Développement et validation de modèles in silico pour évaluer la variation de clairance hépatique des médicaments fortement liés aux protéines plasmatiques

The prediction of pharmacokinetic/toxicokinetic (PK/TK) parameters such as intrinsic clearance (CLint) and hepatic clearance (CLh) for highly bound drugs is a major challenge in quantitative modeling. According to the ‘free drug hypothesis’, only the free drug can pass through the plasma membrane and the CLh of this drug is calculated according to its free fraction (fup). Nevertheless, the hepatic uptake facilitated by albumin (ALB) is a violation of the ‘free drug hypothesis’. This facilitated hepatic uptake is based on the possibility that the ALB-drug complex may provide additional drug intake to the hepatocytes. Thus, this could largely explain the underpredictions of CLh. In addition, some drugs can bind extensively in plasma, and to several plasma proteins such as ALB and alpha-1-glycoprotein acid (AGP). Thus, the high binding of the same drug to either ALB or AGP, or to both, could have distinct impacts on the prediction of these PK/TK parameters. However, no study has yet explored how to simulate the difference between these impacts.  The main objective of this thesis is therefore to evaluate (with accuracy and precision) for a series of drugs, in the in vivo (or in situ) condition, these impacts in the presence of the two plasma proteins, jointly or separately. Also, it is important to verify if a generic model can be applied. This thesis is divided into three specific objectives. The first is to propose a decision tree to facilitate the selection of appropriate predictive approaches of CLhin vivo for drugs with different characteristics. The second is to assess the impacts of extensive binding to the two plasma proteins ALB and AGP on the CLh of two selected xenobiotics (perampanel (PER) and fluoxetine (FLU)); these drugs have strong affinities to both proteins and an exclusive (or predominant) metabolism in the liver. And the last objective is to develop and validate a new predictive model of CLh for xenobiotics with the potential to bind extensively to ALB as well as to AGP.  Firstly, in vitro data obtained in humans were collected for 19 drugs (i.e. substrates of OAT2 and OATP1B1 transporters) and were then used in six in vitro-to-in vivo (IVIVE) extrapolation models to predict these PK/TK parameters. After a statistical comparison, the results showed that the approach 2 (i.e. ‘fup-adjusted model’) that is based on the ALB-facilitated hepatic uptake, had the best predictive performance. However, the approach 5 (i.e. ‘Extended Clearance Model’) that is based on the membrane transporter-mediated uptake, was very relevant to apply for the substrates of membrane transporters. These substrates would potentially be less affected by ALB. Thus, a decision tree has been proposed to quickly and judiciously select the best IVIVE approach to predict CLhin vivo for each xenobiotic in the presence of ALB.  Secondly, the PER and FLU drugs were selected from a data collection of 1907 drugs depending on certain criteria (exclusive or predominant metabolism in the liver, no transport facilitated by membrane transporters, high affinity for the two proteins ALB and AGP, and having a binding ratio between AGP and ALB close to the unity). This selection was made to conduct experiments using the isolated and perfused rat liver (IPRL) apparatus, in the presence, and in the absence of the ALB and AGP proteins (i.e. four IPRL scenarios). The IPRL results showed that PER is low to moderately metabolized (hepatic extraction= 0.2-0.7), while FLU is highly metabolized (hepatic extraction= 0.8-0.99). The Michaelis-Menten model was fitted to the obtained metabolic kinetics, and different parameters Vmax, Km and Km, u were obtained from the model. At low free concentrations for both drugs (i.e. therapeutic concentrations) and in the presence of plasma proteins, the values of unbound CLint increased for PER (with ALB and the mixture of the two proteins (MIX)) and FLU (with ALB, AGP and MIX); when compared to those obtained from the protein-free scenario (except for PER with AGP, the unbound CLint values decreased). In addition, the calculations of CLint ratios (WITHOUT versus WITH protein) indicated the occurrence of a hepatic uptake facilitated by ALB or AGP. These ratios also helped in verifying whether the metabolic kinetics for PER and FLU followed either ‘the free drug hypothesis’ or that of ‘plasma protein-facilitated hepatic uptake’.  Finally, a new predictive approach of CLh (WO-to-MIX approach) was developed based on a new notion of fractional binding and incorporating new parameters such as the ALB bound fraction (fB-ALB) and the AGP bound fraction (fB-AGP) from the MIX scenario into the ‘fup-adjusted model’. This model is based on the ‘ALB-facilitated hepatic uptake’. Unlike the WO-to-MIX approach, the ‘well-stirred model’ is based on ‘the free drug hypothesis’. Then, the Vmax and Km parameters that were obtained in situ for PER and FLU from the protein-free IPRL experiments, were used in combination with the fup-adjusted input parameter for the ‘fup-adjusted model’ or with the free fraction (fup) for the ‘well-stirred model’. A comparison of the two models’ overall predictive performances was made. The predictive performances of the new model were promising for FLU, which showed the highest degree of ‘ALB-mediated hepatic uptake’, compared to the conventional model. This WO-to-MIX approach is a first validation of a novel extrapolation model suggested for drugs such as FLU that bind to both ALB and AGP. The well-stirred model remains however a useful tool to predict the clearance for drugs such as PER. The prediction accuracy was lower for the latter drug probably because the ALB-mediated hepatic uptake does not seem to be maximal, and, hence, the use of fup-adjusted has overestimated its CLhin vivo. Therefore, more work is needed particularly for PER.  This thesis shows that a generic approach to predict the CLh in vivo does not exist. Nevertheless, the choice of an IVIVE approach with satisfactory predictive performances is now possible. The results of this thesis contribute to: 1) better understand the impacts on the PK/TK parameters of extensive drug binding to ALB and AGP; 2) choose the best predictive approach to CLh based on the affinity of xenobiotic (drug or contaminant) to each of the plasma proteins and the mechanisms involved in the liver; and 3) predict accurately and with precision the output CLh of xenobiotics that bind to the two plasma proteins. These IVIVE approaches for CLh can certainly be integrated into physiologically based PK/TK models for xenobiotics to improve the prediction of their pharmacokinetics and to accelerate the drug development process.

Keyphrases: Hepatic clearance, Extensive plasma protein binding, Pharmacokinetic interactions, Albumin, Alpha-1-acid glycoprotein, Plasma protein-mediated uptake, Membrane transporters, In vitro-in vivo extrapolation, Isolated and perfused rat liver