Fiona G. Gao (1,2), Mônica Villa Nova (1), Mukul Ashtikar (1), Matthias G. Wacker (1,2)
(1) Fraunhofer IME, Project Group Translational Medicine and Pharmacology, Germany, (2) Goethe University, Institute of Pharmaceutical Technology, Germany
Introduction: Subcutaneous depot formulations are increasingly being utilized, especially for the administration of biopharmaceuticals. However, the mechanism of drug release and absorption as well as lymphatic uptake at subcutaneous site remains unfathomed. In our project, we focus on Physiologically based pharmacokinetic (PBPK) modeling for subcutaneously administered depot formulations. For the current study, a commercially marketed depot formulation (Provera®) was selected. Feasible in silico pharmacokinetic (PK) simulation for depot formulations requires a suitable in vitro release method. A dialysis-based setup – the Dispersion Releaser (DR) has been successfully applied to test the drug release from nanosized drug carriers [1, 2] and was used to investigate the release kinetic of Provera®. Before the construction of an intricate PBPK model, a mechanism-based pharmacokinetic (MBPK) model was built in order to facilitate an exploratory research to determine the impact of release, absorption and lymphatic uptake on PK profile. Here, we try to demonstrate the influence of relevant changes in release emphatically.
Objectives:
- Integrate in vitro parameters, i.e. release and diffusion rate, into a MBPK model to estimate the in vivo drug performance
- Verify the MBPK model by evaluating the in silico-in vivo correlation
- Investigate the impact of release relevant parameters on PK profile
Methods: The release of Provera® in a buffer system simulating subcutaneous environment was investigated using the patented DR technique. The drug release kinetics was described with the Reciprocal Powered Time (RPT) model. The diffusion of free drug molecules was analyzed by performing agarose gel assay. For this purpose, a validated method was modified to comply with the lipophilic drug molecules [3]. A MBPK model was built in STELLA software integrating the release relevant parameters and diffusion rate. Additionally, other PK or physiological parameters were either determined using PK modeling in Phoenix WinNonlin or taken from literature.[4-6] The model was verified by comparing the in silico simulated PK profile with the clinical data of Provera®. At the same time, the local sensitivity analysis was utilized for evaluating the impact of release relevant parameter on PK simulation output.
Results: The cumulative drug release fraction (F) fitted using RPT model:
where m and b were release relevant parameters with the value of 0.14 and 0.92, respectively. The cumulative diffusion fraction of free drug molecules was determined as 8.75% per hour. Applying these parameters to the model, PK profile was simulated and precise prediction of Cmax, Tmax and AUC was achieved. With the local sensitivity analysis, it was confirmed that release relevant parameters were essential for the built MBPK model. The 10% change of release rate exerted significant influence on Cmax and Tmax. Also the AUC was not affected by this change.
Conclusions: The drug release test using DR technique as well as the agarose gel based diffusion assay were useful tools for the determination of formulation parameters. They enabled a MBPK simulation of subcutaneously administered drug products. The multiple compartment MBPK model was capable of predicting the in vivo release, absorption, distribution, and elimination of Provera® with high precision. The next step will be to develop this MBPK model into a detailed PBPK model to simulate the in vivo PK for subcutaneous depot of biopharmaceuticals.
References:
[1] Janas, C., et al., The dispersion releaser technology is an effective method for testing drug release from nanosized drug carriers. Eur J Pharm Biopharm, 2017. 115: p. 73-83.
[2]Villa Nova, M., et al., Nanocarriers for photodynamic therapy-rational formulation design and medium-scale manufacture. Int J Pharm, 2015. 491(1-2): p. 250-60.
[3] Beyer, S., et al., Optimizing novel implant formulations for the prolonged release of biopharmaceuticals using in vitro and in vivo imaging techniques. J Control Release, 2016. 235: p. 352-364.
[4] McLennan, D.N., C.J. Porter, and S.A. Charman, Subcutaneous drug delivery and the role of the lymphatics. Drug Discov Today Technol, 2005. 2(1): p. 89-96.
[5] Gill, K.L., et al., A Bottom-Up Whole-Body Physiologically Based Pharmacokinetic Model to Mechanistically Predict Tissue Distribution and the Rate of Subcutaneous Absorption of Therapeutic Proteins. Aaps j, 2016. 18(1): p. 156-70.
[6] Soeborg, T., et al., Absorption kinetics of insulin after subcutaneous administration. Eur J Pharm Sci, 2009. 36(1): p. 78-90.
Reference: PAGE 27 (2018) Abstr 8493 [www.page-meeting.org/?abstract=8493]
Poster: Methodology - Study Design