Pharmacokinetic-pharmacodynamic modeling of activity of ceftazidime during continuous and intermittent infusion

We developed and applied pharmacokinetic-pharmacodynamic (PK-PD) models to characterize in vitro bacterial rate of killing as a function of ceftazidime concentrations over time. For PK-PD modeling, data obtained during continuous and intermittent infusion of ceftazidime in Pseudomonas aeruginosa killing experiments with an in vitro pharmacokinetic model were used. The basic PK-PD model was a maximum-effect model which described the number of viable bacteria (N) as a function of the growth rate (lambda) and killing rate (epsilon) according to the equation dN/dt = [lambda - epsilon x [Cgamma(EC50gamma + Cgamma)]] N, where gamma is the Hill factor, C is the concentration of antibiotic, and EC50 is the concentration of antibiotic at which 50% of the maximum effect is obtained. Next, four different models with increasing complexity were analyzed by using the EDSIM program (MediWare, Groningen, The Netherlands). These models incorporated either an adaptation rate factor and a maximum number of bacteria (Nmax) factor or combinations of the two parameters. In addition, a two-population model was evaluated. Model discrimination was by Akaike's information criterion. The experimental data were best described by the model which included an Nmax term and a rate term for adaptation for a period up to 36 h. The absolute values for maximal growth rate and killing rate in this model were different from those in the original experiment, but net growth rates were comparable. It is concluded that the derived models can describe bacterial growth and killing in the presence of antibiotic concentrations mimicking human pharmacokinetics. Application of these models will eventually provide us with parameters which can be used for further dosage optimization

Current opinion on optimal systemic treatment for metastatic colorectal cancer: outcome of the ACTG/AGITG expert meeting ECCO 2013

The treatment of metastatic colorectal cancer has evolved greatly in the last 15 years, involving combined chemotherapy protocols and, in more recent times, new biologic agents. Clinical benefit from the use of targeted therapy with bevacizumab, aflibercept, cetuximab, panitumumab and regorafenib in the treatment of metastatic colorectal cancer is now well established with median overall survival accepted as over 24 months, and with super selection for extended RAS patients higher again. The optimal timing of treatment options requires careful consideration of predictive biomarkers, and importantly the potential for interactions, to derive the maximal benefit. A group of colorectal subspecialty medical oncologists from Australia, the USA, the Netherlands and Germany met during ECCO 2013 to discuss current practice. Subsequent new data from the American Society of Clinical Oncology were also reviewed. This article reviews the evidence discussed in support of modern treatments for colorectal cancer and the decision-making behind the treatment choices, with their benefits and risks.Timothy J Price, Eva Segelov, Matthew Burge, Daniel G Haller, Niall C Tebbutt, Christos S Karapetis, Cornelis JA Punt, Nick Pavlakis, Dirk Arnold, Peter Gibbs and Jeremy D Shapir

Genomic landscape of metastatic colorectal cancer

Contains fulltext : 139110.pdf (publisher's version ) (Open Access)Response to drug therapy in individual colorectal cancer (CRC) patients is associated with tumour biology. Here we describe the genomic landscape of tumour samples of a homogeneous well-annotated series of patients with metastatic CRC (mCRC) of two phase III clinical trials, CAIRO and CAIRO2. DNA copy number aberrations of 349 patients are determined. Within three treatment arms, 194 chromosomal subregions are associated with progression-free survival (PFS; uncorrected single-test P-values <0.005). These subregions are filtered for effect on messenger RNA expression, using an independent data set from The Cancer Genome Atlas which returned 171 genes. Three chromosomal regions are associated with a significant difference in PFS between treatment arms with or without irinotecan. One of these regions, 6q16.1-q21, correlates in vitro with sensitivity to SN-38, the active metabolite of irinotecan. This genomic landscape of mCRC reveals a number of DNA copy number aberrations associated with response to drug therapy

Genome-wide cell-free DNA fragmentation in patients with cancer

Item does not contain fulltextCell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer(1). However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer