Physiologically-Based Kinetics and Mechanistic Models to Assess Exposure to Chemicals
In our modern society we are exposed to a myriad of chemical substances. Before these substances can be brought onto the market for use and consumption, their safety – when used as intended – needs to be confirmed in a risk assessment. Typically, a risk assessment comprises a toxicological hazard assessment, the quantification of a dose-response relationship, an exposure assessment and a risk characterisation under the assessed conditions. Traditionally, a toxicological hazard assessment is performed in vivo in laboratory animals, and more recently, in targeted in vitro testing. However, due to calls for replacement, reduction and refinement of animal testing alternative methods such as in silico models are increasingly being used. Also, increasing emphasis is being placed on understanding mechanisms and pathways of toxicity as well as quantifying exposure which leads to an adverse effect in individuals. Physiologically-based kinetic and mechanistic models allow for a mathematical description of causal relationships between an exposure scenario and a toxicological outcome in a biological system. While much research has been focussed on investigating mechanisms of hepatotoxicity, little is known about adverse effects induced in the kidney and only limited computational models exist to investigate nephrotoxicity. However, the kidney is a major target for toxicity by pharmaceuticals and environmental pollutants. Accumulation is known to play an important role in certain nephrotoxicity pathways. Therefore, physiologically-based kinetic and mechanistic models are considered to offer valuable insights into mechanisms of nephrotoxicity. This thesis addresses the growing attention given to exposure-based and toxicokinetics-driven toxicity which has resulted in increasing recent application of PBK modelling. The overall aim of this thesis was to propose novel ways to use publicly available data for the quantitative assessment of adverse effects induced in the kidney following chemical exposure. The first part of this thesis examines the suitability of publicly available PBK models for the prediction of urine-level concentrations in the general population following oral doses of various chemicals. Human biomonitoring (HBM) data were used for validation of simulation results and a mixture risk assessment to illustrate how predictions may be used in a risk assessment context. The second part of this thesis shows the development of a mechanistic kidney model embedded in a full-body PBK model parameterised for aspirin (ASA) and salicylic acid (SA). The research presented herein demonstrates the generation of a novel kidney model which is set up for a young and healthy individual; this was amended to simulate kinetics of elderly individuals and tested for three exposure scenarios. Key challenges in this endeavour revolve around limited data available in the public literature and uncertainties related to scaling in vitro data to an in vivo setting.
QD Chemistry, QP Physiology, RM Therapeutics. Pharmacology, RS Pharmacy and materia medica
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