The Hippo pathway drives the cellular response to hydrostatic pressure.

Cells need to rapidly and precisely react to multiple mechanical and chemical stimuli in order to ensure precise context-dependent responses. This requires dynamic cellular signalling events that ensure homeostasis and plasticity when needed. A less well-understood process is cellular response to elevated interstitial fluid pressure, where the cell senses and responds to changes in extracellular hydrostatic pressure. Here, using quantitative label-free digital holographic imaging, combined with genome editing, biochemical assays and confocal imaging, we analyse the temporal cellular response to hydrostatic pressure. Upon elevated cyclic hydrostatic pressure, the cell responds by rapid, dramatic and reversible changes in cellular volume. We show that YAP and TAZ, the co-transcriptional regulators of the Hippo signalling pathway, control cell volume and that cells without YAP and TAZ have lower plasma membrane tension. We present direct evidence that YAP/TAZ drive the cellular response to hydrostatic pressure, a process that is at least partly mediated via clathrin-dependent endocytosis. Additionally, upon elevated oscillating hydrostatic pressure, YAP/TAZ are activated and induce TEAD-mediated transcription and expression of cellular components involved in dynamic regulation of cell volume and extracellular matrix. This cellular response confers a feedback loop that allows the cell to robustly respond to changes in interstitial fluid pressure.

Control compounds for preclinical drug-induced liver injury assessment: Consensus-driven systematic review by the ProEuroDILI network.

BACKGROUND & AIMS: Idiosyncratic drug-induced liver injury (DILI) is a complex and unpredictable event caused by drugs, and herbal or dietary supplements. Early identification of human hepatotoxicity at preclinical stages remains a major challenge, in which the selection of validated in vitro systems and test drugs has a significant impact. In this systematic review, we analyzed the compounds used in hepatotoxicity assays and established a list of DILI-positive and -negative control drugs for validation of in vitro models of DILI, supported by literature and clinical evidence and endorsed by an expert committee from the COST Action ProEuroDILI Network (CA17112). METHODS: Following 2020 PRISMA guidelines, original research articles focusing on DILI which used in vitro human models and performed at least one hepatotoxicity assay with positive and negative control compounds, were included. Bias of the studies was assessed by a modified 'Toxicological Data Reliability Assessment Tool'. RESULTS: A total of 51 studies (out of 2,936) met the inclusion criteria, with 30 categorized as reliable without restrictions. Although there was a broad consensus on positive compounds, the selection of negative compounds lacked clarity. 2D monoculture, short exposure times and cytotoxicity endpoints were the most tested, although there was no consensus on drug concentrations. CONCLUSIONS: Extensive analysis highlighted the lack of agreement on control compounds for in vitro DILI assessment. Following comprehensive in vitro and clinical data analysis together with input from the expert committee, an evidence-based consensus-driven list of 10 positive and negative control drugs for validation of in vitro models of DILI is proposed. IMPACT AND IMPLICATIONS: Prediction of human toxicity early in the drug development process remains a major challenge, necessitating the development of more physiologically relevant liver models and careful selection of drug-induced liver injury (DILI)-positive and -negative control drugs to better predict the risk of DILI associated with new drug candidates. Thus, this systematic study has crucial implications for standardizing the validation of new in vitro models of DILI. By establishing a consensus-driven list of positive and negative control drugs, the study provides a scientifically justified framework for enhancing the consistency of preclinical testing, thereby addressing a significant challenge in early hepatotoxicity identification. Practically, these findings can guide researchers in evaluating safety profiles of new drugs, refining in vitro models, and informing regulatory agencies on potential improvements to regulatory guidelines, ensuring a more systematic and efficient approach to drug safety assessment.

Advanced preclinical models for evaluation of drug-induced liver injury - consensus statement by the European Drug-Induced Liver Injury Network [PRO-EURO-DILI-NET].

