The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury

Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.

Considerations for Physiologically Based Modeling in Liver Disease: From Nonalcoholic Fatty Liver (NAFL) to Nonalcoholic Steatohepatitis (NASH)

Nonalcoholic fatty liver disease (NAFLD), representing a clinical spectrum ranging from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH), is rapidly evolving into a global pandemic. Patients with NAFLD are burdened with high rates of metabolic syndrome-related comorbidities resulting in polypharmacy. Therefore, it is crucial to gain a better understanding of NAFLD-mediated changes in drug disposition and efficacy/toxicity. Despite extensive clinical pharmacokinetic data in cirrhosis, current knowledge concerning pharmacokinetic alterations in NAFLD, particularly at different stages of disease progression, is relatively limited. In vitro-to-in vivo extrapolation coupled with physiologically based pharmacokinetic and pharmacodynamic (IVIVE-PBPK/PD) modeling offers a promising approach for optimizing pharmacologic predictions while refining and reducing clinical studies in this population. Use of IVIVE-PBPK to predict intra-organ drug concentrations at pharmacologically relevant sites of action is particularly advantageous when it can be linked to pharmacodynamic effects. Quantitative systems pharmacology/toxicology (QSP/QST) modeling can be used to translate pharmacokinetic and pharmacodynamic data from PBPK/PD models into clinically relevant predictions of drug response and toxicity. In this review, a detailed summary of NAFLD-mediated alterations in human physiology relevant to drug absorption, distribution, metabolism, and excretion (ADME) is provided. The application of literature-derived physiologic parameters and ADME-associated protein abundance data to inform virtual NAFLD population development and facilitate PBPK/PD, QSP, and QST predictions is discussed along with current limitations of these methodologies and knowledge gaps. The proposed methodologic framework offers great potential for meaningful prediction of pharmacological outcomes in patients with NAFLD and can inform both drug development and clinical practice for this population.

Investigating bile acid-mediated cholestatic drug-induced liver injury using a mechanistic model of multidrug resistance protein 3 (MDR3) inhibition

Inhibition of the canalicular phospholipid floppase multidrug resistance protein 3 (MDR3) has been implicated in cholestatic drug-induced liver injury (DILI), which is clinically characterized by disrupted bile flow and damage to the biliary epithelium. Reduction in phospholipid excretion, as a consequence of MDR3 inhibition, decreases the formation of mixed micelles consisting of bile acids and phospholipids in the bile duct, resulting in a surplus of free bile acids that can damage the bile duct epithelial cells, i.e., cholangiocytes. Cholangiocytes may compensate for biliary increases in bile acid monomers via the cholehepatic shunt pathway or bicarbonate secretion, thereby influencing viability or progression to toxicity. To address the unmet need to predict drug-induced bile duct injury in humans, DILIsym, a quantitative systems toxicology model of DILI, was extended by representing key features of the bile duct, cholangiocyte functionality, bile acid and phospholipid disposition, and cholestatic hepatotoxicity. A virtual, healthy representative subject and population (n = 285) were calibrated and validated utilizing a variety of clinical data. Sensitivity analyses were performed for 1) the cholehepatic shunt pathway, 2) biliary bicarbonate concentrations and 3) modes of MDR3 inhibition. Simulations showed that an increase in shunting may decrease the biliary bile acid burden, but raise the hepatocellular concentrations of bile acids. Elevating the biliary concentration of bicarbonate may decrease bile acid shunting, but increase bile flow rate. In contrast to competitive inhibition, simulations demonstrated that non-competitive and mixed inhibition of MDR3 had a profound impact on phospholipid efflux, elevations in the biliary bile acid-to-phospholipid ratio, cholangiocyte toxicity, and adaptation pathways. The model with its extended bile acid homeostasis representation was furthermore able to predict DILI liability for compounds with previously studied interactions with bile acid transport. The cholestatic liver injury submodel in DILIsym accounts for several processes pertinent to bile duct viability and toxicity and hence, is useful for predictions of MDR3 inhibition-mediated cholestatic DILI in humans.

Applications of Quantitative Systems Pharmacology (QSP) in Drug Development for NAFLD and NASH and Its Regulatory Application

Nonalcoholic steatohepatitis (NASH) is a widely prevalent disease, but approved pharmaceutical treatments are not available. As such, there is great activity within the pharmaceutical industry to accelerate drug development in this area and improve the quality of life and reduce mortality for NASH patients. The use of quantitative systems pharmacology (QSP) can help make this overall process more efficient. This mechanism-based mathematical modeling approach describes both the pathophysiology of a disease and how pharmacological interventions can modify pathophysiologic mechanisms. Multiple capabilities are provided by QSP modeling, including the use of model predictions to optimize clinical studies. The use of this approach has grown over the last 20 years, motivating discussions between modelers and regulators to agree upon methodologic standards. These include model transparency, documentation, and inclusion of clinical pharmacodynamic biomarkers. Several QSP models have been developed that describe NASH pathophysiology to varying extents. One specific application of NAFLDsym, a QSP model of NASH, is described in this manuscript. Simulations were performed to help understand if patient behaviors could help explain the relatively high rate of fibrosis stage reductions in placebo cohorts. Simulated food intake and body weight fluctuated periodically over time. The relatively slow turnover of liver collagen allowed persistent reductions in predicted fibrosis stage despite return to baseline for liver fat, plasma ALT, and the NAFLD activity score. Mechanistic insights such as this that have been derived from QSP models can help expedite the development of safe and effective treatments for NASH patients.

OUP accepted manuscript

Calcitonin gene-related peptide (CGRP) signaling inhibitors have shown efficacy in both the acute and preventive treatment of migraine. Telcagepant, a first-generation CGRP receptor antagonist, was effective but failed in clinical trials due to hepatotoxicity. Subsequently, although 4 next-generation CGRP receptor antagonists (rimegepant, zavegepant, atogepant, and ubrogepant) were being advanced into late-stage clinical trials, due to telcagepant’s failure, more confidence in the liver safety of these compounds was needed. DILIsym v6A, a quantitative systems toxicology (QST) model of drug-induced liver injury (DILI), was used to model all 5 compounds and thus to compare the 4 next-generation CGRP receptor antagonists to telcagepant. In vitro experiments were performed to measure the potential for each compound to inhibit bile acid transporters, produce oxidative stress, and cause mitochondrial dysfunction. Physiologically based pharmacokinetic models were produced for each compound in order to appropriately estimate liver exposure. DILIsym predicted clinical elevations of liver enzymes and bilirubin for telcagepant, correctly predicting the observed DILI liability of the first-generation compound. By contrast, DILIsym predicted that each of the 4 next-generation compounds would be significantly less likely to cause DILI than telcagepant. Subsequent clinical trials have validated these predictions for each of the 4 compounds, and all 3 of the compounds submitted to FDA to date (rimegepant, ubrogepant, and atogepant) have since been approved by the FDA with no warning for hepatotoxicity. This work demonstrates the potential for QST modeling to prospectively differentiate between hepatotoxic and nonhepatotoxic molecules within the same class.

Quantitative Systems Toxicology Analysis of In Vitro Mechanistic Assays Reveals Importance of Bile Acid Accumulation and Mitochondrial Dysfunction in TAK-875-Induced Liver Injury

TAK-875 (fasiglifam), a GPR40 agonist in development for the treatment of type 2 diabetes (T2D), was voluntarily terminated in Phase III trials due to adverse liver effects. The potential mechanisms of TAK-875 toxicity were explored by combining in vitro experiments with quantitative systems toxicology (QST) using DILIsym, a mathematical representation of drug-induced liver injury. In vitro assays revealed that bile acid transporters were inhibited by both TAK-875 and its metabolite, TAK-875-Glu. Experimental data indicated that human bile salt export pump (BSEP) inhibition by TAK-875 was mixed whereas sodium taurocholate co-transporting polypeptide (NTCP) inhibition by TAK-875 was competitive. Furthermore, experimental data demonstrated that both TAK-875 and TAK-875-Glu inhibit mitochondrial electron transport chain (ETC) enzymes. These mechanistic data were combined with a physiologically based pharmacokinetic (PBPK) model constructed within DILIsym to estimate liver exposure of TAK-875 and TAK-875-Glu. In a simulated population (SimPops) constructed to reflect T2D patients, 16/245 (6.5%) simulated individuals developed alanine aminotransferase (ALT) elevations, an incidence similar to that observed with 200 mg daily dosing in clinical trials. Determining the mode of bile acid transporter inhibition (K_i) was critical to accurate predictions. In addition, simulations conducted on a sensitive subset of individuals (SimCohorts) revealed that when either BSEP or ETC inhibition was inactive, ALT elevations were not predicted to occur, suggesting that the two mechanisms operate synergistically to produce the observed clinical response. These results demonstrate how utilizing QST methods to interpret in vitro experimental results can lead to an improved understanding of the clinically relevant mechanisms underlying drug-induced toxicity.

Quantitative systems toxicology (QST) reproduces species differences in PF-04895162 liver safety due to combined mitochondrial and bile acid toxicity

Many compounds that appear promising in preclinical species, fail in human clinical trials due to safety concerns. The FDA has strongly encouraged the application of modeling in drug development to improve product safety. This study illustrates how DILIsym, a computational representation of liver injury, was able to reproduce species differences in liver toxicity due to PF-04895162 (ICA-105665). PF-04895162, a drug in development for the treatment of epilepsy, was terminated after transaminase elevations were observed in healthy volunteers (NCT01691274). Liver safety concerns had not been raised in preclinical safety studies. DILIsym, which integrates in vitro data on mechanisms of hepatotoxicity with predicted in vivo liver exposure, reproduced clinical hepatotoxicity and the absence of hepatotoxicity observed in the rat. Simulated differences were multifactorial. Simulated liver exposure was greater in humans than rats. The simulated human hepatotoxicity was demonstrated to be due to the interaction between mitochondrial toxicity and bile acid transporter inhibition; elimination of either mechanism from the simulations abrogated injury. The bile acid contribution occurred despite the fact that the IC50 for bile salt export pump (BSEP) inhibition by PF-04895162 was higher (311 µmol/L) than that has been generally thought to contribute to hepatotoxicity. Modeling even higher PF-04895162 liver exposures than were measured in the rat safety studies aggravated mitochondrial toxicity but did not result in rat hepatotoxicity due to insufficient accumulation of cytotoxic bile acid species. This investigative study highlights the potential for combined in vitro and computational screening methods to identify latent hepatotoxic risks and paves the way for similar and prospective studies.

Using Quantitative Systems Toxicology to Investigate Observed Species Differences in CKA-Mediated Hepatotoxicity

CKA, a chemokine receptor antagonist intended for treating inflammatory conditions, produced dose-dependent hepatotoxicity in rats but advanced into the clinic where single doses of CKA up to 600 mg appeared safe in humans. Because existing toxicological platforms used during drug development are not perfectly predictive, a quantitative systems toxicology model investigated the hepatotoxic potential of CKA in humans and rats through in vitro assessments of CKA on mitochondrial respiration, oxidative stress, and bile acid transporters. DILIsym predicted that single doses of CKA caused serum ALT >3xULN in a subset of the simulated rat population, while single doses in a simulated human population did not produce serum ALT elevations. Species differences were largely attributed to differences in liver exposure, but increased sensitivity to inhibition of mitochondrial respiration in the rat also contributed. We conclude that mechanistic modeling can elucidate species differences in the hepatotoxic potential of drug candidates.

Prediction of Safety Margin and Optimization of Dosing Protocol for a Novel Antibiotic using Quantitative Systems Pharmacology Modeling

Elevations of liver enzymes have been observed in clinical trials with BAL30072, a novel antibiotic. In vitro assays have identified potential mechanisms for the observed hepatotoxicity, including electron transport chain (ETC) inhibition and reactive oxygen species (ROS) generation. DILIsym, a quantitative systems pharmacology (QSP) model of drug-induced liver injury, has been used to predict the likelihood that each mechanism explains the observed toxicity. DILIsym was also used to predict the safety margin for a novel BAL30072 dosing scheme; it was predicted to be low. DILIsym was then used to recommend potential modifications to this dosing scheme; weight-adjusted dosing and a requirement to assay plasma alanine aminotransferase (ALT) daily and stop dosing as soon as ALT increases were observed improved the predicted safety margin of BAL30072 and decreased the predicted likelihood of severe injury. This research demonstrates a potential application for QSP modeling in improving the safety profile of candidate drugs.

Mechanistic Modelling of Drug-Induced Liver Injury: Investigating the Role of Innate Immune Responses

Drug-induced liver injury (DILI) remains an adverse event of significant concern for drug development and marketed drugs, and the field would benefit from better tools to identify liver liabilities early in development and/or to mitigate potential DILI risk in otherwise promising drugs. DILIsym software takes a quantitative systems toxicology approach to represent DILI in pre-clinical species and in humans for the mechanistic investigation of liver toxicity. In addition to multiple intrinsic mechanisms of hepatocyte toxicity (ie, oxidative stress, bile acid accumulation, mitochondrial dysfunction), DILIsym includes the interaction between hepatocytes and cells of the innate immune response in the amplification of liver injury and in liver regeneration. The representation of innate immune responses, detailed here, consolidates much of the available data on the innate immune response in DILI within a single framework and affords the opportunity to systematically investigate the contribution of the innate response to DILI.

Refining Liver Safety Risk Assessment: Application of Mechanistic Modeling and Serum Biomarkers to Cimaglermin Alfa (GGF2) Clinical Trials

Cimaglermin alfa (GGF2) is a recombinant human protein growth factor in development for heart failure. Phase I trials were suspended when two cimaglermin alfa‐treated subjects experienced concomitant elevations in serum aminotransferases and total bilirubin, meeting current US Food and Drug Administration criteria for a serious liver safety signal (i.e., “Hy's Law”). We assayed mechanistic biomarkers in archived clinical trial serum samples which confirmed the hepatic origin of the aminotransferase elevations in these two subjects and identified apoptosis as the major mode of hepatocyte death. Using a mathematical model of drug‐induced liver injury (DILIsym) and a simulated population, we estimated that the maximum hepatocyte loss in these two subjects was <13%, which would not result in liver dysfunction sufficient to significantly increase serum bilirubin levels. We conclude that the two subjects should not be considered Hy's Law cases and that mechanistic biomarkers and modeling can aid in refining liver safety risk assessment in clinical trials.

Systems pharmacology modeling of drug-induced hyperbilirubinemia: Differentiating hepatotoxicity and inhibition of enzymes/transporters

Elevations in serum bilirubin during drug treatment may indicate global liver dysfunction and a high risk of liver failure. However, drugs also can increase serum bilirubin in the absence of hepatic injury by inhibiting specific enzymes/transporters. We constructed a mechanistic model of bilirubin disposition based on known functional polymorphisms in bilirubin metabolism/transport. Using physiologically based pharmacokinetic (PBPK) model-predicted drug exposure and enzyme/transporter inhibition constants determined in vitro, our model correctly predicted indinavir-mediated hyperbilirubinemia in humans and rats. Nelfinavir was predicted not to cause hyperbilirubinemia, consistent with clinical observations. We next examined a new drug candidate that caused both elevations in serum bilirubin and biochemical evidence of liver injury in rats. Simulations suggest that bilirubin elevation primarily resulted from inhibition of transporters rather than global liver dysfunction. We conclude that mechanistic modeling of bilirubin can help elucidate underlying mechanisms of drug-induced hyperbilirubinemia, and thereby distinguish benign from clinically important elevations in serum bilirubin.

The role of quantitative systems pharmacology modeling in the prediction and explanation of idiosyncratic drug-induced liver injury

Idiosyncratic drug-induced liver injury (iDILI) is a serious concern in drug development. The rarity and multifactorial nature of iDILI makes it difficult to predict and explain. Recently, human leukocyte antigen (HLA) allele associations have provided strong support for a role of an adaptive immune response in the pathogenesis of many iDILI cases; however, it is likely that an adaptive immune attack requires several preceding events. Quantitative systems pharmacology (QSP), an in silico modeling technique that leverages known physiology and the results of in vitro experiments in order to make predictions about how drugs affect biological processes, is proposed as a potentially useful tool for predicting and explaining critical events that likely precede immune-mediated iDILI, as well as the immune attack itself. DILIsym, a QSP platform for drug-induced liver injury, has demonstrated success in predicting the presence of delayed hepatocellular stress events that likely precede the iDILI cascade, and has successfully predicted hepatocellular stress likely underlying iDILI attributed to troglitazone and tolvaptan. The incorporation of a model of the adaptive immune system into DILIsym would represent and important advance. In summary, QSP methods can play a key role in the future prediction and understanding of both immune-mediated and non-immune-mediated iDILI.

Application of a Mechanistic Model to Evaluate Putative Mechanisms of Tolvaptan Drug-Induced Liver Injury and Identify Patient Susceptibility Factors

Tolvaptan is a selective vasopressin V2 receptor antagonist, approved in several countries for the treatment of hyponatremia and autosomal dominant polycystic kidney disease (ADPKD). No liver injury has been observed with tolvaptan treatment in healthy subjects and in non-ADPKD indications, but ADPKD clinical trials showed evidence of drug-induced liver injury (DILI). Although all DILI events resolved, additional monitoring in tolvaptan-treated ADPKD patients is required. In vitro assays identified alterations in bile acid disposition and inhibition of mitochondrial respiration as potential mechanisms underlying tolvaptan hepatotoxicity. This report details the application of DILIsym software to determine whether these mechanisms could account for the liver safety profile of tolvaptan observed in ADPKD clinical trials. DILIsym simulations included physiologically based pharmacokinetic estimates of hepatic exposure for tolvaptan and2 metabolites, and their effects on hepatocyte bile acid transporters and mitochondrial respiration. The frequency of predicted alanine aminotransferase (ALT) elevations, following simulated 90/30  mg split daily dosing, was 7.9% compared with clinical observations of 4.4% in ADPKD trials. Toxicity was multifactorial as inhibition of bile acid transporters and mitochondrial respiration contributed to the simulated DILI. Furthermore, simulation analysis identified both pre-treatment risk factors and on-treatment biomarkers predictive of simulated DILI. The simulations demonstrated that in vivo hepatic exposure to tolvaptan and the DM-4103 metabolite, combined with these 2 mechanisms of toxicity, were sufficient to account for the initiation of tolvaptan-mediated DILI. Identification of putative risk-factors and potential novel biomarkers provided insight for the development of mechanism-based tolvaptan risk-mitigation strategies.

Elucidating Differences in the Hepatotoxic Potential of Tolcapone and Entacapone With DILIsym(®), a Mechanistic Model of Drug-Induced Liver Injury

Tolcapone and entacapone are catechol‐O‐methyltransferase (COMT) inhibitors developed as adjunct therapies for treating Parkinson's disease. While both drugs have been shown to cause mitochondrial dysfunction and inhibition of the bile salt export protein (BSEP), liver injury has only been associated with the use of tolcapone. Here we used a multiscale, mechanistic model (DILIsym^®) to simulate the response to tolcapone and entacapone. In a simulated population (SimPops™) receiving recommended doses of tolcapone (200 mg t.i.d.), increases in serum alanine transaminase (ALT) >3× the upper limit of normal (ULN) were observed in 2.2% of the population. In contrast, no simulated patients receiving recommended doses of entacapone (200 mg 8× day) experienced serum ALT >3× ULN. Further, DILIsym^® analyses revealed patient‐specific risk factors that may contribute to tolcapone‐mediated hepatotoxicity. In summary, the simulations demonstrated that differences in mitochondrial uncoupling potency and hepatic exposure primarily account for the difference in hepatotoxic potential for tolcapone and entacapone.

