In addition, the impact of demographic and pathophysiological risk factors on the risk for PN was explored. The time‐to‐event analysis suggested that the development of PN risk increased with ADC exposure, treatment duration, body weight, and previously reported PN. This model can be used to inform clinical strategies such as adaptations to dosing regimen and/or treatment duration as well as inform clinical eligibility to reduce the incidence of grade ≥ 2 PN. [ABSTRACT FROM AUTHOR]