Nuclear magnetic resonance spectroscopy (NMR) is a valuable analytical tool with applications in a vast array of research fields from chemistry and biology to medicine and beyond. NMR is renowned for its straightforward data interpretation and quantitative properties, making it attractive for pharmacokinetic applications, where drug metabolism pathways, concentrations, and kinetics need to be evaluated. However, pharmacologically active compounds and their metabolites in biofluids often appear in minute concentrations, well below the detection limit of NMR. Herein, we demonstrate how parahydrogen hyperpolarization overcomes this sensitivity barrier, allowing us to detect mid-nanomolar concentrations of a drug and a drug metabolite in a biofluid matrix. The performance of the method is demonstrated by monitoring nicotine and cotinine urinary elimination, reflected by their concentrations in urine during the onset and withdrawal from nicotine consumption. An NMR limit of detection of 0.1 μM and a limit of quantitation of 0.7 μM is achieved in a practical pharmacokinetics scenario where precise quantitative and qualitative analysis is desired.
Parahydrogen hyperpolarization has been shown to enhance NMR sensitivity in urine analysis by several orders of magnitude if urine samples are prepared by solid phase extraction (SPE). We present a...
Parahydrogen hyperpolarization has emerged as a promising tool for sensitivity-enhanced NMR metabolomics. It allows resolution and quantification of NMR signals of certain classes of low-abundance metabolites that would otherwise be undetectable. Applications have been implemented in pharmacokinetics and doping drug detection, demonstrating the versatility of the technique. Yet, in order for the method to be adopted by the analytical community, certain limitations have to be understood and overcome. One such question is NMR signal assignment. At present, the only reliable way to establish the identity of an analyte that gives rise to certain parahydrogen hyperpolarized NMR signals is internal standard addition, which can be laborious. Herein we show that analogously to regular NMR metabolomics, generating libraries of hyperpolarized analyte signals is a viable way to address this limitation. We present hyperpolarized spectral data of adenosines and give an early example of identifying them from a urine sample with the small library. Doing so, we verify the detectability of a class of diagnostically valuable metabolites: adenosine and its derivatives, some of which are cancer biomarkers, and some are central to cellular energy management (e.g., ATP).
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