Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans.

Physiologically based kinetic (PBK) modelling offers a mechanistic basis for predicting the pharmaco-/toxicokinetics of compounds and thereby provides critical information for integrating toxicity and exposure data to replace animal testing with in vitro or in silico methods. However, traditional PBK modelling depends on animal and human data, which limits its usefulness for non-animal methods. To address this limitation, high-throughput PBK modelling aims to rely exclusively on in vitro and in silico data for model generation. Here, we evaluate a variety of in silico tools and different strategies to parameterise PBK models with input values from various sources in a high-throughput manner. We gather 2000 + publicly available human in vivo concentration-time profiles of 200 + compounds (IV and oral administration), as well as in silico, in vitro and in vivo determined compound-specific parameters required for the PBK modelling of these compounds. Then, we systematically evaluate all possible PBK model parametrisation strategies in PK-Sim and quantify their prediction accuracy against the collected in vivo concentration-time profiles. Our results show that even simple, generic high-throughput PBK modelling can provide accurate predictions of the pharmacokinetics of most compounds (87% of Cmax and 84% of AUC within tenfold). Nevertheless, we also observe major differences in prediction accuracies between the different parameterisation strategies, as well as between different compounds. Finally, we outline a strategy for high-throughput PBK modelling that relies exclusively on freely available tools. Our findings contribute to a more robust understanding of the reliability of high-throughput PBK modelling, which is essential to establish the confidence necessary for its utilisation in Next-Generation Risk Assessment.

Blood Endotoxin Levels as Biomarker of Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-analysis.

BACKGROUND & AIMS: Growing evidence supports a role of gut-derived metabolites in nonalcoholic fatty liver disease (NAFLD), but the relation of endotoxin levels with gut permeability and NAFLD stage remains unclear. This systematic review with meta-analysis aims to provide further insights. METHODS: PubMed, Embase, and Cochrane Library were searched for studies published until January 2022 assessing blood endotoxins in patients with NAFLD. Meta-analyses and univariate/multivariate meta-regression, as well as correlation analyses, were performed for endotoxin values and potential relationships to disease stage, age, sex, parameters of systemic inflammation, and metabolic syndrome, as well as liver function and histology. RESULTS: Forty-three studies were included, of which 34 were used for meta-analyses. Blood endotoxin levels were higher in patients with simple steatosis vs liver-healthy controls (standardized mean difference, 0.86; 95% confidence interval, 0.62-1.11) as well as in patients with nonalcoholic steatohepatitis vs patients with nonalcoholic fatty liver/non-nonalcoholic steatohepatitis (standardized mean difference, 0.81; 95% confidence interval, 0.27-1.35; P = .0078). Consistently, higher endotoxin levels were observed in patients with more advanced histopathological gradings of liver steatosis and fibrosis. An increase of blood endotoxin levels was partially attributed to a body mass index rise in patients with NAFLD compared with controls. Nevertheless, significant increases of blood endotoxin levels in NAFLD retained after compensation for differences in body mass index, metabolic condition, or liver enzymes. Increases in blood endotoxin levels were associated with increases in C-reactive protein concentrations, and in most cases, paralleled a rise in markers for intestinal permeability. CONCLUSION: Our results support blood endotoxin levels as relevant diagnostic biomarker for NAFLD, both for disease detection as well as staging during disease progression, and might serve as surrogate marker of enhanced intestinal permeability in NAFLD. Registration number in Prospero: CRD42022311166.

Early prediction of decompensation (EPOD) score: Non-invasive determination of cirrhosis decompensation risk.

BACKGROUND & AIMS: Decompensation is a hallmark of disease progression in cirrhotic patients. Early detection of a phase transition from compensated cirrhosis to decompensation would enable targeted therapeutic interventions potentially extending life expectancy. This study aims to (a) identify the predictors of decompensation in a large, multicentric cohort of patients with compensated cirrhosis, (b) to build a reliable prognostic score for decompensation and (c) to evaluate the score in independent cohorts. METHODS: Decompensation was identified in electronic health records data from 6049 cirrhosis patients in the IBM Explorys database training cohort by diagnostic codes for variceal bleeding, encephalopathy, ascites, hepato-renal syndrome and/or jaundice. We identified predictors of clinical decompensation and developed a prognostic score using Cox regression analysis. The score was evaluated using the IBM Explorys database validation cohort (N = 17662), the Penn Medicine BioBank (N = 1326) and the UK Biobank (N = 317). RESULTS: The new Early Prediction of Decompensation (EPOD) score uses platelet count, albumin, and bilirubin concentration. It predicts decompensation during a 3-year follow-up in three validation cohorts with AUROCs of 0.69, 0.69 and 0.77, respectively, and outperforms the well-known MELD and Child-Pugh score in predicting decompensation. Furthermore, the EPOD score predicted the 3-year probability of decompensation. CONCLUSIONS: The EPOD score provides a prediction tool for the risk of decompensation in patients with cirrhosis that outperforms well-known cirrhosis scores. Since EPOD is based on three blood parameters, only, it provides maximal clinical feasibility at minimal costs.

Subcellular spatio-temporal intravital kinetics of aflatoxin B1 and ochratoxin A in liver and kidney.

Local accumulation of xenobiotics in human and animal tissues may cause adverse effects. Large differences in their concentrations may exist between individual cell types, often due to the expression of specific uptake and export carriers. Here we established a two-photon microscopy-based technique for spatio-temporal detection of the distribution of mycotoxins in intact kidneys and livers of anesthetized mice with subcellular resolution. The mycotoxins ochratoxin A (OTA, 10 mg/kg b.w.) and aflatoxin B1 (AFB1, 1.5 mg/kg b.w.), which both show blue auto-fluorescence, were analyzed after intravenous bolus injections. Within seconds after administration, OTA was filtered by glomeruli, and enriched in distal tubular epithelial cells (dTEC). A striking feature of AFB1 toxicokinetics was its very rapid uptake from sinusoidal blood into hepatocytes (t1/2 ~ 4 min) and excretion into bile canaliculi. Interestingly, AFB1 was enriched in the nuclei of hepatocytes with zonal differences in clearance. In the cytoplasm of pericentral hepatocytes, the half-life (t1/2~ 63 min) was much longer compared to periportal hepatocytes of the same lobules (t1/2 ~ 9 min). In addition, nuclear AFB1 from periportal hepatocytes cleared faster compared to the pericentral region. These local differences in AFB1 clearance may be due to the pericentral expression of cytochrome P450 enzymes that activate AFB1 to protein- and DNA-binding metabolites. In conclusion, the present study shows that large spatio-temporal concentration differences exist within the same tissues and its analysis may provide valuable additional information to conventional toxicokinetic studies.

Bile Microinfarcts in Cholestasis Are Initiated by Rupture of the Apical Hepatocyte Membrane and Cause Shunting of Bile to Sinusoidal Blood.

Bile duct ligation (BDL) is an experimental procedure that mimics obstructive cholestatic disease. One of the early consequences of BDL in rodents is the appearance of so-called bile infarcts that correspond to Charcot-Gombault necrosis in human cholestasis. The mechanisms causing bile infarcts and their pathophysiological relevance are unclear. Therefore, intravital two photon-based imaging of BDL mice was performed with fluorescent bile salts (BS) and non-BS organic anion analogues. Key findings were followed up by matrix-assisted laser desorption ionization imaging, clinical chemistry, immunostaining, and gene expression analyses. In the acute phase, 1-3 days after BDL, BS concentrations in bile increased and single-cell bile microinfarcts occurred in dispersed hepatocytes throughout the liver caused by the rupture of the apical hepatocyte membrane. This rupture occurred after loss of mitochondrial membrane potential, followed by entry of bile, cell death, and a "domino effect" of further death events of neighboring hepatocytes. Bile infarcts provided a trans-epithelial shunt between bile canaliculi and sinusoids by which bile constituents leaked into blood. In the chronic phase, ≥21 days after BDL, uptake of BS tracers at the sinusoidal hepatocyte membrane was reduced. This contributes to elevated concentrations of BS in blood and decreased concentrations in the biliary tract. Conclusion: Bile microinfarcts occur in the acute phase after BDL in a limited number of dispersed hepatocytes followed by larger infarcts involving neighboring hepatocytes, and they allow leakage of bile from the BS-overloaded biliary tract into blood, thereby protecting the liver from BS toxicity; in the chronic phase after BDL, reduced sinusoidal BS uptake is a dominant protective factor, and the kidney contributes to the elimination of BS until cholemic nephropathy sets in.

A workflow to build PBTK models for novel species.

Physiology-based pharmacokinetic and toxicokinetic (PBPK/TK) models allow us to simulate the concentration of xenobiotica in the plasma and different tissues of an organism. PBPK/TK models are therefore routinely used in many fields of life sciences to simulate the physiological concentration of exogenous compounds in plasma and tissues. The application of PBTK models in ecotoxicology, however, is currently hampered by the limited availability of models for focal species. Here, we present a best practice workflow that describes how to build PBTK models for novel species. To this end, we extrapolated eight previously established rabbit models for several drugs to six additional mammalian species (human, beagle, rat, monkey, mouse, and minipig). We used established PBTK models for these species to account for the species-specific physiology. The parameter sensitivity in the resulting 56 PBTK models was systematically assessed to rank the relevance of the parameters on overall model performance. Interestingly, more than 80% of the 609 considered model parameters showed a negligible sensitivity throughout all models. Only approximately 5% of all parameters had a high sensitivity in at least one of the PBTK models. This approach allowed us to rank the relevance of the various parameters on overall model performance. We used this information to formulate a best practice guideline for the efficient development of PBTK models for novel animal species. We believe that the workflow proposed in this study will significantly support the development of PBTK models for new animal species in the future.

Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations.

Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity.

A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations.

Drug-induced toxicity is a significant problem in clinical care. A key problem here is a general understanding of the molecular mechanisms accompanying the transition from desired drug effects to adverse events following administration of either therapeutic or toxic doses, in particular within a patient context. Here, a comparative toxicity analysis was performed for fifteen hepatotoxic drugs by evaluating toxic changes reflecting the transition from therapeutic drug responses to toxic reactions at the cellular level. By use of physiologically-based pharmacokinetic modeling, in vitro toxicity data were first contextualized to quantitatively describe time-resolved drug responses within a patient context. Comparatively studying toxic changes across the considered hepatotoxicants allowed the identification of subsets of drugs sharing similar perturbations on key cellular processes, functional classes of genes, and individual genes. The identified subsets of drugs were next analyzed with regard to drug-related characteristics and their physicochemical properties. Toxic changes were finally evaluated to predict both molecular biomarkers and potential drug-drug interactions. The results may facilitate the early diagnosis of adverse drug events in clinical application.

Spatio-temporal visualization of the distribution of acetaminophen as well as its metabolites and adducts in mouse livers by MALDI MSI.

Acetaminophen (APAP) is one of the most intensively studied compounds that causes hepatotoxicity in the pericentral region of the liver lobules. However, spatio-temporal information on the distribution of APAP, its metabolites and GSH adducts in the liver tissue is not yet available. Here, we addressed the question, whether APAP-GSH adducts and GSH depletion show a zonated pattern and whether the distribution of APAP and its glucuronide as well as sulfate conjugates in liver lobules are zonated. For this purpose, a matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) technique was established, where the MSI images were superimposed onto CYP2E1 immunostained tissue. A time-dependent analysis (5, 15, 30, 60, 120, 240, 480 min) after intraperitoneal administration of 300 mg/kg APAP and a dose-dependent analysis (56 up to 500 mg APAP/kg) at 30 min were performed. The results demonstrate that the MALDI MSI technique allows the assignment of compounds and their metabolites to specific lobular zones. APAP-GSH adducts and GSH depletion occurred predominantly in the CYP2E1-positive zone of the liver, although GSH also decreased in the periportal region. In contrast, the parent compound, APAP sulfate and APAP glucuronide did not show a zonated pattern and tissue concentrations showed a similar time course as the corresponding analyses were performed with blood from the portal and liver veins. In conclusion, the present study is in agreement with the concept that pericentral CYPs form NAPQI that in the same cell binds to and depletes GSH but a lower level of GSH adducts is also observed in the periportal region. The results also provide further evidence of the recently published concept of 'aggravated loss of clearance capacity' according to which also liver tissue that survives intoxication may transiently show decreased metabolic capacity.

