Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations

Drug-induced liver injury (DILI) is the leading cause for acute liver failure in the USA and in Germany and one of the most common reasons for withdrawal of drugs from the market or failure of a drug candidate during development. Since DILI cannot be accurately predicted by animal models, a reliable in vitro test system for the prediction of human hepatotoxicity would be a valuable asset for drug development as well as for regulatory purposes. In this thesis an in vitro/in silico approach for the prediction of human hepatotoxicity in relation to blood concentrations and oral doses was established. This approach combines in vitro effective concentrations derived from a cytotoxicity assay, in vivo concentrations obtained by physiologically based pharmacokinetic (PBPK) modelling and a support vector machine (SVM) classifier based on these concentration pairs to predict the risk for hepatotoxicity for specific exposure scenarios. For systematic test system evaluation and optimization two novel performance metrics, the Toxicity Separation Index (TSI) and Toxicity Estimation Index (TEI), were utilized. These indices eliminate the need for a priori defined in vitro and in vivo concentrations and foster the systematic evaluation of the benefit of additional readouts. As a first step the feasibility of the in vitro/in silico approach was tested for primary human hepatocytes (PHH) and a training set of 28 compounds with in total 30 different in vitro/in vivo concentration vectors, yielding a sensitivity of 100%, a specificity of 88% and an accuracy of 93% in the leave-one-out classification with the SVM based classifier. A SVM based classifier utilizing all vectors was then applied to derive in combination with reverse PBPK modelling an acceptable daily intake (ADI) for the hepatotoxicant pulegone. The derived ADI was comparable to published ADIs based on two rodent studies. Next, the compound set was extended to a total of 80 compounds with 82 distinct in vitro/in vivo concentration pairs. The SVM leave-one-out classification resulted in a sensitivity of 77.8%, a specificity of 59.4% and an accuracy of 70.1%. Furthermore, the feasibility of the approach substituting HepG2 cells for the PHH and a combination of both cell culture systems for the extended compound set was evaluated. The obtained sensitivity was 88.9% and 86.7% and the specificity 62.5% and 65.6%, respectively. The accuracy was in both cases 77.9%

Nachweis des ßA4-Proteins mittels NIR: eine in vitro Machbarkeitsstudie

Die vorgelegte Studie beinhaltet Vorversuche zur möglichen Bildgebung des ßA4-Proteins in vivo im menschlichen Gehirn im Nah-Infrarot-Bereich. Dazu wurden Alzheimer-gehirngewebsproben mit einem biotinylierten D-Peptid und einem Cy5.0-Streptavidin inkubiert und das ßA4-Protein im Small Animal Near Infrared Fluorescence Imager optisch dargestellt. Die beiden Komponenten wurden zu einer fluorochromen one-step Sonde verbunden und damit auch Alzheimerplaques im Gehirngewebsschnitten im Detektor sichtbar gemacht. Der Einfluß des die Plaques umgebenden Gewebes auf die Fluoreszenzintensität des Fluorochroms wurde anhand von Phantomversuchen überprüft

Heterogeneity of oxygen reactivity: key for selectivity of partial methanol oxidation on gold surfaces

Recent evidence for low-temperature oxidation of methyl formate on Au(332) may affect the selectivity of gold catalysts during partial oxidation of methanol. Under isothermal conditions, overoxidation of methyl formate is significantly slower than methanol oxidation which can be attributed to special oxygen species required for overoxidation

Handling deviating control values in concentration-response curves

In cell biology, pharmacology and toxicology dose-response and concentration-response curves are frequently fitted to data with statistical methods. Such fits are used to derive quantitative measures (e.g. EC20 values) describing the relationship between the concentration of a compound or the strength of an intervention applied to cells and its effect on viability or function of these cells. Often, a reference, called negative control (or solvent control), is used to normalize the data. The negative control data sometimes deviate from the values measured for low (ineffective) test compound concentrations. In such cases, normalization of the data with respect to control values leads to biased estimates of the parameters of the concentration-response curve. Low quality estimates of effective concentrations can be the consequence. In a literature study, we found that this problem occurs in a large percentage of toxicological publications. We propose different strategies to tackle the problem, including complete omission of the controls. Data from a controlled simulation study indicate the best-suited problem solution for different data structure scenarios. This was further exemplified by a real concentration-response study. We provide the following recommendations how to handle deviating controls: (1) The log-logistic 4pLL model is a good default option. (2) When there are at least two concentrations in the no-effect range, low variances of the replicate measurements, and deviating controls, control values should be omitted before fitting the model. (3) When data are missing in the no-effect range, the Brain-Cousens model sometimes leads to better results than the default model

Unexpectedly high thermal stability of Au nanotriangle@mSiO2 yolk-shell nanoparticles

The shape of Au nanoparticles (NPs) plays a crucial role for applications in, amongst others, catalysis, electronic devices, biomedicine, and sensing. Typically, the deformation of the morphology of Au NPs is the most significant cause of loss of functionality. Here, we systematically investigate the thermal stability of Au nanotriangles (NTs) coated with (mesoporous) silica shells with different morphologies (core-shell (CS): Au NT@mSiO2/yolk-shell (YS): Au NT@mSiO2) and compare these to 'bare' nanoparticles (Au NTs), by a combination of in situ and/or ex situ TEM techniques and spectroscopy methods. Au NTs with a mesoporous silica (mSiO2) coating were found to show much higher thermal stability than those without a mSiO2 coating, as the mSiO2 shell restricts the (self-)diffusion of surface atoms. For the Au NT@mSiO2 CS and YS NPs, a thicker mSiO2 shell provides better protection than uncoated Au NTs. Surprisingly, the Au NT@mSiO2 YS NPs were found to be as stable as Au NT@mSiO2 CS NPs with a core-shell morphology. We hypothesize that the only explanation for this unexpected finding was the thicker and higher density SiO2 shell of YS NPs that prevents diffusion of Au surface atoms to more thermodynamically favorable positions