Investigating the PK/PD relationship of a new pro-apoptotic drug through tumor growth inhibition modelling in NUDE rats
Adrien Tessier, Sylvain Fouliard and Marylore Chenel
Clinical Pharmacokinetics and Pharmacometrics division, Servier, France
Objectives: Apoptosis is the process of programmed cell death that tumor cells escape. Drug S is a pro-apoptotic compound in preclinical development. Using data from a tumor growth inhibition study in rats, the relationship between drug concentrations and efficacy was estimated through PK/PD modelling in order to determine active concentrations.
Methods: Drug S was administered once to 18 RS4;11 xenografted NUDE rats at doses 30 or 75 mg/kg in 1h intravenous (IV) infusion or 30 mg/kg in IV bolus (6 rats per group + 6 rats in the control group). Two PK samples were performed per rat to measure total plasma concentrations. Tumor volumes were measured for all individuals until 52 days after administration.
A population PK/PD modelling analysis was performed using MONOLIX 4.3.3 and SAEM algorithm to estimate active drug S concentrations to reduce the tumor volume.
Results: A one-compartment model with Michaelis-Menten elimination best described the drug plasma concentrations. The tumor growth was described through the Simeoni model [1] with a sigmoid relationship between drug plasma concentrations and apoptosis triggering. The drug effect was interpreted as the transformation rate (in time-1) of tumor cells from a proliferating to a non-proliferating state. The typical maximum transformation rate (Emax) and plasma concentration leading to 90% of the maximum rate (EC90) were estimated. Emax was estimated at 0.87 h-1, indicating quick triggering of apoptosis. The drug effect showed a high sigmoidicity with a Hill coefficient estimated at 7.09.
Using the same approach as proposed by Simeoni [1] the threshold concentration (leading to tumor stasis) was computed and was approximately 2.5 fold lower than EC90, corresponding to a low activity on the concentrations - drug effect relationship (approximately 1.3% of the maximal effect).
Conclusions: Drug S showed an activity to inhibit tumor growth in rats with a strong tumor regression at the highest dose. A PK/PD modelling approach has allowed to described the steep relationship between drug concentrations and tumor regression and to estimate a concentration EC90 corresponding to a high drug activity. The threshold concentration usually estimated through modelling in such analyses corresponds to the lowest active concentrations. For translation to human, it is more relevant to predict the active dose using the estimated EC90, instead of the much lower threshold concentration.
References:
[1] Simeoni M, Magni P, Cammia C, De Nicolao G, Croci V, Pesenti E, Germani M, Poggesi I and Rocchetti M. Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administrations of anticancer agents. Cancer Res (2004) 64: 1094-1101.