Mass spectrometry methods for profiling xenobiotic distribution in biofluids and whole tissues

Abstract

Historically, studies of drug biodistribution are traditionally carried out in the later stages of pre-clinical pharmaceutical research and development (R&D) using radio-labelled techniques. Such studies are often slow, expensive and unselective, meaning resulting data can be complicated to deconvolute and too late in the development pipeline to change the medicine under investigation. Mass spectrometry imaging (MSI) has the potential to provide an unlabelled, multiplex method of mapping and quantifying molecular distributions within tissues at a much earlier stage in the R&D timeline, informing researchers of exposure in target tissue or providing evidence of localised and accumulated drug concentration in tissues exhibiting symptoms of toxicity. The research presented in this thesis begins by exploring the use of MALDI, DESI and LESA-MSI in early pharmacokinetic cassette dosing studies. Furthermore, MSI techniques were applied to blood brain barrier penetration studies to assess compound penetration profiles. Quantitative MSI (qMSI) methods were studied using tissue mimetics to generate accurate calibration lines and produce in situ concentration data. Finally, region specific qMSI was used to quantify endogenous metabolite concentrations and evaluate tumour heterogeneity in several different tumour models, identifying a model that would be used in pre-clinical efficacy studies. The results indicate that MSI drug distribution studies can be performed much earlier in the lead optimisation stage of the drug discovery process. This was done using a range of MSI platforms with different sensitivity, spatial resolution and chemical scope. The use of LESA-MSI to assess drug blood brain barrier penetration revealed benefits 2 over non-spatially resolved analytical methods. The multiplex nature of MSI analysis was shown to mitigate residual blood contamination in brain tissue sections giving greater differentiation of poorly BBB permeable drugs. Development of quantitative LESA and DESI-MSI methods were used in conjunction with tissue mimetics to show that qMSI is a reliable way of generating in-tissue concentration data. qMSI results compared favourably with ‘gold standard’ LC-MS approaches. Finally, MALDI-qMSI was shown to be capable of generating region-specific concentration data of endogenous metabolites in heterogeneous tumour tissues. This culminated in drug project selection of a tumour model with a less heterogeneous lactate distribution, less intra-tumour lactate variability and a better platform to discriminate lactate modulation in drug dosed animals versus control in efficacy studies. The research presented in this thesis has shown that the MSI methodology developed can be successfully applied to pharmaceutical R&D. The validated protocols can be employed earlier in the development timeline allowing researchers time to evaluate and react to any data produced. Furthermore, MSI has been shown to be applicable in pharmacokinetic, pharmacodynamic and toxicity studies, offering spatially enhanced results that complement the data generated using existing analytical techniques and hence can make a contribution to safer, more efficacious medicines being brought to patients.