Álvaro Janda1, Zinnia Para-Guillén1, Julian Gorrochategui2, Joan Ballesteros2 , and Iñaki F. Trocóniz1
1, Department of Pharmacy and Pharmaceutical Technology; School of Pharmacy; University of Navarra; Pamplona; Spain
Objectives: To describe the methodology followed to characterize the subject’s specific type of pharmacodynamic (PD) drug interactions in leukemic patients.
Methods: Data obtained from ex vivo response vs concentration studies were used. Two studies including combination of two of drugs have been tested. Response was expressed as the absolute number of malignant cells alive (MCA). Data analysis was performed using the population approach using NONMEM 7.2. The modelling exercise involved the following steps: (i) population PD modelling of the ex vivo response vs concentration data in monotherapy, (ii) establishing for each patient the 95% prediction intervals (PI) of the isobologram based on the variance-covariance matrix from each individual parameter, (iii) computation of the combination index [1] using raw data descriptors from combination experiments, and (iv) finally characterization of the type of interaction calculating the distance between CI and the lower limit of the PI, and visualization of the results using colour maps.
Results: The inhibitory IMAX model was the selected model for all the drugs tested in this analysis. Inter-patient variability was included in all model parameters and in the residual part of the population model as well. For each patient and drug tested one thousand concentrations values corresponding to a 20, 40, 60 and 80% decrease in MAC with respect to baseline were simulated, allowing to generate for each patient and drug combination the individual isobologram with uncertainty. The type of interaction and its frequency found in the two studies, correlated well to which was previously known.
Conclusions: The proposed procedure can be largely automated to be used efficiently in personalized medicine programs. It avoids the need of modelling drug combination data, which it is not trivial and can lead to limitations at the time of estimating variability in the interaction parameters, making patient stratification difficult.
References:
[1] Chou T. Drug Combination Studies and Their Synergy Quantification Using the Chou-Talalay Method. Cancer Research 70: 440-446 (2010).
Reference: PAGE 22 () Abstr 2850 [www.page-meeting.org/?abstract=2850]
Poster: Oncology