Development of an in vitro system and model-based translational framework to assess haemolysis risk following intravenous abuse of medications containing polyethylene oxide.

Multiple cases of potentially life-threatening thrombotic microangiopathy (TMA) have resulted from intravenous abuse of medications containing polyethylene oxide (PEO), most often Opana ER (oxymorphone hydrochloride extended release). No validated models are available to assess the risk of TMA with different formulations and extraction methods following intravenous abuse. We have developed an in vitro system that involves passing pooled blood containing the excipient of interest through a syringe needle and assessing haemolysis via haemoglobin release. Haemolysis is induced by high shear stress caused by the flow of blood containing PEO through a narrow-bore syringe needle, recapitulating the mechanism in small blood vessels. Using the in vitro system, we demonstrate that high-molecular-weight PEO (>1 MDa) induces haemolysis in a concentration-dependent manner under flowing but not static conditions. We use data from the in vitro system and published in vivo data to predict the time course of the haemolytic response in vivo via a pharmacometric model. The in vitro system is a novel method for investigating factors influencing PEO-induced haemolysis. In combination with our model-based translational framework, the in vitro system allows straightforward assessment of the haemolytic potential of PEO-containing medications, and may find application in gauging TMA risk following intravenous abuse.

Model-based assessment of erlotinib effect in vitro measured by real-time cell analysis.

Real time cell analysis (RTCA) is an impedance-based technology which tracks various living cell characteristics over time, such as their number, morphology or adhesion to the extra cellular matrix. However, there is no consensus about how RTCA data should be used to quantitatively evaluate pharmacodynamic parameters which describe drug efficacy or toxicity. The purpose of this work was to determine how RTCA data can be analyzed with mathematical modeling to explore and quantify drug effect in vitro. The pharmacokinetic-pharmacodynamic erlotinib concentration profile predicted by the model and its effect on the human epidermoïd carcinoma cell line A431 in vitro was measured through RTCA output, designated as cell index. A population approach was used to estimate model parameter values, considering a plate well as the statistical unit. The model related the cell index to the number of cells by means of a proportionality factor. Cell growth was described by an exponential model. A delay between erlotinib pharmacokinetics and cell killing was described by a transit compartment model, and the effect potency, by an E max function of erlotinib concentration. The modeling analysis performed on RTCA data distinguished drug effects in vitro on cell number from other effects likely to modify the relationship between cell index and cell number. It also revealed a time-dependent decrease of erlotinib concentration over time, described by a mono-exponential pharmacokinetic model with nonspecific binding.

100% human monoclonal antibodies in oncology: hype or breakthrough?

Targeted therapies have dramatically modified treatment strategies in oncology since the early 2000's, especially for treating digestive cancers. These new biotherapies such as anti-VEGF (bevacizumab) or anti-EGFR (cetuximab) monoclonal antibodies have given oncologists new opportunities to use innovative treatment schedules or combinations with cytotoxics. Consequently, significant improvements in response rates, with trends to longer progression-free survival and/or overall survival have been achieved in patients with metastatic colorectal cancer (mCRC). Panitumumab is a novel, 100% human, anti-EGFR1 (HER1) antibody that has been approved in late 2007 for use as monotherapy in mCRC patients resistant to standard chemotherapy, provided that their tumor express EGFR and display wild-type K-Ras status. Panitumumab has been recently further approved in combination with chemotherapy in mCRC patients. However, owing to the fact that its mechanism of action for targeting EGFR is similar to that of chimeric cetuximab, picturing the specificities in pharmacological and pharmacokinetic properties of this 100% human antibody could help the oncologists to better define their strategies at the bedside.

Progress in strategies for dosage regimen individualization.

Several findings suggest that patient outcome would be improved with individualized doses. The aim of this paper is to describe major approaches, methods and underlying basic foundations implemented, in clinical practice, for dosage individualization. Also we propose a new method codified by kinetic nomograms as reliable alternative to traditional Bayesian methods. Clinical and simulation data were reported to evaluate performances of the proposed methods. Real examples of therapeutic drug monitoring were selected. Bayesian methods were used to individualize high-dose methotrexate rate infusion and amikacin dosage regimen, and kinetic nomograms to adjust sirolimus doses. 1) Using only few measurements, Bayesian method resulted in accurate estimates of individual pharmacokinetic parameters of high dose methotrexate infusion. Targeting a pre-defined end-of-infusion level, infusion rate was individualized according to the previously obtained pharmacokinetic parameters. 2) With the same reasoning, individual pharmacokinetic parameters of amikacin were obtained by Bayesian estimation using three individual samples. Subsequent dosage adjustment allowed achievement of therapeutic goals at steady state. 3) Without computing individual pharmacokinetic parameters, nor using pharmacokinetic software, kinetic nomograms steered individual sirolimus blood levels within its therapeutic window with only two samples and in the first week after starting treatment. This contribution relates traditional Bayesian methods developed in 80's but not yet fully integrated in clinical context because of their complexity. The contribution focuses on recent developments based on population approaches, rendering the dosage adjustment methodology a simple and quick bedside application.