Exploring BSEP inhibition-mediated toxicity with a mechanistic model of drug-induced liver injury

Inhibition of the bile salt export pump (BSEP) has been linked to incidence of drug-induced liver injury (DILI), presumably by the accumulation of toxic bile acids in the liver. We have previously constructed and validated a model of bile acid disposition within DILIsym®, a mechanistic model of DILI. In this paper, we use DILIsym® to simulate the DILI response of the hepatotoxic BSEP inhibitors bosentan and CP-724,714 and the non-hepatotoxic BSEP inhibitor telmisartan in humans in order to explore whether we can predict that hepatotoxic BSEP inhibitors can cause bile acid accumulation to reach toxic levels. We also simulate bosentan in rats in order to illuminate potential reasons behind the lack of toxicity in rats compared to the toxicity observed in humans. DILIsym® predicts that bosentan, but not telmisartan, will cause mild hepatocellular ATP decline and serum ALT elevation in a simulated population of humans. The difference in hepatotoxic potential between bosentan and telmisartan is consistent with clinical observations. However, DILIsym® underpredicts the incidence of bosentan toxicity. DILIsym® also predicts that bosentan will not cause toxicity in a simulated population of rats, and that the difference between the response to bosentan in rats and in humans is primarily due to the less toxic bile acid pool in rats. Our simulations also suggest a potential synergistic role for bile acid accumulation and mitochondrial electron transport chain (ETC) inhibition in producing the observed toxicity in CP-724,714, and suggest that CP-724,714 metabolites may also play a role in the observed toxicity. Our work also compares the impact of competitive and noncompetitive BSEP inhibition for CP-724,714 and demonstrates that noncompetitive inhibition leads to much greater bile acid accumulation and potential toxicity. Our research demonstrates the potential for mechanistic modeling to contribute to the understanding of how bile acid transport inhibitors cause DILI.

A mechanistic model of drug-induced liver injury AIDS the interpretation of elevated liver transaminase levels in a phase I clinical trial

Entolimod (CBLB502) is a Toll-like receptor 5 agonist in development as a single-dose countermeasure against total body irradiation. Efficacy can be assessed from animal studies, but the “Animal Rule” does not apply to safety assessment. Marked elevations of serum aminotransferases (exceeding 1,000 IU/l) were observed in some human subjects receiving Entolimod in a safety study, threatening its continued development. The percentage of total hepatocytes undergoing necrosis in these subjects was estimated using a mechanistic, multiscale, mathematical model (DILIsym). The simulations suggested that no subject in the safety study experienced more than a modest loss of hepatocytes (<5%), which was comparable to estimates from a study of healthy volunteers receiving treatment with heparins. The predicted hepatocyte loss with Entolimod was lower than that required to cause liver dysfunction or that is routinely excised from volunteers donating for autologous liver transplantation and did not likely represent a serious health risk.

Modeling drug- and chemical-induced hepatotoxicity with systems biology approaches

We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of “toxicity pathways” is described in the context of the 2007 US National Academies of Science report, “Toxicity testing in the 21st Century: A Vision and A Strategy.” Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity) – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular “virtual tissue” model of the liver lobule that combines molecular circuits in individual hepatocytes with cell–cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the aryl hydrocarbon receptor toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsym™) to understand drug-induced liver injury (DILI), the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

Treatment with sitagliptin or metformin does not increase body weight despite predicted reductions in urinary glucose excretion

BACKGROUND

We used a mathematical model to estimate the contribution of urinary glucose excretion (UGE) to reported changes in body weight (BW) following oral antihyperglycemic agent (AHA) therapy. This modeling approach was used to gain novel insight into the mechanisms by which oral AHA affects BW.

METHODS

Twenty-four hour glucose profiles were used to predict UGE before and after treatment with oral AHA. Model-predicted changes in BW due to reduced UGE were compared with reported changes in BW to quantify non-UGE-dependent effects (fluid retention, food intake, and energy expenditure).

RESULTS

In type 2 diabetes patients [hemoglobin A1c (HbA1c) >7.3%], the energy lost to UGE is predicted to decrease an average of 100 kcal/day for each 1% decrease in HbA1c. This effect, alone, is predicted to increase BW 1.4 kg after 6 months. Differences from this value reported for changes in BW with oral AHA therapy (+1.4 kg for pioglitazone and rosiglitazone; -0.4 kg for glyburide; -0.9 kg for sitagliptin and vildagliptin; -2.3 kg for metformin) are therefore predicted to be due to additional, non-UGE-dependent mechanisms.

