The project has focused on three relevant target organs of toxicity, the liver, the kidney and the central nervous system. The overall aim of the project was to improve the predictivity of in vitro systems for unwanted effects of pharmaceutical entities by applying a combination of “omics” technology in optimized cellular systems along with biokinetic quantification.
For the liver, 11 compounds were tested in three different hepatic models: primary human hepatocytes (PHH), primary rat hepatocytes (PRH) and the hepatoma cell line HepaRG. The different cell models were capable of metabolising the selected parent compounds, albeit with different sensitivities. For example, ibuprofen metabolism was highest in PHH, where cytotoxicity was also lowest. Bioinformatic analysis of the transcriptomic signatures also provided highly useful mechanistic information. For example analysis of chlorpromazine differentially regulated genes revealed inflammation/hepatitis, cholestasis and hyperplasia to be the major mechanisms, which is in line what is known in vivo. A number of other tissue specific and mechanistic biomarkers have been identified.
A single model was chosen for the kidney, i.e. the non-transformed normal human proximal tubular cell line, RPTEC/TERT1. Nine compounds were tested for in depth omic analysis where cells were cultured on microporous supports and differentiated for 10 days prior to treatment. Furthermore, since renal disease often has an ischemic component, we have investigated the effects of hypoxia on compound-induced toxicity a number of compounds and conducted deep omic analysis for two of these. We have focused our bioinformatics analysis to three areas; (1) mechanistic effects, (2) tissue specific effects and (3) potential clinical biomarkers. The results from the three kidney kinetic compounds show that the RPTEC/TERT1 cells coupled with pharmacokinetics and high content omic approaches gives extremely detailed and quantitative insights into both the pharmacological and toxicological effects of compounds.
As CNS models, we analysed two neuronal primary models including a 2D mouse model and a 3D aggregating rat model. Twelve compounds were tested using both target assays and omics analysis, and as with the other organs a smaller subgroup was used for biokinetic modelling. Aggregating 3D brain cultures developed features of higher cellular organization, including neurons, astrocytes and oligodendrocytes. A stochastic time-concentration activity model for in vitro cytotoxicity has been developed describing transitions from healthy to stressed cells and from stressed cells to death. The 2D mouse model allows the measurement of neuronal activity by measuring electrophysiological alteration when cells are cultured on micro electrode arrays. For the majority of the compounds tested the neuroactive effects did not correlate with toxicity. Pattern recognition of this data allowed for the development of „activity fingerprints“ for the compound classes. An in vitro blood-brain barrier (BBB) was also investigated for its potential integration into the in vitro testing strategy for drug-induced neurotoxicity testing. The effects of single and repeated exposure regimens on an in vitro BBB model showed the treatment regimens strongly influence the exposure levels achieved and demonstrated the importance of evaluating BBB toxicity in repeated-dose testing.
Taken together, we have generated a large data-set of mechanistically-rich information for three target organs in long-term repeat-dose investigations. The data-set represents several layers of biological information and includes transcriptomic, proteomic and metabolomic profiles. Moreover we have quantified parent compounds and their distribution in various in vitro compartments. This has allowed us to develop biokinetic models where we could derive the real exposure concentration in vitro, enabling the definition of human relevant free and toxic exposure levels. The knowledge developed within the project can be applied for screening purposes to filter highly toxic substances from being tested in animals in preclinical studies, and therefore contributes to the 3R principle. Furthermore this project demonstrates the applicability of in vitro test systems for human drug safety evaluation and will form the basis for the eventual replacement of animals in pre-clinical testing regimes.