A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim.

Proteins are an increasingly important class of drugs used as therapeutic as well as diagnostic agents. A generic physiologically based pharmacokinetic (PBPK) model was developed in order to represent at whole body level the fundamental mechanisms driving the distribution and clearance of large molecules like therapeutic proteins. The model was built as an extension of the PK-Sim model for small molecules incorporating (i) the two-pore formalism for drug extravasation from blood plasma to interstitial space, (ii) lymph flow, (iii) endosomal clearance and (iv) protection from endosomal clearance by neonatal Fc receptor (FcRn) mediated recycling as especially relevant for antibodies. For model development and evaluation, PK data was used for compounds with a wide range of solute radii. The model supports the integration of knowledge gained during all development phases of therapeutic proteins, enables translation from pre-clinical species to human and allows predictions of tissue concentration profiles which are of relevance for the analysis of on-target pharmacodynamic effects as well as off-target toxicity. The current implementation of the model replaces the generic protein PBPK model available in PK-Sim since version 4.2 and becomes part of the Open Systems Pharmacology Suite.

Model-based contextualization of in vitro toxicity data quantitatively predicts in vivo drug response in patients.

Understanding central mechanisms underlying drug-induced toxicity plays a crucial role in drug development and drug safety. However, a translation of cellular in vitro findings to an actual in vivo context remains challenging. Here, physiologically based pharmacokinetic (PBPK) modeling was used for in vivo contextualization of in vitro toxicity data (PICD) to quantitatively predict in vivo drug response over time by integrating multiple levels of biological organization. Explicitly, in vitro toxicity data at the cellular level were integrated into whole-body PBPK models at the organism level by coupling in vitro drug exposure with in vivo drug concentration-time profiles simulated in the extracellular environment within the organ. PICD was exemplarily applied on the hepatotoxicant azathioprine to quantitatively predict in vivo drug response of perturbed biological pathways and cellular processes in rats and humans. The predictive accuracy of PICD was assessed by comparing in vivo drug response predicted for rats with observed in vivo measurements. To demonstrate clinical applicability of PICD, in vivo drug responses of a critical toxicity-related pathway were predicted for eight patients following acute azathioprine overdoses. Moreover, acute liver failure after multiple dosing of azathioprine was investigated in a patient case study by use of own clinical data. Simulated pharmacokinetic profiles were therefore related to in vivo drug response predicted for genes associated with observed clinical symptoms and to clinical biomarkers measured in vivo. PICD provides a generic platform to investigate drug-induced toxicity at a patient level and thus may facilitate individualized risk assessment during drug development.

In vivo imaging of systemic transport and elimination of xenobiotics and endogenous molecules in mice.

We describe a two-photon microscopy-based method to evaluate the in vivo systemic transport of compounds. This method comprises imaging of the intact liver, kidney and intestine, the main organs responsible for uptake and elimination of xenobiotics and endogenous molecules. The image quality of the acquired movies was sufficient to distinguish subcellular structures like organelles and vesicles. Quantification of the movement of fluorescent dextran and fluorescent cholic acid derivatives in different organs and their sub-compartments over time revealed significant dynamic differences. Calculated half-lives were similar in the capillaries of all investigated organs but differed in the specific sub-compartments, such as parenchymal cells and bile canaliculi of the liver, glomeruli, proximal and distal tubules of the kidney and lymph vessels (lacteals) of the small intestine. Moreover, tools to image immune cells, which can influence transport processes in inflamed tissues, are described. This powerful approach provides new possibilities for the analysis of compound transport in multiple organs and can support physiologically based pharmacokinetic modeling, in order to obtain more precise predictions at the whole body scale.

Model-guided identification of a therapeutic strategy to reduce hyperammonemia in liver diseases.

