Model-based prediction of effective target exposure for MEN1611 in combination with trastuzumab in HER2-positive advanced or metastatic breast cancer patients.

MEN1611 is a novel orally bioavailable PI3K inhibitor currently in clinical development for patients with HER2-positive (HER2+) PI3KCA mutated advanced/metastatic breast cancer (BC) in combination with trastuzumab (TZB). In this work, a translational model-based approach to determine the minimum target exposure of MEN1611 in combination with TZB was applied. First, pharmacokinetic (PK) models for MEN1611 and TZB in mice were developed. Then, in vivo tumor growth inhibition (TGI) data from seven combination studies in mice xenograft models representative of the human HER2+ BC non-responsive to TZB (alterations of the PI3K/AkT/mTOR pathway) were analyzed using a PK-pharmacodynamic (PD) TGI model for co-administration of MEN1611 and TZB. The established PK-PD relationship was used to quantify the minimum effective MEN1611 concentration, as a function of TZB concentration, needed for tumor eradication in xenograft mice. Finally, a range of minimum effective exposures for MEN1611 were extrapolated to patients with BC, considering the typical steady-state TZB plasma levels in patients with BC following three alternative regimens (i.v. 4 mg/kg loading dose +2 mg/kg q1w, i.v. 8 mg/kg loading dose +6 mg/kg q3w or s.c. 600 mg q3w). A threshold of about 2000 ng·h/ml for MEN1611 exposure associated with a high likelihood of effective antitumor activity in a large majority of patients was identified for the 3-weekly and the weekly i.v. schedule for TZB. A slightly lower exposure (i.e., 25% lower) was found for the 3-weekly s.c. schedule. This important outcome confirmed the adequacy of the therapeutic dose administered in the ongoing phase 1b B-PRECISE-01 study in patients with HER2+ PI3KCA mutated advanced/metastatic BC.

A Minimal Physiologically Based Pharmacokinetic Model to Characterize CNS Distribution of Metronidazole in Neuro Care ICU Patients.

Understanding antibiotic concentration-time profiles in the central nervous system (CNS) is crucial to treat severe life-threatening CNS infections, such as nosocomial ventriculitis or meningitis. Yet CNS distribution is likely to be altered in patients with brain damage and infection/inflammation. Our objective was to develop a physiologically based pharmacokinetic (PBPK) model to predict brain concentration-time profiles of antibiotics and to simulate the impact of pathophysiological changes on CNS profiles. A minimal PBPK model consisting of three physiological brain compartments was developed from metronidazole concentrations previously measured in plasma, brain extracellular fluid (ECF) and cerebrospinal fluid (CSF) of eight brain-injured patients. Volumes and blood flows were fixed to their physiological value obtained from the literature. Diffusion clearances characterizing transport across the blood-brain barrier and blood-CSF barrier were estimated from system- and drug-specific parameters and were confirmed from a Caco-2 model. The model described well unbound metronidazole pharmacokinetic profiles in plasma, ECF and CSF. Simulations showed that with metronidazole, an antibiotic with extensive CNS distribution simply governed by passive diffusion, pathophysiological alterations of membrane permeability, brain ECF volume or cerebral blood flow would have no effect on ECF or CSF pharmacokinetic profiles. This work will serve as a starting point for the development of a new PBPK model to describe the CNS distribution of antibiotics with more limited permeability for which pathophysiological conditions are expected to have a greater effect.

A non-linear mixed effect model for innate immune response: In vivo kinetics of endotoxin and its induction of the cytokines tumor necrosis factor alpha and interleukin-6.

Endotoxin, a component of the outer membrane of Gram-negative bacteria, has been extensively studied as a stimulator of the innate immune response. However, the temporal aspects and exposure-response relationship of endotoxin and resulting cytokine induction and tolerance development is less well defined. The aim of this work was to establish an in silico model that simultaneously captures and connects the in vivo time-courses of endotoxin, tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), and associated tolerance development. Data from six studies of porcine endotoxemia in anesthetized piglets (n = 116) were combined and used in the analysis, with purified endotoxin (Escherichia coli O111:B4) being infused intravenously for 1-30 h in rates of 0.063-16.0 µg/kg/h across studies. All data were modelled simultaneously by means of importance sampling in the non-linear mixed effects modelling software NONMEM. The infused endotoxin followed one-compartment disposition and non-linear elimination, and stimulated the production of TNF-α to describe the rapid increase in plasma concentration. Tolerance development, observed as declining TNF-α concentration with continued infusion of endotoxin, was also driven by endotoxin as a concentration-dependent increase in the potency parameter related to TNF-α production (EC50). Production of IL-6 was stimulated by both endotoxin and TNF-α, and four consecutive transit compartments described delayed increase in plasma IL-6. A model which simultaneously account for the time-courses of endotoxin and two immune response markers, the cytokines TNF-α and IL-6, as well as the development of endotoxin tolerance, was successfully established. This model-based approach is unique in its description of the time-courses and their interrelation and may be applied within research on immune response to bacterial endotoxin, or in pre-clinical pharmaceutical research when dealing with study design or translational aspects.