CONCLUSIONS

Weight gain following thiazolidinedione therapy is predicted to result from both reduced UGE and non-UGE-dependent mechanisms. Reduced UGE alone is predicted to account for most of the weight gain reported following sulfonylurea therapy. Weight loss observed in response to metformin and weight maintenance observed in response to dipeptidyl peptidase-4 inhibitors may result from an increase in satiety, energy expenditure, or both.

Advances in the stable isotope-mass spectrometric measurement of DNA synthesis and cell proliferation

Methods for measuring rates of DNA synthesis, and thus cell proliferation, in humans had not been available until recently. We (D. C. Macallan, C. A. Fullerton, R. A. Neese, K. Haddock, S. S. Park, and M. K. Hellerstein, 1998, Proc. Natl. Acad. Sci. USA 95, 708-713) recently developed a stable isotope-mass spectrometric technique for measuring DNA synthesis by labeling the deoxyribose (dR) moiety of purine deoxyribonucleotides through the de novo nucleotide synthesis pathway. The original analytic approach had limitations, however. Here, we describe technical improvements that increase yield, stability, sensitivity, and reproducibility of the method. The purine deoxyribonucleoside, deoxyadenosine (dA), is directly isolated from hydrolysates of DNA by using an LC18 SPE column. Two derivatives were developed for analyzing the dR moiety of dA alone (without the base), an aldonitrile-triacetate derivative, and a reduced pentose-tetraacetate (PTA) derivative. The PTA derivative in particular exhibited greater stability (no degradation after several weeks), greater GC/MS signal, and much less abundance sensitivity of isotope ratios (i.e., less dependence of mass isotopomer abundances on the amount of material injected into the mass spectrometer source), compared to previous derivatives of dA. The need for complex, multidimensional abundance corrected standard curves was thereby avoided. Using the PTA derivative, dR enrichments from DNA of fully turned over cells of rodents with 2H2O enrichments in body water of 2.2-2.8% were 9.0-9.5%, and less than 1.0 microg DNA (ca. 2 x 10(5) cells) was required for reproducible analyses. In summary, these methodologic advances allow measurement of stable isotope incorporation into DNA and calculation of cell proliferation and death rates in vivo in humans and experimental animals, with fewer cells, greater reproducibility, and less labor. Many applications of this approach can be envisioned.

De novo lipogenesis, lipid kinetics, and whole-body lipid balances in humans after acute alcohol consumption

BACKGROUND

Acute alcohol intake is associated with changes in plasma lipid concentrations and whole-body lipid balances in humans. The quantitative roles of hepatic de novo lipogenesis (DNL) and plasma acetate production in these changes have not been established, however.

OBJECTIVE

We used stable-isotope mass spectrometric methods with indirect calorimetry to establish the metabolic basis of changes in whole-body lipid balances in healthy men after consumption of 24 g alcohol.

DESIGN

Eight healthy subjects were studied and DNL (by mass-isotopomer distribution analysis), lipolysis (by dilution of [1,2,3,4-(13)C(4)]palmitate and [(2)H(5)]glycerol), conversion of alcohol to plasma acetate (by incorporation from [1-(13)C(1)]ethanol), and plasma acetate flux (by dilution of [1-(13)C(1)]acetate) were measured.

RESULTS

The fractional contribution from DNL to VLDL-triacylglycerol palmitate rose after alcohol consumption from 2 +/- 1% to 30 +/- 8%; nevertheless, the absolute rate of DNL (0.8 g/6 h) represented <5% of the ingested alcohol dose; 77 +/- 13% of the alcohol cleared from plasma was converted directly to acetate entering plasma. Acetate flux increased 2.5-fold after alcohol consumption. Adipose release of nonesterified fatty acids into plasma decreased by 53% and whole-body lipid oxidation decreased by 73%.

CONCLUSIONS

We conclude that the consumption of 24 g alcohol activates the hepatic DNL pathway modestly, but acetate produced in the liver and released into plasma inhibits lipolysis, alters tissue fuel selection, and represents the major quantitative fate of ingested ethanol.

