General Framework to Quantitatively Predict Pharmacokinetic Induction Drug-Drug Interactions Using In Vitro Data.

INTRODUCTION: Metabolic inducers can expose people with polypharmacy to adverse health outcomes. A limited fraction of potential drug-drug interactions (DDIs) have been or can ethically be studied in clinical trials, leaving the vast majority unexplored. In the present study, an algorithm has been developed to predict the induction DDI magnitude, integrating data related to drug-metabolising enzymes. METHODS: The area under the curve ratio (AUCratio) resulting from the DDI with a victim drug in the presence and absence of an inducer (rifampicin, rifabutin, efavirenz, or carbamazepine) was predicted from various in vitro parameters and then correlated with the clinical AUCratio (N = 319). In vitro data including fraction unbound in plasma, substrate specificity and induction potential for cytochrome P450s, phase II enzymes and uptake, and efflux transporters were integrated. To represent the interaction potential, the in vitro metabolic metric (IVMM) was generated by combining the fraction of substrate metabolised by each hepatic enzyme of interest with the corresponding in vitro fold increase in enzyme activity (E) value for the inducer. RESULTS: Two independent variables were deemed significant and included in the algorithm: IVMM and fraction unbound in plasma. The observed and predicted magnitudes of the DDIs were categorised accordingly: no induction, mild, moderate, and strong induction. DDIs were assumed to be well classified if the predictions were in the same category as the observations, or if the ratio between these two was < 1.5-fold. This algorithm correctly classified 70.5% of the DDIs. CONCLUSION: This research presents a rapid screening tool to identify the magnitude of potential DDIs utilising in vitro data which can be highly advantageous in early drug development.

Actin filaments form a size-dependent diffusion barrier around centrosomes.

The centrosome, a non-membranous organelle, constrains various soluble molecules locally to execute its functions. As the centrosome is surrounded by various dense components, we hypothesized that it may be bordered by a putative diffusion barrier. After quantitatively measuring the trapping kinetics of soluble proteins of varying size at centrosomes by a chemically inducible diffusion trapping assay, we find that centrosomes are highly accessible to soluble molecules with a Stokes radius of less than 5.8 nm, whereas larger molecules rarely reach centrosomes, indicating the existence of a size-dependent diffusion barrier at centrosomes. The permeability of this barrier is tightly regulated by branched actin filaments outside of centrosomes and it decreases during anaphase when branched actin temporally increases. The actin-based diffusion barrier gates microtubule nucleation by interfering with γ-tubulin ring complex recruitment. We propose that actin filaments spatiotemporally constrain protein complexes at centrosomes in a size-dependent manner.

Evaluation of drug-drug interaction between rilpivirine and rifapentine using PBPK modelling.

Tuberculosis remains the leading cause of death among people living with HIV. Rifapentine is increasingly used to treat active disease or prevent reactivation, in both cases given either as weekly or daily therapy. However, rifapentine is an inducer of CYP3A4, potentially interacting with antiretrovirals like rilpivirine. This in silico study investigates the drug-drug interaction (DDI) magnitude between daily oral rilpivirine 25 mg with either daily 600 mg or weekly 900 mg rifapentine. A physiologically based pharmacokinetic (PBPK) model was built in Simbiology (Matlab R2018a) to simulate the drug-drug interaction. The simulated PK parameters from the PBPK model were verified against reported clinical data for rilpivirine and rifapentine separately, daily rifapentine with midazolam, and weekly rifapentine with doravirine. The simulations of concomitant administration of rifapentine with rilpivirine at steady-state lead to a maximum decrease on AUC0-24 and Ctrough by 83% and 92% on day 5 for the daily rifapentine regimen and 68% and 92% for the weekly regimen on day 3. In the weekly regimen, prior to the following dose, AUC0-24 and Ctrough were still reduced by 47% and 53%. In both simulations, the induction effect ceased 2 weeks after the interruption of rifapentine's treatment. A daily double dose of rilpivirine after initiating rifapentine 900 mg weekly was simulated but failed to compensate the drug-drug interaction. The drug-drug interaction model suggested a significant decrease on rilpivirine exposure which is unlikely to be corrected by dose increment, thus coadministration should be avoided.

Multiscale modelling of drug transport and metabolism in liver spheroids.

In early preclinical drug development, potential candidates are tested in the laboratory using isolated cells. These in vitro experiments traditionally involve cells cultured in a two-dimensional monolayer environment. However, cells cultured in three-dimensional spheroid systems have been shown to more closely resemble the functionality and morphology of cells in vivo. While the increasing usage of hepatic spheroid cultures allows for more relevant experimentation in a more realistic biological environment, the underlying physical processes of drug transport, uptake and metabolism contributing to the spatial distribution of drugs in these spheroids remain poorly understood. The development of a multiscale mathematical modelling framework describing the spatio-temporal dynamics of drugs in multicellular environments enables mechanistic insight into the behaviour of these systems. Here, our analysis of cell membrane permeation and porosity throughout the spheroid reveals the impact of these properties on drug penetration, with maximal disparity between zonal metabolism rates occurring for drugs of intermediate lipophilicity. Our research shows how mathematical models can be used to simulate the activity and transport of drugs in hepatic spheroids and in principle any organoid, with the ultimate aim of better informing experimentalists on how to regulate dosing and culture conditions to more effectively optimize drug delivery.

Innovative organotypic in vitro models for safety assessment: aligning with regulatory requirements and understanding models of the heart, skin, and liver as paradigms.

The development of improved, innovative models for the detection of toxicity of drugs, chemicals, or chemicals in cosmetics is crucial to efficiently bring new products safely to market in a cost-effective and timely manner. In addition, improvement in models to detect toxicity may reduce the incidence of unexpected post-marketing toxicity and reduce or eliminate the need for animal testing. The safety of novel products of the pharmaceutical, chemical, or cosmetics industry must be assured; therefore, toxicological properties need to be assessed. Accepted methods for gathering the information required by law for approval of substances are often animal methods. To reduce, refine, and replace animal testing, innovative organotypic in vitro models have emerged. Such models appear at different levels of complexity ranging from simpler, self-organized three-dimensional (3D) cell cultures up to more advanced scaffold-based co-cultures consisting of multiple cell types. This review provides an overview of recent developments in the field of toxicity testing with in vitro models for three major organ types: heart, skin, and liver. This review also examines regulatory aspects of such models in Europe and the UK, and summarizes best practices to facilitate the acceptance and appropriate use of advanced in vitro models.

Modeling the dynamics of hypoxia inducible factor-1α (HIF-1α) within single cells and 3D cell culture systems.

HIF (hypoxia inducible factor) is an oxygen-regulated transcription factor that mediates the intracellular response to hypoxia in human cells. There is increasing evidence that cell signaling pathways encode temporal information, and thus cell fate may be determined by the dynamics of protein levels. We have developed a mathematical model to describe the transient dynamics of the HIF-1α protein measured in single cells subjected to hypoxic shock. The essential characteristics of these data are modeled with a system of differential equations describing the feedback inhibition between HIF-1α and prolyl hydroxylases (PHD) oxygen sensors. Heterogeneity in the single-cell data is accounted through parameter variation in the model. We previously identified the PHD2 isoform as the main PHD sensor responsible for controlling the HIF-1α transient response, and make here testable predictions regarding HIF-1α dynamics subject to repetitive hypoxic pulses. The model is further developed to describe the dynamics of HIF-1α in cells cultured as 3D spheroids, with oxygen dynamics parameterized using experimental measurements of oxygen within spheroids. We show that the dynamics of HIF-1α and transcriptional targets of HIF-1α display a non-monotone response to the oxygen dynamics. Specifically we demonstrate that the dynamic transient behavior of HIF-1α results in differential dynamics in transcriptional targets.