A Whole-Body Physiologically Based Pharmacokinetic Model for Colistin and Colistin Methanesulfonate in Rat.

Colistin is a polymyxin antibiotic used to treat patients infected with multidrug-resistant Gram-negative bacteria (MDR-GNB). The objective of this work was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model to predict tissue distribution of colistin in rat. The distribution of a drug in a tissue is commonly characterized by its tissue-to-plasma partition coefficient, Kp . Colistin and its prodrug, colistin methanesulfonate (CMS) Kp priors, were measured experimentally from rat tissue homogenates or predicted in silico. The PK parameters of both compounds were estimated fitting in vivo their plasma concentration-time profiles from six rats receiving an i.v. bolus of CMS. The variability in the data was quantified by applying a nonlinear mixed effect (NLME) modelling approach. A WB-PBPK model was developed assuming a well-stirred and perfusion-limited distribution in tissue compartments. Prior information on tissue distribution of colistin and CMS was investigated following three scenarios: Kp was estimated using in silico Kp priors (I) or Kp was estimated using experimental Kp priors (II) or Kp was fixed to the experimental values (III). The WB-PBPK model best described colistin and CMS plasma concentration-time profiles in scenario II. Colistin-predicted concentrations in kidneys in scenario II were higher than in other tissues, which was consistent with its large experimental Kp prior. This might be explained by a high affinity of colistin for renal parenchyma and active reabsorption into the proximal tubular cells. In contrast, renal accumulation of colistin was not predicted in scenario I. Colistin and CMS clearance estimates were in agreement with published values. The developed model suggests using experimental priors over in silico Kp priors for kidneys to provide a better prediction of colistin renal distribution. Such models might serve in drug development for interspecies scaling and investigate the impact of disease state on colistin disposition.

A Population WB-PBPK Model of Colistin and its Prodrug CMS in Pigs: Focus on the Renal Distribution and Excretion.

PURPOSE: The objective was the development of a whole-body physiologically-based pharmacokinetic (WB-PBPK) model for colistin, and its prodrug colistimethate sodium (CMS), in pigs to explore their tissue distribution, especially in kidneys. METHODS: Plasma and tissue concentrations of CMS and colistin were measured after systemic administrations of different dosing regimens of CMS in pigs. The WB-PBPK model was developed based on these data according to a non-linear mixed effect approach and using NONMEM software. A detailed sub-model was implemented for kidneys to handle the complex disposition of CMS and colistin within this organ. RESULTS: The WB-PBPK model well captured the kinetic profiles of CMS and colistin in plasma. In kidneys, an accumulation and slow elimination of colistin were observed and well described by the model. Kidneys seemed to have a major role in the elimination processes, through tubular secretion of CMS and intracellular degradation of colistin. Lastly, to illustrate the usefulness of the PBPK model, an estimation of the withdrawal periods after veterinary use of CMS in pigs was made. CONCLUSIONS: The WB-PBPK model gives an insight into the renal distribution and elimination of CMS and colistin in pigs; it may be further developed to explore the colistin induced-nephrotoxicity in humans.

First plasma and tissue pharmacokinetic study of the YSNSG cyclopeptide, a new integrin antagonist, using microdialysis.