VLDL-triglyceride production after alcohol ingestion, studied using [2-13C1] glycerol

We used [2-13C1]glycerol to characterize very low density lipoprotein (VLDL)-triglyceride kinetics and intrahepatic glycerol metabolism in normal men (n = 4) after alcohol (EtOH) ingestion. [2-13C1]glycerol was infused before and after the consumption of 48 g EtOH or a placebo. Three additional subjects also received [1-13C1]acetate in addition to the [2-13C1]glycerol with EtOH treatment. Incorporation of tracer into the glycerol or fatty acid moiety of VLDL-triglyceride was measured by gas chromatography-mass spectrometry and used to calculate VLDL-triglyceride production rates. Intrahepatic triose-phosphate enrichments were also calculated based on mass isotopomer distribution analysis of plasma glucose. There was no difference in VLDL-triglyceride production rates after 48 g EtOH (11.9 +/- 3.7 mg/kg/h) or placebo (14.7 +/- 3. 3 mg/kg/h). The VLDL-triglyceride rate constants calculated by kinetic modeling using the glycerol and acetate tracers in the combined isotope infusion subjects were very closely correlated (r 2 = 0.94). The peak VLDL-glycerol enrichments after EtOH were 22.5 +/- 3.3% versus 7.6 +/- 0.8% after placebo (P < 0.001), while intrahepatic triose-phosphate enrichments were 19.8 +/- 1.3% and 13. 1 +/- 1.2% (P < 0.001), respectively. Moreover, the calculated asymptotic VLDL-glycerol enrichments (representing the hepatic alpha-glycerol phosphate enrichment) were significantly higher after EtOH than placebo. The higher ratio of VLDL-glycerol to triose-phosphate labeling after EtOH suggests a metabolic block at glycerol 3-phosphate dehydrogenase. We conclude that consumption of 48 g EtOH does not increase VLDL-triglyceride production in normal men but does cause accumulation of tracer in hepatic alpha-glycerol phosphate.

The inhibition of gluconeogenesis following alcohol in humans

Accurate quantification of gluconeogenic flux following alcohol ingestion in overnight-fasted humans has yet to be reported. [2-13C1]glycerol, [U-13C6]glucose, [1-2H1]galactose, and acetaminophen were infused in normal men before and after the consumption of 48 g alcohol or a placebo to quantify gluconeogenesis, glycogenolysis, hepatic glucose production, and intrahepatic gluconeogenic precursor availability. Gluconeogenesis decreased 45% vs. the placebo (0.56 +/- 0.05 to 0.44 +/- 0.04 mg. kg-1. min-1 vs. 0.44 +/- 0.05 to 0.63 +/- 0.09 mg. kg-1. min-1, respectively, P < 0. 05) in the 5 h after alcohol ingestion, and total gluconeogenic flux was lower after alcohol compared with placebo. Glycogenolysis fell over time after both the alcohol and placebo cocktails, from 1.46-1. 47 mg. kg-1. min-1 to 1.35 +/- 0.17 mg. kg-1. min-1 (alcohol) and 1. 26 +/- 0.20 mg. kg-1. min-1, respectively (placebo, P < 0.05 vs. baseline). Hepatic glucose output decreased 12% after alcohol consumption, from 2.03 +/- 0.21 to 1.79 +/- 0.21 mg. kg-1. min-1 (P < 0.05 vs. baseline), but did not change following the placebo. Estimated intrahepatic gluconeogenic precursor availability decreased 61% following alcohol consumption (P < 0.05 vs. baseline) but was unchanged after the placebo (P < 0.05 between treatments). We conclude from these results that gluconeogenesis is inhibited after alcohol consumption in overnight-fasted men, with a somewhat larger decrease in availability of gluconeogenic precursors but a smaller effect on glucose production and no effect on plasma glucose concentrations. Thus inhibition of flux into the gluconeogenic precursor pool is compensated by changes in glycogenolysis, the fate of triose-phosphates, and peripheral tissue utilization of plasma glucose.