Drug-induced liver injury (DILI) is a major cause of acute liver failure (ALF) and one of the leading indications for liver transplantation in Western societies. Given the wide use of both prescribed and over the counter drugs, DILI has become a major health issue for which there is a pressing need to find novel and effective therapies. Although significant progress has been made in understanding the molecular mechanisms underlying DILI, our incomplete knowledge of its pathogenesis and inability to predict DILI is largely due to both discordance between human and animal DILI in preclinical drug development and a lack of models that faithfully recapitulate complex pathophysiological features of human DILI. This is exemplified by the hepatotoxicity of acetaminophen (APAP) overdose, a major cause of ALF because of its extensive worldwide use as an analgesic. Despite intensive efforts utilising current animal and in vitro models, the mechanisms involved in the hepatotoxicity of APAP are still not fully understood. In this expert Consensus Statement, which is endorsed by the European Drug-Induced Liver Injury Network, we aim to facilitate and outline clinically impactful discoveries by detailing the requirements for more realistic human-based systems to assess hepatotoxicity and guide future drug safety testing. We present novel insights and discuss major players in APAP pathophysiology, and describe emerging in vitro and in vivo pre-clinical models, as well as advanced imaging and in silico technologies, which may improve prediction of clinical outcomes of DILI.

Blur resolved OCT: full-range interferometric synthetic aperture microscopy through dispersion encoding.

We present a computational method for full-range interferometric synthetic aperture microscopy (ISAM) under dispersion encoding. With this, one can effectively double the depth range of optical coherence tomography (OCT), whilst dramatically enhancing the spatial resolution away from the focal plane. To this end, we propose a model-based iterative reconstruction (MBIR) method, where ISAM is directly considered in an optimization approach, and we make the discovery that sparsity promoting regularization effectively recovers the full-range signal. Within this work, we adopt an optimal nonuniform discrete fast Fourier transform (NUFFT) implementation of ISAM, which is both fast and numerically stable throughout iterations. We validate our method with several complex samples, scanned with a commercial SD-OCT system with no hardware modification. With this, we both demonstrate full-range ISAM imaging and significantly outperform combinations of existing methods.

Blue-light induced breakdown of barrier function on human retinal epithelial cells is mediated by PKC-ζ over-activation and oxidative stress.

We aimed to study the time course decrease of human retinal pigment epithelium (RPE) barrier function when exposed to blue light. To this end, we cultured ARPE-19 cells on Electrical Cell-substrate Impedance Sensing (ECIS) multi-well arrays. Using an ad hoc light emitting diode (LED) array illumination system together with a set of neutral density filters and a 3-dimensional (3D) printed filter holder, cells were exposed to a gradient of irradiances of blue-light with a measured peak at 468 nm. The electrical resistance between 4 kHz and 64 kHz was recorded during the exposure. Blue light exposure induced a dose-dependent decrease in the resistances at 4 kHz, however the time course resistance at 64 kHz did not show any decrease before t = 52 h. Quantification of the barrier function using mathematical model integrated in the ECIS software showed that blue-light exposure induced a dose-dependent decrease in the barrier function associated with tight junction formation (P < 0.05). This was confirmed by the immunostaining of the tight-junction associated structural protein, Zonula occludens-1 (ZO-1). The detection of reactive oxygen species by carboxy-H2DCFDA confirmed that the blue light induced dose-dependent decrease in the barrier function is mediated by oxidative stress. On a separate experiment, blue-light exposed ARPE-19 cells were treated with 100 nM Protein Kinase C zeta (PKC-ζ) pseudo substrate inhibitor to identify underlying pathway for blue-light induced damage on the barrier function. The treatment with 100 nM PKC-ζ pseudo substrate inhibitor induced faster recovery of the barrier function compared to no treatment. Altogether our results document that blue LED light exposure decreased RPE barrier function in-vitro in a dose-dependent manner, before any cell death occurred. This damage induced by blue-light on tight junctions is mediated by oxidative stress through PKC-ζ activation. The quantification of the healing effect observed by inhibition of PKC-ζ might lead to development of high throughput wound healing assays through ECIS in the future.

Electrical impedance tomography for real-time and label-free cellular viability assays of 3D tumour spheroids.

There is currently a need to culture cells in 3D to better mimic the behaviour of cells growing in the natural environment. In parallel, this calls for novel technologies to assess cell growth in 3D cell culture. In this study, we demonstrated both in silico and in vitro that cell viability inside large cell spheroids could be monitored in real time and label-free with electrical impedance tomography (EIT). Simulations using a single shell model and the effective media approximation (EMA) method were performed to prove the performance of EIT on spheroid imaging and viability monitoring. Then in vitro experiments were conducted to measure in real time a loss of cell viability in MCF-7 breast cancer spheroids when exposed to Triton X-100 and validate with conventional biochemical assays. It is shown that EIT has a spatial resolution of 1.14% and it could monitor the cell mortality over 20% of a spheroid under laboratory noise level. The reconstructed conductivity images for cell mortality induced by the chemical are clear and match the result in the cellular metabolic viability assay. Furthermore, the image reconstruction speed in the experiment was less than 0.3 seconds. Taken together, the results show the potential of EIT for non-destructive real-time and label-free cellular assays in the miniature sensor, providing physiological information in the applications of 3D drug screening and tissue engineering.