The YSNSG peptide is a synthetic peptide targeting αvß3 integrin. This peptide exhibits promising activity in vitro and in vivo against melanoma. To determine pharmacokinetic parameters and predictive active doses in the central nervous system (CNS) and subcutaneous tissue (SC), we conducted microdialysis coupled with pharmacokinetic modeling and Monte Carlo simulation. After a recovery period of surgical procedures, a microdialysis probe was inserted in the caudate and in subcutaneous tissue. Plasma samples and dialysates collected 5h after YSNSG intravenous administration (10mg/kg) were analyzed by UPLC-MS/MS. A nonlinear mixed-effect modeling approach implemented in Monolix® 2016R1 was performed. Model selection and evaluation were based on the usual diagnostic plot, precision and information criteria. The primary plasma and tissue pharmacokinetic parameters were comparable with those of other integrin antagonists, such as cilengitide or ATN-161. Tissue/plasma and brain/plasma area under the curve (AUC) ratio were 66.2±21.6% and 3.6±4.7%, respectively. Two models of 2-compartments with an additional microdialysis compartment, parameterized as rate constants (k for elimination, k12/k21 and k13/k31 for distribution) and volumes (central V1 and peripheral microdialysis compartment V3) with zero-order input were selected to describe the dialysate concentrations in CNS and SC. The inter-individual variability (IIV) was described by exponential terms, and residual variability was described by a combined additive and proportional error model. Individual AUC (plasma and tissues) values were derived for each animal using the Empirical-Bayes-Estimates of the individual parameters. The regimens needed to achieve an in vitro predetermined target concentration in tissues were studied by Monte Carlo simulations using Monolix® 2016R1. YSNSG pharmacokinetic parameters show promising results in terms of subcutaneous disposition. Further investigations into such processes as encapsulation and intratumoral disposition are currently being conducted.

Pharmacokinetics of Colistin Methansulphonate (CMS) and Colistin after CMS Nebulisation in Baboon Monkeys.

PURPOSE: The objective of this study was to compare two different nebulizers: Eflow rapid® and Pari LC star® by scintigraphy and PK modeling to simulate epithelial lining fluid concentrations from measured plasma concentrations, after nebulization of CMS in baboons. METHODS: Three baboons received CMS by IV infusion and by 2 types of aerosols generators and colistin by subcutaneous infusion. Gamma imaging was performed after nebulisation to determine colistin distribution in lungs. Blood samples were collected during 9 h and colistin and CMS plasma concentrations were measured by LC-MS/MS. A population pharmacokinetic analysis was conducted and simulations were performed to predict lung concentrations after nebulization. RESULTS: Higher aerosol distribution into lungs was observed by scintigraphy, when CMS was nebulized with Pari LC® star than with Eflow Rapid® nebulizer. This observation was confirmed by the fraction of CMS deposited into the lung (respectively 3.5% versus 1.3%).CMS and colistin simulated concentrations in epithelial lining fluid were higher after using the Pari LC star® than the Eflow rapid® system. CONCLUSIONS: A limited fraction of CMS reaches lungs after nebulization, but higher colistin plasma concentrations were measured and higher intrapulmonary colistin concentrations were simulated with the Pari LC Star® than with the Eflow Rapid® system.

Utility of in vitro systems and preclinical data for the prediction of human intestinal first-pass metabolism during drug discovery and preclinical development.

A growing awareness of the risks associated with extensive intestinal metabolism has triggered an interest in developing robust methods for its quantitative assessment. This study explored the utility of intestinal S9 fractions, human liver microsomes, and recombinant cytochromes P450 to quantify CYP3A-mediated intestinal extraction in humans for a selection of marketed drugs that are predominantly metabolized by CYP3A4. A simple competing rates model is used to estimate the fraction of drug escaping gut wall metabolism (fg) from in vitro intrinsic clearance in humans. The fg values extrapolated from the three in vitro systems used in this study, together with literature-derived fg from human intestinal microsomes, were validated against fg extracted from human in vivo pharmacokinetic (PK) profiles using a generic whole-body physiologically-based pharmacokinetic (PBPK) model. The utility of the rat as a model for human CYP3A-mediated intestinal metabolism was also evaluated. Human fg from PBPK compares well with that from the grapefruit juice method, justifying its use for the evaluation of human in vitro systems. Predictive performance of all human in vitro systems was comparable [root mean square error (RMSE) = 0.22-0.27; n = 10]. Rat fg derived from in vivo PK profiles using PBPK has the lowest RMSE (0.19; n = 11) for the prediction of human fg for the selected compounds, most of which have a fraction absorbed close to 1. On the basis of these evaluations, the combined use of fg from human in vitro systems and rats is recommended for the estimation of CYP3A4-mediated intestinal metabolism in lead optimization and preclinical development phases.