BACKGROUND & AIMS: Recently, spatial-temporal/metabolic mathematical models have been established that allow the simulation of metabolic processes in tissues. We applied these models to decipher ammonia detoxification mechanisms in the liver. METHODS: An integrated metabolic-spatial-temporal model was used to generate hypotheses of ammonia metabolism. Predicted mechanisms were validated using time-resolved analyses of nitrogen metabolism, activity analyses, immunostaining and gene expression after induction of liver damage in mice. Moreover, blood from the portal vein, liver vein and mixed venous blood was analyzed in a time dependent manner. RESULTS: Modeling revealed an underestimation of ammonia consumption after liver damage when only the currently established mechanisms of ammonia detoxification were simulated. By iterative cycles of modeling and experiments, the reductive amidation of alpha-ketoglutarate (α-KG) via glutamate dehydrogenase (GDH) was identified as the lacking component. GDH is released from damaged hepatocytes into the blood where it consumes ammonia to generate glutamate, thereby providing systemic protection against hyperammonemia. This mechanism was exploited therapeutically in a mouse model of hyperammonemia by injecting GDH together with optimized doses of cofactors. Intravenous injection of GDH (720 U/kg), α-KG (280 mg/kg) and NADPH (180 mg/kg) reduced the elevated blood ammonia concentrations (>200 µM) to levels close to normal within only 15 min. CONCLUSION: If successfully translated to patients the GDH-based therapy might provide a less aggressive therapeutic alternative for patients with severe hyperammonemia.

A Physiologically Based Pharmacokinetic Model of Isoniazid and Its Application in Individualizing Tuberculosis Chemotherapy.

Due to its high early bactericidal activity, isoniazid (INH) plays an essential role in tuberculosis treatment. Genetic polymorphisms of N-acetyltransferase type 2 (NAT2) cause a trimodal distribution of INH pharmacokinetics in slow, intermediate, and fast acetylators. The success of INH-based chemotherapy is associated with acetylator and patient health status. Still, a standard dose recommended by the FDA is administered regardless of acetylator type or immune status, even though adverse effects occur in 5 to 33% of all patients. Slow acetylators have a higher risk of development of drug-induced toxicity, while fast acetylators and immune-deficient patients face lower treatment success rates. To mechanistically assess the trade-off between toxicity and efficacy, we developed a physiologically based pharmacokinetic (PBPK) model describing the NAT2-dependent pharmacokinetics of INH and its metabolites. We combined the PBPK model with a pharmacodynamic (PD) model of antimycobacterial drug effects in the lungs. The resulting PBPK/PD model allowed the simultaneous simulation of treatment efficacies at the site of infection and exposure to toxic metabolites in off-target organs. Subsequently, we evaluated various INH dosing regimens in NAT2-specific immunocompetent and immune-deficient virtual populations. Our results suggest the need for acetylator-specific dose adjustments for optimal treatment outcomes. A reduced dose for slow acetylators substantially lowers the exposure to toxic metabolites and thereby the risk of adverse events, while it maintains sufficient treatment efficacies. Vice versa, intermediate and fast acetylators benefit from increased INH doses and a switch to a twice-daily administration schedule. Our analysis outlines how PBPK/PD modeling may be used to design and individualize treatment regimens.

Modeling and Simulation of In Vivo Drug Effects.

The concept of a pharmacokinetics-pharmacodynamics (PK/PD) assessment of drug development candidates is well established in pharmaceutical research and development, and PK/PD modeling is common practice in all pharmaceutical companies. A recent analysis (Morgan et al., Drug Discov Today 17(9-10):419-424, 2012) revealed however that insufficient certainty in the integrity of the causal chain of fundamental pharmacological steps from drug dosing through systemic exposure, target tissue exposure, and engagement of molecular target to pharmacological response is still the major driver of failure in phase II of clinical drug development. Despite the rise of molecular biomarkers, ethical, scientific, and practical constraints very often still prevent a direct assessment of each necessary step ultimately leading to an intended drug effect or an unintended adverse reaction. Yet, incomplete investigation of the causality of drug responses is a major risk for translational assessments and the prediction of drug responses in different species or other populations. Mechanism-based modeling and simulation (M&S) offers a means to investigate complex physiological and pharmacological processes and to complement experimental data for non-accessible steps in the pharmacological causal chain. With the help of two examples, it is illustrated, what level of physiological detail, state-of-the-art models can represent, how predictive these models are and how mechanism-based approaches can be combined with empirical correlation-based concepts.

