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. 2013 Jan;71(1):133-43.
doi: 10.1007/s00280-012-1988-6. Epub 2012 Oct 7.

PK-PD modeling of combination efficacy effect from administration of the MEK inhibitor GDC-0973 and PI3K inhibitor GDC-0941 in A2058 xenografts

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PK-PD modeling of combination efficacy effect from administration of the MEK inhibitor GDC-0973 and PI3K inhibitor GDC-0941 in A2058 xenografts

Edna F Choo et al. Cancer Chemother Pharmacol. 2013 Jan.

Abstract

Purpose: Mutations and activations of the MEK and PI3K pathways are associated with the development of many cancers. GDC-0973 and GDC-0941 are inhibitors of MEK and PI3K, respectively, currently being evaluated clinically in combination as anti-cancer treatment. The objective of these studies was to characterize the relationship between the plasma concentrations of GDC-0973 and GDC-0941 administered in combination and efficacy in A2058 melanoma xenograft.

Methods: GDC-0973 and GDC-0941 were administered to A2058 tumor-bearing mice daily (QD) or every third day (Q3D) either as single agents or in combination. A semi-mechanistic population anti-cancer model was developed to simultaneously describe the tumor growth following QD/Q3D single-agent and QD combination treatments. The interaction terms ψ included in the model were used to assess whether the combination was additive. Using this model, data from the Q3D combination regimen were simulated and compared with the observed tumor volumes.

Results: The model consisting of saturable tumor growth provided the best fit of the data. The estimates for ψ were not significantly different from 1, suggesting an additive effect of GDC-0973 and GDC-0941 on tumor growth inhibition. The population rate constants associated with tumor growth inhibition for GDC-0973 and GDC-0941 were 0.00102 and 0000651 μM(-1) h(-1), respectively. Using the model based on single-agent and QD combination efficacy data, simulations adequately described the tumor growth from the Q3D combination regimen.

Conclusions: These findings suggest that, based on minimal data, it is possible to predict the effects of various combinations preclinically and also assess the potential clinical efficacy of combinations using human pharmacokinetic inputs.

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