PBPK modeling of propofol using the middle out approach
Robin Michelet, Jan Van Bocxlaer, An Vermeulen
Laboratory of Medical Biochemistry and Clinical Analysis, Faculty of Pharmaceutical Sciences, Ghent University, Belgium
Introduction: The project SAFEPEDRUG aims to provide guidelines for drug research in children, based on a combination of bottom-up and top-down approaches. Propofol, one of the drugs under study, is extensively metabolized in the liver and the kidney [1]–[3]. Furthermore, being a lipophilic molecule it distributes into the fat tissues, from where it slowly redistributes into the circulation [4]. In the past, both the bottom-up (PBPK, [5]) and top-down approach (popPK,[6], [7]) were applied to describe the PK of this compound with mixed results. In this work, a combination of the two approaches (middle-out approach) was applied to describe propofol PK.
Materials and methods: Clinical data containing different trial conditions were analyzed using a 3-compartment model in NONMEM v. 7.3, [8]. In vitro metabolism data was generated the same methodology as Gill et al. [9]. All data was then described using a full PBPK model in the Simcyp® Simulator V16 (Sheffield, UK). In vivo clearances were either obtained starting from in vitro clearance or scaled back from the in vivo clearance values estimated using NONMEM. Once an accurate in vivo clearance was obtained, the resulting model was challenged with new data.
Results: A CL of 1.07 L/h/kg and Vd of 822 L were estimated using the population approach. In vitro CLint values were consistent with literature, and an IVIVE would thus result in the same underprediction of total CL as described before. Therefore, the published model [9] was examined to see which parameters could increase the predicted CLiv. It was found that estimating the B:P and fu resulted in a predicted average CLiv of 1.01 L/h/kg compared to 0.39 L/h/kg before. Using the retrograde approach based on literature data, a match between predicted CLiv and NONMEM-derived CL was obtained. The model performed better than previous models and was able to describe PK for both long- and short-term infusions.
Conclusion: In the past, PBPK and PopPK have mostly been used side by side to describe PK. However, a better result is achieved if both are combined. When studying a complex ADME compound such as propofol, a PBPK approach is often recommended. However, current in vitro systems and IVIVE are not yet optimized for complexities such as UGT metabolism. Therefore, the best strategy is to integrate in vivo data with in vitro studies as is done in this model. Once an adult PBPK model is built, it can be scaled to children using knowledge of the ontogeny and maturation, which implies a correctly predicted contribution of each subsystem to the systemic clearance.
References:
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