Cellular micromotion monitored by long-range surface plasmon resonance with optical fluctuation analysis.

Long-range surface plasmon resonance (LRSPR) is a powerful biosensing technology due to a substantially larger probing depth into the medium and sensitivity, compared with conventional SPR. We demonstrate here that LRSPR can provide sensitive noninvasive measurement of the dynamic fluctuation of adherent cells, often referred to as the cellular micromotion. Proof of concept was achieved using confluent layers of 3T3 fibroblast cells and MDA-MB-231 cancer cells. The slope of the power spectral density (PSD) of the optical fluctuations was calculated to determine the micromotion index, and significant differences were measured between live and fixed cell layers. Furthermore, the performances of LRSPR and conventional surface plasmon resonance (cSPR) were compared with respect to micromotion monitoring. Our study showed that the micromotion index of cells measured by LRSPR sensors was higher than when measured with cSPR, suggesting a higher sensitivity of LRSPR to the micromotion of cells. To investigate further this finding, simulations were conducted to establish the relative sensitivities of LRSPR and cSPR to membrane fluctuations. Increased signal intensity was predicted for LRSPR in comparison to cSPR, suggesting that membrane fluctuations play a significant role in the optical micromotion measured in LRSPR. Analogous to cellular micromotion measured using impedance techniques, LRSPR micromotion has the potential to provide important biological information on the metabolic activity and viability of adherent cells.

Real-time label-free monitoring of adipose-derived stem cell differentiation with electric cell-substrate impedance sensing.

Real-time monitoring of stem cells (SCs) differentiation will be critical to scale-up SC technologies, while label-free techniques will be desirable to quality-control SCs without precluding their therapeutic potential. We cultured adipose-derived stem cells (ADSCs) on top of multielectrode arrays and measured variations in the complex impedance Z* throughout induction of ADSCs toward osteoblasts and adipocytes. Z* was measured up to 17 d, every 180 s, over a 62.5-64 kHz frequency range with an ECIS Z instrument. We found that osteogenesis and adipogenesis were characterized by distinct Z* time-courses. Significant differences were found (P = 0.007) as soon as 12 h post induction. An increase in the barrier resistance (Rb) up to 1.7 ohm·cm(2) was associated with early osteo-induction, whereas Rb peaked at 0.63 ohm·cm(2) for adipo-induced cells before falling to zero at t = 129 h. Dissimilarities in Z* throughout early induction (<24 h) were essentially attributed to variations in the cell-substrate parameter α. Four days after induction, cell membrane capacitance (Cm) of osteo-induced cells (Cm = 1.72 ± 0.10 µF/cm(2)) was significantly different from that of adipo-induced cells (Cm = 2.25 ± 0.27 µF/cm(2)), indicating that Cm could be used as an early marker of differentiation. Finally, we demonstrated long-term monitoring and measured a shift in the complex plane in the middle frequency range (1 kHz to 8 kHz) between early (t = 100 h) and late induction (t = 380 h). This study demonstrated that the osteoblast and adipocyte lineages have distinct dielectric properties and that such differences can be used to perform real-time label-free quantitative monitoring of adult stem cell differentiation with impedance sensing.

UVR and RPE - The Good, the Bad and the degenerate Macula.

Ultraviolet Radiation (UVR) has a well-established causative influence within the aetiology of conditions of the skin and the anterior segment of the eye. However, a grounded assessment of the role of UVR within conditions of the retina has been hampered by a historical lack of quantitative, and spectrally resolved, assessment of how UVR impacts upon the retina in terms congruent with contemporary theories of ageing. In this review, we sought to summarise the key findings of research investigating the connection between UVR exposure in retinal cytopathology while identifying necessary avenues for future research which can deliver a deeper understanding of UVR's place within the retinal risk landscape.

