No abstract

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 ( EC 50 ). 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 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.

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.

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, K . Colistin and its prodrug, colistin methanesulfonate (CMS) K 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: K was estimated using in silico K priors (I) or K was estimated using experimental K priors (II) or K 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 K 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 K 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.

No abstract

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.

-Objectives:A liquid/liquid extraction technique on solid support of Δ 9 -tetradydrocannabinol (THC), 11-hydroxy-Δ 9 -tetradydrocannabinol (11-OH-THC) and 11-nor-Δ 9 -tetradydrocannabinol-9-carboxylic acid (THC-COOH) in plasma was developed in order to be assayed by high-performance liquid chromatography and tandem mass spectrometry (HPLC-MS/MS). Methods: The samples were extracted by liquid/liquid extraction over solid support of an extraction cartridge. The extracts were thereafter dried down and injected into the HPLC-MS/MS system set with a positive electrospray mode using a Waters XTerra MS C18 3.5-μm 2.1 × 150 mm column. Results: The extraction recovery levels were 66%, 70% and 71% for THC, and 75%, 93% and 101% for 11-OH-THC at concentrations of 2.5, 5 and 10 ng/mL, respectively. They were 86% and 78% for THC-COOH at concentrations of 5 and 10 ng/mL. The limits of detection (LOD) were 0.09, 0.08 and 0.91 ng/mL for THC, 11-OH-THC and THC-COOH, respectively. The limits of quantification (LOQ) were 0.16, 0.15 and 3.24 ng/mL for THC, 11-OH-THC and THC-COOH, respectively. The inter-series incertitude CV determined for concentrations of 1, 2.5 and 10 ng/mL were 12.1%, 12.0% and 6.4% for THC, 14.5%, 11.1% and 7.2% for 11-OH-THC, and 14.9%, 26.2% and 11.3% for THC-COOH. Conclusion: The novel extraction method for THC, 11-OH-THC and THC-COOH developed in this work is rapid, sensitive and specific. It may be a valuable tool for predictive toxicology, high-throughput metabolism and pharmacokinetic studies of cannabinoids.