Collaborative work with Jerome Charmet and Holosensor Medical Technology Ltd.

Immunoaffinity-based liquid biopsies of circulating tumour cells (CTCs) hold great promise for cancer management, but typically suffer from low throughput, relative complexity and post-processing limitations. Here we address these issues simultaneously by decoupling and independently optimising the nano-, micro- and macro-scales of a CTC enrichment device that is both simple to fabricate and operate. Our device achieved an 80% positive match in the identification of HER2+ breast cancer (n=26) compared to clinical standard FISH on solid biopsy. The results suggest that our approach, which overcomes major limitations previously associated with affinity-based liquid biopsies, could provide a versatile tool to improve cancer management.

Denise Türk from Thorsten Lehr's group at the University of Saarbrücken, Germany, led this work on PBPK modeling of biomarkers important for predicting drug-drug interactions mediated by kidney transporters. Obviously this is modulated by the circadian clock to some extend.

Drug-drug interactions (DDI) can lead to severe and unexpected side effects of medication because uptake, metabolism or excretion kinetics are significantly altered. For example, drug excretion in the kidney might be hampered because the relevant transporters are inhibited by a co-medication that is in the system at the same time. Thus, DDI studies are an important part of clinical investigations to determine the safety profile of novel and marketed drugs. However, testing multiple drugs in many different clinical scenarios is time-consuming and expensive. A possible improvement could be to study endogenous biomarkers that might predict DDI and facilitate better designed studies. Here, physiologically based pharmacokinetic (PBPK) modelling can help to characterise the behaviour of such biomarkers and establish the key components determining the kinetics.  

Here, we developed PBPK models of the endogenous organic cation transporter (OCT) 2 and multidrug and toxin extrusion protein (MATE) 1 substrates creatinine and N1-methylnicotinamide (NMN). These performed well, i.e., aligned with the available clinical data and even took food and diurnal regulation into account. Then, the models were coupled with the previously built and evaluated models for the OCT2 and MATE1 inhibitors trimethoprim, pyrimethamine and cimetidine for DDI predictions. These models allowed us to predict previously unappreciated inhibition of NMN synthesis by trimethoprim that improved the fit to clinical data.

Thus, these whole-body PBPK models seem well suited to identify knowledge gaps and, ultimately, to facilitate investigations of renal transporter mediated DDIs during drug development.