Non-invasive methods of monitoring Fe3O4 magnetic nanoparticle toxicity in human liver HepaRG cells using impedance biosensing and Coherent anti-Stokes Raman spectroscopic (CARS) microscopy.

Functionalized nanoparticles have been developed for use in nanomedicines for treating life threatening diseases including various cancers. To ensure safe use of these new nanoscale reagents, various assays for biocompatibility or cytotoxicity in vitro using cell lines often serve as preliminary assessments prior to in vivo animal testing. However, many of these assays were designed for soluble, colourless materials and may not be suitable for coloured, non-transparent nanoparticles. Moreover, cell lines are not always representative of mammalian organs in vivo. In this work, we use non-invasive impedance sensing methods with organotypic human liver HepaRG cells as a model to test the toxicity of PEG-Fe3O4 magnetic nanoparticles. We also use Coherent anti-Stokes Raman Spectroscopic (CARS) microscopy to monitor the formation of lipid droplets as a parameter to the adverse effect on the HepaRG cell model. The results were also compared with two commercial testing kits (PrestoBlue and ATP) for cytotoxicity. The results suggested that the HepaRG cell model can be a more realistic model than commercial cell lines while use of impedance monitoring of Fe3O4 nanoparticles circumventing the uncertainties due to colour assays. These methods can play important roles for scientists driving towards the 3Rs principle - Replacement, Reduction and Refinement.

MMV-Net: A Multiple Measurement Vector Network for Multifrequency Electrical Impedance Tomography.

Multifrequency electrical impedance tomography (mfEIT) is an emerging biomedical imaging modality to reveal frequency-dependent conductivity distributions in biomedical applications. Conventional model-based image reconstruction methods suffer from low spatial resolution, unconstrained frequency correlation, and high computational cost. Deep learning has been extensively applied in solving the EIT inverse problem in biomedical and industrial process imaging. However, most existing learning-based approaches deal with the single-frequency setup, which is inefficient and ineffective when extended to the multifrequency setup. This article presents a multiple measurement vector (MMV) model-based learning algorithm named MMV-Net to solve the mfEIT image reconstruction problem. MMV-Net considers the correlations between mfEIT images and unfolds the update steps of the Alternating Direction Method of Multipliers for the MMV problem (MMV-ADMM). The nonlinear shrinkage operator associated with the weighted l2,1 regularization term of MMV-ADMM is generalized in MMV-Net with a cascade of a Spatial Self-Attention module and a Convolutional Long Short-Term Memory (ConvLSTM) module to better capture intrafrequency and interfrequency dependencies. The proposed MMV-Net was validated on our Edinburgh mfEIT Dataset and a series of comprehensive experiments. The results show superior image quality, convergence performance, noise robustness, and computational efficiency against the conventional MMV-ADMM and the state-of-the-art deep learning methods.

Dual-Modal Image Reconstruction for Electrical Impedance Tomography With Overlapping Group Lasso and Laplacian Regularization.

OBJECTIVE: Electrical Impedance Tomography (EIT) is a promising biomedical imaging modality, yet EIT image reconstruction remains an open challenge due to its severe ill-posedness. High-quality EIT image reconstruction algorithms are desired. METHODS: This paper reports a segmentation-free dual-modal EIT image reconstruction algorithm that uses Overlapping Group Lasso and Laplacian (OGLL) regularization. An overlapping group lasso penalty is constructed based on conductivity change properties and encodes the imaging targets' structural information obtained from an auxiliary imaging modality that provides structural images of the sensing region. We introduce Laplacian regularization to alleviate the artifacts caused by group overlapping. RESULTS: The performance of OGLL is evaluated and compared with single-modal and dual-modal image reconstruction algorithms using simulation and real-world data. Quantitative metrics and visualized images confirm the superiority of the proposed method in terms of structure preservation, background artifact (BA) suppression, and conductivity contrast differentiation. CONCLUSION: This work proves the effectiveness of OGLL in improving EIT image quality. SIGNIFICANCE: This study demonstrates that EIT has the potential to be adopted in quantitative tissue analysis by using such dual-modal imaging approaches.

Debiased ambient vibrations optical coherence elastography to profile cell, organoid and tissue mechanical properties.