Spatio-temporal simulation of first pass drug perfusion in the liver.

The liver is the central organ for detoxification of xenobiotics in the body. In pharmacokinetic modeling, hepatic metabolization capacity is typically quantified as hepatic clearance computed as degradation in well-stirred compartments. This is an accurate mechanistic description once a quasi-equilibrium between blood and surrounding tissue is established. However, this model structure cannot be used to simulate spatio-temporal distribution during the first instants after drug injection. In this paper, we introduce a new spatially resolved model to simulate first pass perfusion of compounds within the naive liver. The model is based on vascular structures obtained from computed tomography as well as physiologically based mass transfer descriptions obtained from pharmacokinetic modeling. The physiological architecture of hepatic tissue in our model is governed by both vascular geometry and the composition of the connecting hepatic tissue. In particular, we here consider locally distributed mass flow in liver tissue instead of considering well-stirred compartments. Experimentally, the model structure corresponds to an isolated perfused liver and provides an ideal platform to address first pass effects and questions of hepatic heterogeneity. The model was evaluated for three exemplary compounds covering key aspects of perfusion, distribution and metabolization within the liver. As pathophysiological states we considered the influence of steatosis and carbon tetrachloride-induced liver necrosis on total hepatic distribution and metabolic capacity. Notably, we found that our computational predictions are in qualitative agreement with previously published experimental data. The simulation results provide an unprecedented level of detail in compound concentration profiles during first pass perfusion, both spatio-temporally in liver tissue itself and temporally in the outflowing blood. We expect our model to be the foundation of further spatially resolved models of the liver in the future.

Computational identification of natural senotherapeutic compounds that mimic dasatinib based on gene expression data.

The major risk factor for chronic disease is chronological age, and age-related chronic diseases account for the majority of deaths worldwide. Targeting senescent cells that accumulate in disease-related tissues presents a strategy to reduce disease burden and to increase healthspan. The senolytic combination of the tyrosine-kinase inhibitor dasatinib and the flavonol quercetin is frequently used in clinical trials aiming to eliminate senescent cells. Here, our goal was to computationally identify natural senotherapeutic repurposing candidates that may substitute dasatinib based on their similarity in gene expression effects. The natural senolytic piperlongumine (a compound found in long pepper), and the natural senomorphics parthenolide, phloretin and curcumin (found in various edible plants) were identified as potential substitutes of dasatinib. The gene expression changes underlying the repositioning highlight apoptosis-related genes and pathways. The four compounds, and in particular the top-runner piperlongumine, may be combined with quercetin to obtain natural formulas emulating the dasatinib + quercetin formula.

Integrating cellular metabolism into a multiscale whole-body model.

Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development.

Quantitative systems pharmacology of the eye: Tools and data for ocular QSP.

Good eyesight belongs to the most-valued attributes of health, and diseases of the eye are a significant healthcare burden. Case numbers are expected to further increase in the next decades due to an aging society. The development of drugs in ophthalmology, however, is difficult due to limited accessibility of the eye, in terms of drug administration and in terms of sampling of tissues for drug pharmacokinetics (PKs) and pharmacodynamics (PDs). Ocular quantitative systems pharmacology models provide the opportunity to describe the distribution of drugs in the eye as well as the resulting drug-response in specific segments of the eye. In particular, ocular physiologically-based PK (PBPK) models are necessary to describe drug concentration levels in different regions of the eye. Further, ocular effect models using molecular data from specific cellular systems are needed to develop dose-response correlations. We here describe the current status of PK/PBPK as well as PD models for the eyes and discuss cellular systems, data repositories, as well as animal models in ophthalmology. The application of the various concepts is highlighted for the development of new treatments for postoperative fibrosis after glaucoma surgery.