Qualichem In Vivo: A Tool for Assessing the Quality of In Vivo Studies and Its Application for Bisphenol A

In regulatory toxicology, quality assessment of in vivo studies is a critical step for assessing chemical risks. It is crucial for preserving public health studies that are considered suitable for regulating chemicals are robust. Current procedures for conducting quality assessments in safety agencies are not structured, clear or consistent. This leaves room for criticism about lack of transparency, subjective influence and the potential for insufficient protection provided by resulting safety standards. We propose a tool called “Qualichem in vivo” that is designed to systematically and transparently assess the quality of in vivo studies used in chemical health risk assessment. We demonstrate its use here with 12 experts, using two controversial studies on Bisphenol A (BPA) that played an important role in BPA regulation in Europe. The results obtained with Qualichem contradict the quality assessments conducted by expert committees in safety agencies for both of these studies. Furthermore, they show that reliance on standardized guidelines to ensure scientific quality is only partially justified. Qualichem allows experts with different disciplinary backgrounds and professional experiences to express their individual and sometimes divergent views—an improvement over the current way of dealing with minority opinions. It provides a transparent framework for expressing an aggregated, multi-expert level of confidence in a study, and allows a simple graphical representation of how well the study integrates the best available scientific knowledge. Qualichem can be used to compare assessments of the same study by different health agencies, increasing transparency and trust in the work of expert committees. In addition, it may be used in systematic evaluation of in vivo studies submitted by industry in the dossiers that are required for compliance with the REACH Regulation. Qualichem provides a balanced, common framework for assessing the quality of studies that may or may not be following standardized guidelines.     

A Statistical Model for In Vivo Neuronal Dynamics

Single neuron models have a long tradition in computational neuroscience. Detailed biophysical models such as the Hodgkin-Huxley model as well as simplified neuron models such as the class of integrate-and-fire models relate the input current to the membrane potential of the neuron. Those types of models have been extensively fitted to in vitro data where the input current is controlled. Those models are however of little use when it comes to characterize intracellular in vivo recordings since the input to the neuron is not known. Here we propose a novel single neuron model that characterizes the statistical properties of in vivo recordings. More specifically, we propose a stochastic process where the subthreshold membrane potential follows a Gaussian process and the spike emission intensity depends nonlinearly on the membrane potential as well as the spiking history. We first show that the model has a rich dynamical repertoire since it can capture arbitrary subthreshold autocovariance functions, firing-rate adaptations as well as arbitrary shapes of the action potential. We then show that this model can be efficiently fitted to data without overfitting. We finally show that this model can be used to characterize and therefore precisely compare various intracellular in vivo recordings from different animals and experimental conditions.