The role of the mechanical environment in defining tissue function, development and growth has been shown to be fundamental. Assessment of the changes in stiffness of tissue matrices at multiple scales has relied mostly on invasive and often specialist equipment such as AFM or mechanical testing devices poorly suited to the cell culture workflow.In this paper, we have developed a unbiased passive optical coherence elastography method, exploiting ambient vibrations in the sample that enables real-time noninvasive quantitative profiling of cells and tissues. We demonstrate a robust method that decouples optical scattering and mechanical properties by actively compensating for scattering associated noise bias and reducing variance. The efficiency for the method to retrieve ground truth is validated in silico and in vitro, and exemplified for key applications such as time course mechanical profiling of bone and cartilage spheroids, tissue engineering cancer models, tissue repair models and single cell. Our method is readily implementable with any commercial optical coherence tomography system without any hardware modifications, and thus offers a breakthrough in on-line tissue mechanical assessment of spatial mechanical properties for organoids, soft tissues and tissue engineering.

Impedance-Optical Dual-Modal Cell Culture Imaging With Learning-Based Information Fusion.

While Electrical Impedance Tomography (EIT) has found many biomedicine applications, better image quality is needed to provide quantitative analysis for tissue engineering and regenerative medicine. This paper reports an impedance-optical dual-modal imaging framework that primarily targets at high-quality 3D cell culture imaging and can be extended to other tissue engineering applications. The framework comprises three components, i.e., an impedance-optical dual-modal sensor, the guidance image processing algorithm, and a deep learning model named multi-scale feature cross fusion network (MSFCF-Net) for information fusion. The MSFCF-Net has two inputs, i.e., the EIT measurement and a binary mask image generated by the guidance image processing algorithm, whose input is an RGB microscopic image. The network then effectively fuses the information from the two different imaging modalities and generates the final conductivity image. We assess the performance of the proposed dual-modal framework by numerical simulation and MCF-7 cell imaging experiments. The results show that the proposed method could improve the image quality notably, indicating that impedance-optical joint imaging has the potential to reveal the structural and functional information of tissue-level targets simultaneously.

Quantitative action spectroscopy reveals ARPE19 sensitivity to ultraviolet radiation at 350 nm and 380 nm.

The role of ultraviolet radiation (UVR) exposure in the aetiology of retinal degeneration has been debated for decades with epidemiological evidence failing to find a clear consensus for or against it playing a role. A key reason for this is a lack of foundational research into the response of living retinal tissue to UVR in regard to modern ageing-specific parameters of tissue function. We therefore explored the response of cultured retinal pigmented epithelium (RPE), the loss of which heralds advanced visual decline, to specific wavelengths of UVR across the UV-B and UV-A bands found in natural sunlight. Using a bespoke in vitro UVR exposure apparatus coupled with bandpass filters we exposed the immortalised RPE cell line, ARPE-19, to 10 nm bands of UVR between 290 and 405 nm. Physical cell dynamics were assessed during exposure in cells cultured upon specialist electrode culture plates which allow for continuous, non-invasive electrostatic interrogation of key cell parameters during exposure such as monolayer coverage and tight-junction integrity. UVR exposures were also utilised to quantify wavelength-specific effects using a rapid cell viability assay and a phenotypic profiling assay which was leveraged to simultaneously quantify intracellular reactive oxygen species (ROS), nuclear morphology, mitochondrial stress, epithelial integrity and cell viability as part of a phenotypic profiling approach to quantifying the effects of UVR. Electrical impedance assessment revealed unforeseen detrimental effects of UV-A, beginning at 350 nm, alongside previously demonstrated UV-B impacts. Cell viability analysis also highlighted increased effects at 350 nm as well as 380 nm. Effects at 350 nm were further substantiated by high content image analysis which highlighted increased mitochondrial dysfunction and oxidative stress. We conclude that ARPE-19 cells exhibit a previously uncharacterised sensitivity to UV-A radiation, specifically at 350 nm and somewhat less at 380 nm. If upheld in vivo, such sensitivity will have impacts upon geoepidemiological risk scoring of macular sensitivity.

Optical Cellular Micromotion: A New Paradigm to Measure Tumor Cells Invasion within Gels Mimicking the 3D Tumor Environments.