Tight control of hypoxia-inducible factor-α transient dynamics is essential for cell survival in hypoxia.

Intracellular signaling involving hypoxia-inducible factor (HIF) controls the adaptive responses to hypoxia. There is a growing body of evidence demonstrating that intracellular signals encode temporal information. Thus, the dynamics of protein levels, as well as protein quantity and/or localization, impacts on cell fate. We hypothesized that such temporal encoding has a role in HIF signaling and cell fate decisions triggered by hypoxic conditions. Using live cell imaging in a controlled oxygen environment, we observed transient 3-h pulses of HIF-1α and -2α expression under continuous hypoxia. We postulated that the well described prolyl hydroxylase (PHD) oxygen sensors and HIF negative feedback regulators could be the origin of the pulsatile HIF dynamics. We used iterative mathematical modeling and experimental analysis to scrutinize which parameter of the PHD feedback could control HIF timing and we probed for the functional redundancy between the three main PHD proteins. We identified PHD2 as the main PHD responsible for HIF peak duration. We then demonstrated that this has important consequences, because the transient nature of the HIF pulse prevents cell death by avoiding transcription of p53-dependent pro-apoptotic genes. We have further shown the importance of considering HIF dynamics for coupling mathematical models by using a described HIF-p53 mathematical model. Our results indicate that the tight control of HIF transient dynamics has important functional consequences on the cross-talk with key signaling pathways controlling cell survival, which is likely to impact on HIF targeting strategies for hypoxia-associated diseases such as tumor progression and ischemia.

Transport of fibroblast growth factor 2 in the pericellular matrix is controlled by the spatial distribution of its binding sites in heparan sulfate.

The heparan sulfate (HS) chains of proteoglycans are a key regulatory component of the extracellular matrices of animal cells, including the pericellular matrix around the plasma membrane. In these matrices they regulate transport, gradient formation, and effector functions of over 400 proteins central to cell communication. HS from different matrices differs in its selectivity for its protein partners. However, there has been no direct test of how HS in the matrix regulates the transport of its partner proteins. We address this issue by single molecule imaging and tracking in fibroblast pericellular matrix of fibroblast growth factor 2 (FGF2), stoichiometrically labelled with small gold nanoparticles. Transmission electron microscopy and photothermal heterodyne imaging (PHI) show that the spatial distribution of the HS-binding sites for FGF2 in the pericellular matrix is heterogeneous over length scales ranging from 22 nm to several µm. Tracking of individual FGF2 by PHI in the pericellular matrix of living cells demonstrates that they undergo five distinct types of motion. They spend much of their time in confined motion (∼110 nm diameter), but they are not trapped and can escape by simple diffusion, which may be slow, fast, or directed. These substantial translocations (µm) cover distances far greater than the length of a single HS chain. Similar molecular motion persists in fixed cells, where the movement of membrane PGs is impeded. We conclude that FGF2 moves within the pericellular matrix by translocating from one HS-binding site to another. The binding sites on HS chains form non-random, heterogeneous networks. These promote FGF2 confinement or substantial translocation depending on their spatial organisation. We propose that this spatial organisation, coupled to the relative selectivity and the availability of HS-binding sites, determines the transport of FGF2 in matrices. Similar mechanisms are likely to underpin the movement of many other HS-binding effectors.

Diffusion about the mean drift location in a biased random walk.

Random walks are used to model movement in a wide variety of contexts: from the movement of cells undergoing chemotaxis to the migration of animals. In a two-dimensional biased random walk, the diffusion about the mean drift position is entirely dependent on the moments of the angular distribution used to determine the movement direction at each step. Here we consider biased random walks using several different angular distributions and derive expressions for the diffusion coefficients in each direction based on either a fixed or variable movement speed, and we use these to generate a probability density function for the long-time spatial distribution. We demonstrate how diffusion is typically anisotropic around the mean drift position and illustrate these theoretical results using computer simulations. We relate these results to earlier studies of swimming microorganisms and explain how the results can be generalized to other types of animal movement.