Current in vitro cellular methods utilised in drug metabolism and pharmacokinetic (DMPK) studies during drug development do not provide the 3D structure and functions of organs found in vivo, such that resulting in vitro-in vivo extrapolation (IVIVE) may not always accurately reflect clinical outcome. This highlights the need for the development of new dynamic in vitro cell models to aid improvement of IVIVE. The aim of this project was to incorporate characterised primary renal cells within a hollow fibre bioreactor for use in DMPK studies investigating renal clearance. Fluorescence based assays were developed to assess the functionality of three drug transporters involved in the renal transport of pharmaceutical compounds: P-gp, BCRP and OCT2. The developed assays were then applied alongside transporter visualisation and genetic expression assays to characterise primary human proximal tubule cells over a series of population doublings. Cells at a population doubling of 5 demonstrated the best transporter activity whilst allowing cells to be expanded in vitro. Polysulfone (PSF) based membranes, which are widely used in dialysis components were developed by blending additives to improve renal cell attachment and culture. The membranes exhibited a characteristic porous internal structure with smooth skin layers on the surface, and were able to be sterilised via autoclaving due to their high thermal stability. PSF blended with polyvinylpyrrolidone (PVP) was the most hydrophilic with cell metabolic activity similar to standard tissue culture plastic. The production of hollow fibres of varying thicknesses and properties from the PSF and PVP blend yielded a marked difference in renal cell attachment and long term viability. Fibres incorporated into glass casings to produce the single hollow fibre bioreactors (HFBs) were able to be sterilised by autoclaving whilst remaining intact. Due to the variation of fibre integrity within the batch, many fibres exhibited tears within the HFBs. This ultimately led to cell depletion within the fibre over the culture period; however, intact fibres demonstrated an increase in cell growth towards the end of the culture period under flow conditions. These results demonstrate the progress made towards a small scale in vitro renal model incorporating characterised primary renal cells to aid the improvement of IVIVE in DMPK research.

Ein nicht-invasiver Atemtest zur Lungenkrebsdetektion setzt Kenntnis über lungenkrebsspezifische Substanzen voraus. Die Identifizierung von Lungenkrebsbiomarkern in der Atemluft war das Ziel dieser Arbeit. Leichtflüchtige organische Substanzen (VOC) wurden als Zielkomponenten ausgewählt. Für die VOC-Analytik wurde eine SPME-GC-MS-Methode entwickelt und sowohl auf Modellsysteme als auch auf Realproben angewendet. Drei Lungenadenokarzinomzelllinien wurden in-vitro untersucht. Die VOC-Analyse wurde mit drei verschiedenen Probenahmestrategien durchgeführt und es war ein deutlicher Hintergrundeinfluss der eingesetzten Einwegzellkulturflaschen auf das analysierte VOC-Profil feststellbar. Trotzdem konnten signifikante Unterschiede zwischen Tumorzellen und zellfreien Nährmedien beobachtet werden: 1-Propanol wurde von den Zellen produziert, während der Gehalt einiger Aldehyde sank. Die eingeschränkte Ähnlichkeit des gewählten Zellkulturmodells mit realen Atemluftproben bedingt eine geringe Eignung dieser Ergebnisse für die Biomarkerableitung. Ein Gasmodell auf Basis angefeuchteter, synthetischer Luft wurde als Grundlage für die qualitätsgesicherte, quantitative VOC-Analyse der realen Atemluftproben konzipiert. Diese Modellluft wurde mit 24 Zielsubstanzen (Alkane, Aromaten, sauerstoffhaltige Spezies) sowie 3 Matrix-VOC mit starker Dominanz in den Atemluftproben (Isopren, Aceton, 2-Propanol) angereichert. In Kooperation mit zwei Berliner Kliniken wurden 37 Atemluftproben von Lungenkrebspatienten und 23 Proben von Gesunden gesammelt. Die Anwendung von 1-Butanol als univariater Marker erlaubt eine Erkennung von Lungenkrebs mit einer Sensitivität von 92% und Spezifität von 78%. Durch lineare Diskriminanzanalyse konnte ein Set aus 4 VOC (1-Butanol, 2-Butanon, 2-Pentanon, n-Hexanal) ermittelt werden, welches ebenfalls eine Sensitivität von 92% und mit 87% eine höhere Spezifität aufwies. Gegebenenfalls handelt es sich bei diesen Substanzen jedoch nur um allgemeine Krankheitsmarker. / A non-invasive breath test for lung cancer detection would be favorable but knowledge on lung cancer specific substances is required. This work aims at the identification of potential lung cancer biomarkers in breath. Volatile organic compounds (VOC) were chosen as targets and a SPME-GC-MS method was developed to analyze the VOC profiles of model systems and real samples. Three lung adenocarcinoma cell lines were investigated in-vitro. The VOC analysis, carried out with 3 different sampling strategies, was influenced by the VOC background of the used disposable culture vessels. Changes in the VOC profiles of cell lines compared to cell-free culture media were obvious: 1-propanol was released by the tumor cells whereas the content of some aldehydes was diminished. The similarity of this model system with real breath samples of lung cancer patients was seen to be insignificant. Consequently, these cell cultures were not suitable for biomarker identification. A gaseous model consisting of humidified synthetic air was developed. It was fortified with 24 target VOC (alkanes, aromatics and oxygenated species) as well as 3 matrix compounds (isoprene, acetone and 2-propanol) dominating patients’ VOC profiles in breath. This model was used for the quality assured quantitative VOC analysis in real breath samples. In cooperation with two hospitals 37 single mixed expiratory breath samples from lung cancer patients and 23 from healthy controls were collected. Applying 1-butanol as an univariate biomarker patients and controls were discriminated with a sensitivity of 92% and a specificity of 78%. Linear discriminant analysis displayed a set of 4 VOC (1-butanol, 2-butanone, 2-pentanone, n-hexanal) with similar sensitivity but higher specificity of 87%. However, these potential biomarkers might rather be a consequence of illness in general.