I-34 Nick Holford

Evaluation of NONMEM and Monolix by Parametric Bootstrap

Nick Holford

University of Auckland

Objectives: To evaluate NONMEM and Monolix in terms of parameter estimation bias and uncertainty coverage bias using a parametric bootstrap procedure.

Methods: Default SAEM estimation options (NONMEM AUTO, Monolix algorithms options created when no algorithms file supplied as input) were used. All calculations were performed using the NeSI PAN cluster. Four problems of increasing difficulty were tested: warfarin pharmacokinetics, simple and complex tumour growth inhibition, viral load kinetics. Uncertainty bias was based on the bootstrap standard deviation relative to the standard error which described 95% coverage of the bootstrap distribution.

Results and Conclusions: Some problems were better described using FOCE while others were better described using SAEM (see Table 1 for tumour growth inhibition [1] example). Both methods had biased uncertainty relative to bootstrap coverage (Table 2). 

Table 1 Estimation Bias for Model Parameters

Tham TGI

NONMEM

NONMEM

Monolix

Method

FOCE

SAEM

SAEM

Option

INTER

AUTO

No algo

Parameter

TRUE

MDL

MDL

MDL

POP_SIZE0

6.39

1.1%

3.7%

10.8%

POP_TOVER

33.9

-37%

22%

230%

POP_AE50

6324

60%

1.7%

-76%

POP_TEQ

4.407

111%

24%

-34%

PPV_SIZE0

0.6

-7%

-6%

-33%

PPV_TOVER

0.420

-72%

38%

67%

PPV_AE50

1.200

-4%

-24%

20%

PPV_TEQ 

0.200

-64%

59%

324%

RUV_CV

0.199

-3.9%

-5%

58%

TRUE=Parameter used for simulation MDL=Model parameter bias

Table 2 Uncertainty Bias for Model Parameters

Tham TGI

NONMEM

NONMEM

NONMEM

Monolix

Method

FOCE

FOCE

SAEM

SAEM

Option

INTER

AUTO

No algo

Parameter

95 SE

AsymRSE

AsymRSE

AsymRSE

POP_SIZE0

7%

-3%

26%

-6%

POP_TOVER

65%

-16%

4%

-17%

POP_AE50

61%

45%

42%

125%

POP_TEQ

64%

-38%

10%

11%

PPV_SIZE0

10%

-10%

13%

42%

PPV_TOVER

105%

164%

289%

-41%

PPV_AE50

41%

-47%

140%

123%

PPV_TEQ

120%

14%

65%

-35%

RUV_CV

5%

30%

22%

22%

95SE= standard error which described 95% coverage of the bootstrap distribution

AsymRSE=bias of asymptotic relative standard error relative to 95SE

References:
[1] Tham LS, Wang L, Soo RA, Lee SC, Lee HS, Yong WP, et al. A pharmacodynamic model for the time course of tumor shrinkage by gemcitabine + carboplatin in non-small cell lung cancer patients. Clin Cancer Res. 2008;14(13):4213-8.

Reference: PAGE 23 () Abstr 3143 [www.page-meeting.org/?abstract=3143]

Poster: Methodology - Estimation Methods

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