Measuring tumor cell invasiveness through 3D tissues, particularly at the single-cell level, can provide important mechanistic understanding and assist in identifying therapeutic targets of tumor invasion. However, current experimental approaches, including standard in vitro invasion assays, have limited physiological relevance and offer insufficient insight into the vast heterogeneity in tumor cell migration through tissues. To address these issues, here the concept of optical cellular micromotion is reported on, where digital holographic microscopy is used to map the optical nano- to submicrometer thickness fluctuations within single-cells. These fluctuations are driven by the dynamic movement of subcellular structures including the cytoskeleton and inherently associated with the biological processes involved in cell invasion within tissues. It is experimentally demonstrated that the optical cellular micromotion correlates with tumor cells motility and invasiveness both at the population and single-cell levels. In addition, the optical cellular micromotion significantly reduced upon treatment with migrastatic drugs that inhibit tumor cell invasion. These results demonstrate that micromotion measurements can rapidly and non-invasively determine the invasive behavior of single tumor cells within tissues, yielding a new and powerful tool to assess the efficacy of approaches targeting tumor cell invasiveness.

Combined impedance spectroscopy and Fourier domain optical coherence tomography to monitor cells in three-dimensional structures.

OBJECTIVES: To assess non-invasively and in real time the three- dimensional organization of cells within porous matrices by combining Fourier Domain Optical Coherence Tomography (FDOCT) and Impedance Spectroscopy (IS). MATERIALS AND METHODS: Broadband interferences resulting from the recombination of in-depth light scattering events within the sample and light from a reference arm are measured as a modulation of the spectrum generated by a superluminescent laser diode (lambdao = 930nm, FWHM 90nm). Fourier transform allows in-depth localization of the scatterers, and the 3D microstructure of the sample is reconstructed by raster scanning. Simultaneously impedance spectroscopy is performed with a dielectric probe connected to an impedance analyzer to gather additional cellular information, and synchronized with FDOCT measurements. RESULTS: A combined IS-FDOCT system allowing an axial resolution of 5 micrometer in tissues and impedance measurements over the range 20MHz-1GHz has been developed. Alginate matrices have been characterized in terms of microstructure and impedance. Matrices seeded with adipose-derived stem cells have been monitored without the use of labeling agent. CONCLUSIONS: We have developed a multimodality system that will be instrumental to non-invasively monitor changes in total cell volume fraction and infer cell-specific dielectric properties in 3D structure.

Doppler optical coherence tomography imaging of local fluid flow and shear stress within microporous scaffolds.

Establishing a relationship between perfusion rate and fluid shear stress in a 3D cell culture environment is an ongoing and challenging task faced by tissue engineers. We explore Doppler optical coherence tomography (DOCT) as a potential imaging tool for in situ monitoring of local fluid flow profiles inside porous chitosan scaffolds. From the measured fluid flow profiles, the fluid shear stresses are evaluated. We examine the localized fluid flow and shear stress within low- and high-porosity chitosan scaffolds, which are subjected to a constant input flow rate of 0.5 ml min(-1). The DOCT results show that the behavior of the fluid flow and shear stress in micropores is strongly dependent on the micropore interconnectivity, porosity, and size of pores within the scaffold. For low-porosity and high-porosity chitosan scaffolds examined, the measured local fluid flow and shear stress varied from micropore to micropore, with a mean shear stress of 0.49+/-0.3 dyn cm(-2) and 0.38+/-0.2 dyn cm(-2), respectively. In addition, we show that the scaffold's porosity and interconnectivity can be quantified by combining analyses of the 3D structural and flow images obtained from DOCT.

Combining stem cell-derived hepatocytes with impedance sensing to better predict human drug toxicity.

Background: The liver plays a central role in human drug metabolism. To model drug metabolism, the major cell type of the liver, the hepatocyte, is commonly used. Hepatocytes can be derived from human and animal sources, including pluripotent stem cells. Cell-based models have shown promise in modeling human drug exposure. The assays used in those studies are normally 'snap-shot' in nature, and do not provide the complete picture of human drug exposure. Research design and methods: In this study, we employ stem cell-derived hepatocytes and impedance sensing to model human drug toxicity. This impedance-based stem cell assay reports hepatotoxicity in real time after treatment with compounds provided by industry. Results: Using electric cell-substrate impedance Sensing (ECIS), we were able to accurately measure drug toxicity post-drug exposure in real time and more quickly than gold standard biochemical assays. Conclusions: ECIS is robust and non-destructive methodology capable of monitoring human drug exposure with superior performance to current gold standard 'snapshot' assays. We believe that the methodology presented within this article could prove valuable in the quest to better predict off-target effects of drugs in humans.