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. 2019 Jun;8(6):415-427.
doi: 10.1002/psp4.12406. Epub 2019 Apr 25.

Time-Varying Clearance and Impact of Disease State on the Pharmacokinetics of Avelumab in Merkel Cell Carcinoma and Urothelial Carcinoma

Justin J Wilkins  1 , Brigitte Brockhaus  2 , Haiqing Dai  3 , Yulia Vugmeyster  3 , Joleen T White  3 , Satjit Brar  4 , Carlo L Bello  4 , Berend Neuteboom  3 , Janet R Wade  1 , Pascal Girard  5 , Akash Khandelwal  2
Affiliations

Time-Varying Clearance and Impact of Disease State on the Pharmacokinetics of Avelumab in Merkel Cell Carcinoma and Urothelial Carcinoma

Justin J Wilkins et al. CPT Pharmacometrics Syst Pharmacol. 2019 Jun.

Abstract

Avelumab, a human anti-programmed death ligand 1 immunoglobulin G1 antibody, has shown efficacy and manageable safety in multiple tumors. A two-compartment population pharmacokinetic model for avelumab incorporating intrinsic and extrinsic covariates and time-varying clearance (CL) was identified based on data from 1,827 patients across three clinical studies. Of 14 tumor types, a decrease in CL over time was more notable in metastatic Merkel cell carcinoma and squamous cell carcinoma of the head and neck, which had maximum decreases of 32.1% and 24.7%, respectively. The magnitude of reduction in CL was higher in responders than in nonresponders. Significant covariate effects of baseline weight, baseline albumin, and sex were identified on both CL and central distribution volume. Significant covariate effects of black/African American race, C-reactive protein, and immunogenicity were found on CL. None of the covariate or time-dependent effects were clinically important or warranted dose adjustment.

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Conflict of interest statement

J.J.W. and J.R.W. were employed as consultants by Merck Healthcare KGaA at the time the analysis was performed. B.B. and A.K. are employees of Merck Healthcare KGaA. H.D., Y.V., J.T.W., and B.N. are employees of EMD Serono, business of Merck Healthcare KGaA. P.G. is an employee of Merck Serono S.A., Lausanne, Switzerland, an affiliate of Merck Healthcare KGaA. S.B. and C.L.B. are employees of Pfizer Inc.

Figures

Figure 1
Figure 1
Forest plots illustrating the effects of covariates in the final reduced model. AST, aspartate transaminase; CL, clearance; CRP, C‐reactive protein; eGFR, estimated glomerular filtration rate; HAHA, human anti‐human antibody; Imax, maximal change in CL relative to baseline; MCC, Merkel cell carcinoma; SCCHN, squamous cell carcinoma of the head and neck; V1, central volume of distribution.
Figure 2
Figure 2
Visual predictive check for the final reduced model: (a) single cycle and (b) across the complete time course. CI, confidence interval; h, hour.
Figure 3
Figure 3
Change in clearance (CL) over time by tumor type predicted by the final reduced model. Lines are individual patients. ACC, adrenocortical carcinoma; CRC, colorectal cancer; CRPC, castration‐resistant prostate cancer; GC, gastric cancer; GEJC, gastroesophageal junction cancer; d, day; MCC, Merkel cell carcinoma; NSCLC, non‐small cell lung cancer; RCC, renal cell carcinoma; SCCHN, squamous cell carcinoma of the head and neck; UC, urothelial carcinoma.
Figure 4
Figure 4
Estimated clearance (CL) over time relative to baseline stratified by response and tumor. d, day; MCC, Merkel cell carcinoma; UC, urothelial carcinoma.
Figure 5
Figure 5
Estimated clearance (CL) at baseline and after 26 weeks of biweekly treatment, comparing mMCC and UC tumor types. h, hours; MCC, Merkel cell carcinoma; UC, urothelial carcinoma.
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