Journal of Pharmacokinetics and Pharmacodynamics

, Volume 39, Issue 5, pp 577–590 | Cite as

Intracellular-signaling tumor-regression modeling of the pro-apoptotic receptor agonists dulanermin and conatumumab

  • Brittany P. Kay
  • Cheng-Pang Hsu
  • Jian-Feng Lu
  • Yu-Nien Sun
  • Shuang Bai
  • Yan Xin
  • David Z. D’Argenio
Original Paper


Dulanermin (rhApo2L/TRAIL) and conatumumab bind to transmembrane death receptors and trigger the extrinsic cellular apoptotic pathway through a caspase-signaling cascade resulting in cell death. Tumor size time series data from rodent tumor xenograft (COLO205) studies following administration of either of these two pro-apoptotic receptor agonists (PARAs) were combined to develop a intracellular-signaling tumor-regression model that includes two levels of signaling: upstream signals unique to each compound (representing initiator caspases), and a common downstream apoptosis signal (representing executioner caspases) shared by the two agents. Pharmacokinetic (PK) models for each drug were developed based on plasma concentration data following intravenous and/or intraperitoneal administration of the compounds and were used in the subsequent intracellular-signaling tumor-regression modeling. A model relating the PK of the two PARAs to their respective and common downstream signals, and to the resulting tumor burden was developed using mouse xenograft tumor size measurements from 448 experiments that included a wide range of dose sizes and dosing schedules. Incorporation of a pro-survival signal—consistent with the hypothesis that PARAs may also result in the upregulation of pro-survival factors that can lead to a reduction in effectiveness of PARAs with treatment—resulted in improved predictions of tumor volume data, especially for data from the long-term dosing experiments.


Extrinsic apoptotic pathway Tumor-regression modeling Death receptor activation of NF-κB Pro-apoptotic receptor agonists Dulanermin Conatumumab 



We gratefully acknowledge the helpful comments provided by Liviawati Sutjandra, an employee of Amgen Inc. We would also like to thank Michelle Zakson, an employee of Amgen Inc, for providing editorial and formatting assistance with the manuscript. This work was supported by Amgen Inc., as well as by grant NIH/NIBIB P41-EB001978 (DZD).

Supplementary material

10928_2012_9269_MOESM1_ESM.docx (1.4 mb)
Supplementary material 1 (DOCX 1386 kb)


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Brittany P. Kay
    • 1
  • Cheng-Pang Hsu
    • 2
  • Jian-Feng Lu
    • 2
  • Yu-Nien Sun
    • 2
  • Shuang Bai
    • 3
  • Yan Xin
    • 3
  • David Z. D’Argenio
    • 1
  1. 1.Department of Biomedical EngineeringUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Quantitative PharmacologyPKDM, AmgenThousand OaksUSA
  3. 3.Clinical PharmacologyGenentech IncSouth San FranciscoUSA

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