2011 - Athens - Greece

PAGE 2011: Study design
Camille Vong

Optimal Design of Anticancer Regimens

Camille Vong, Lena E. Friberg, Mats O. Karlsson and Andrew C. Hooker

Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

Objectives: Anticancer regimens are often a delicate compromise between dose intensity and acceptable toxicity, for example neutropenia. The aim of the present study was to develop methods in an optimal design approach to select the optimal dosing and sampling strategies within clinical restrictions, based on predictions of nadir neutrophil counts.

Methods: A semi-physiological PK/PD model for docetaxel's haematological toxicity [1, 2] was used to determine the population mean value of nadir concentration and time of nadir. An optimization on both time and size of dosing was performed in PopED v.2.11 [3].The optimizations maximized the expected nadir value given a set of clinical constraints using a penalty function. Constraints investigated included 1) 5 doses of  20 mg/m2 given within 21 days (optimization on dose time) and 2) 5 doses fixed to be given on day 1 then every 5 days with a total dose of at least 100 mg/m2 (optimization on dose size). Sampling schedules were also optimized to allow for model identification of the nadir value using a C-optimal criterion [4]  and by using a Sample Reuse Simulation approach [5].

Results: Suitable dosing schedules were found for the different scenarios specified above. For scenario (1) optimized dosing times were found to be 1, 5, 11, 16 and 21 days, resulting in a nadir value of 2.0 x 109/L. For scenario (2) optimized doses were found to be 27.0, 19.5, 21.8, 10.4, and 33.5 mg/m2, resulting in a nadir value of 1.9 x 109/L. Nadir was estimated more precisely with the optimized time points compared to a typical D-optimal design.

Conclusions: Optimal design methodology can be applied for toxicity monitoring within clinical constraints in oncology studies. Future optimal dosing designs will incorporate both efficacy and toxicity and incorporate between subject variability.

[1] Friberg LE, Henningsson A, Maas H, Nguyen L, Karlsson MO. Model of chemotherapy-induced myelosuppression with parameter consistency across drugs. J Clin Oncol. 2002 Dec 15;20(24):4713-21.
[2] Friberg LE, Karlsson MO. Mechanistic models for myelosuppression. Invest New Drugs. 2003 May;21(2):183-94.
[3] Nyberg J, Ueckert S, Karlsson MO, Hooker A. PopED v. 2.11. 2010. (http://poped.sourceforge.net/)
[4] Atkinson A, Donev AN. Optimum Experimental Designs. Oxford: Clarendon Press; 1992.
[5] Wang JX. Sample reuse simulation in optimal design for T-max in pharmacokinetic experiments. J Roy Stat Soc C-App. 2002;51:59-67.

Reference: PAGE 20 (2011) Abstr 2256 [www.page-meeting.org/?abstract=2256]
Poster: Study design
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