AZD8233 antisense oligonucleotide targeting PCSK9 does not prolong QT interval.

AIMS: AZD8233 is a proprotein convertase subtilisin/kexin type 9 (PCSK9) antisense oligonucleotide under development for treatment of hypercholesterolaemia. A prespecified concentration-QT analysis was performed based on data from a single ascending dose study that was prospectively designed to act as a TQT study substitute. METHODS: Subcutaneous single doses ranging from 4 to 120 mg were evaluated in 73 adult healthy male subjects. Time-matched 12-lead digital ECG and plasma concentrations (n = 15) were measured at baseline and up to 48 hours after dose in each subject. The analysis was performed using a linear mixed effect model, where change from baseline QTc (ΔQTc) was a dependent variable and time-matched AZD8233 concentration was an independent variable. RESULTS: The high clinical exposure scenario was defined as 1.7-fold the expected Cmax following an assumed therapeutic dose of 60 mg, which corresponds to AZD8233 plasma concentration of 1.39 µg/mL. Estimated placebo-corrected and baseline-adjusted QTcF interval (ΔΔQTcF) at this concentration was -2.2 ms (90% CI: -4.11, -0.28). Furthermore, the upper 90% ΔΔQTcF confidence interval was estimated to be below 10 ms at all observed concentrations. CONCLUSION: As the effect on ΔΔQTcF is below the threshold for regulatory concern (10 ms), it can be concluded that AZD8233 does not induce QTcF prolongation at the high clinical exposure scenario.

Novel NIR-Phosphorescent Ir(III) Complexes: Synthesis, Characterization and Their Exploration as Lifetime-Based O2 Sensors in Living Cells.

A series of [Ir(N^C)2(N^N)]+ NIR-emitting orthometalated complexes (1-7) has been prepared and structurally characterized using elemental analysis, mass-spectrometry, and NMR spectroscopy. The complexes display intense phosphorescence with vibrationally structured emission bands exhibiting the maxima in the range 713-722 nm. The DFT and TD DFT calculations showed that the photophysical characteristics of these complexes are largely determined by the properties of the metalating N^C ligands, with their major contribution into formation of the lowest S1 and T1 excited states responsible for low energy absorption and emission, respectively. Emission lifetimes of 1-7 in degassed methanol solution vary from 1.76 to 5.39 µs and show strong quenching with molecular oxygen to provide an order of magnitude lifetime reduction in aerated solution. The photophysics of two complexes (1 and 7) were studied in model physiological media containing fetal bovine serum (FBS) and Dulbecco's Modified Eagle Medium (DMEM) to give linear Stern-Volmer calibrations with substantially lower oxygen-quenching constants compared to those obtained in methanol solution. These observations were interpreted in terms of the sensors' interaction with albumin, which is an abundant component of FBS and cell media. The studied complexes displayed acceptable cytotoxicity and preferential localization, either in mitochondria (1) or in lysosomes (7) of the CHO-K1 cell line. The results of the phosphorescence lifetime imaging (PLIM) experiments demonstrated considerable variations of the sensors' lifetimes under normoxia and hypoxia conditions and indicated their applicability for semi-quantitative measurements of oxygen concentration in living cells. The complexes' emission in the NIR domain and the excitation spectrum, extending down to ca. 600 nm, also showed that they are promising for use in in vivo studies.

Polymeric Nanoparticles with Embedded Eu(III) Complexes as Molecular Probes for Temperature Sensing.

Three novel luminescent Eu(III) complexes, Eu1-Eu3, have been synthesized and characterized with CHN analysis, mass-spectrometry and 1H NMR spectroscopy. The complexes display strong emission in dichloromethane solution upon excitation at 405 and 800 nm with a quantum yield from 18.3 to 31.6%, excited-state lifetimes in the range of 243-1016 ms at 20 °C, and lifetime temperature sensitivity of 0.9%/K (Eu1), 1.9%/K (Eu2), and 1.7%/K (Eu3). The chromophores were embedded into biocompatible latex nanoparticles (NPs_Eu1-NPs_Eu3) that prevented emission quenching and kept the photophysical characteristics of emitters unchanged with the highest temperature sensitivity of 1.3%/K (NPs_Eu2). For this probe cytotoxicity, internalization dynamics and localization in CHO-K1 cells were studied together with lifetime vs. temperature calibration in aqueous solution, phosphate buffer, and in a mixture of growth media and fetal bovine serum. The obtained data were then averaged to give the calibration curve, which was further used for temperature estimation in biological samples. The probe was stable in physiological media and displayed good reproducibility in cycling experiments between 20 and 40 °C. PLIM experiments with thermostated CHO-K1 cells incubated with NPs_Eu2 indicated that the probe could be used for temperature estimation in cells including the assessment of temperature variations upon chemical shock (sample treatment with mitochondrial uncoupling reagent).

A model-based approach to investigating the relationship between glucose-insulin dynamics and dapagliflozin treatment effect in patients with type 2 diabetes.

AIMS: To develop a quantitative systems pharmacology model to describe the effect of dapagliflozin (a sodium-glucose co-transporter-2 [SGLT2] inhibitor) on glucose-insulin dynamics in type 2 diabetes mellitus (T2DM) patients, and to identify key determinants of treatment-mediated glycated haemoglobin (HbA1c) reduction. MATERIALS AND METHODS: Glycaemic control during dapagliflozin treatment was mechanistically characterized by integrating components representing dapagliflozin pharmacokinetics (PK), glucose-insulin homeostasis, renal glucose reabsorption, and HbA1c formation. The model was developed using PK variables, glucose, plasma insulin, and urinary glucose excretion (UGE) from a phase IIa dapagliflozin trial in patients with T2DM (NCT00162305). The model was used to predict dapagliflozin-induced HbA1c reduction; model predictions were compared to actual data from phase III trials (NCT00528879, NCT00683878, NCT00680745 and NCT00673231). RESULTS: The integrated glucose-insulin-dapagliflozin model successfully described plasma glucose and insulin levels, as well as UGE in response to oral glucose tolerance tests and meal intake. HbA1c reduction was also well predicted. The results show that dapagliflozin-mediated glycaemic control is anticorrelated to steady-state insulin concentration and insulin sensitivity. CONCLUSIONS: The developed model framework is the first to integrate SGLT2 inhibitor mechanism of action with both short-term glucose-insulin dynamics and long-term glucose control (HbA1c). The results suggest that dapagliflozin treatment is beneficial in patients with inadequate glycaemic control from insulin alone and this benefit increases as insulin control diminishes.

Possible Steps of the Carboxylation of Ribulose-1,5-biphosphate from Intermediates: 2,3-Enediol versus 1,2-Enol.

Ribulose 1,5-bisphosphate (RuBP) undergoes enolization to initiate fixation of atmospheric carbon dioxide in the plant carbon cycle. The known model assumes the binding of RuBP to the Rubisco active site with the subsequent formation of 2,3-enediol (2,3,4-trihydroxypent-2-ene-1,5-diyl diphosphate). In the present study, it is assumed that 1,2-enol (2,3,4-trihydroxypent-1-ene-1,5-diyl diphosphate) can be formed in the enolization step to initiate the carboxylation reaction. We have used Kohn-Sham density functional theory on WB97X-D3/Def2-TZVP levels to compare the reaction barriers in the two ways. We considered the pathways of carboxylation of 1/2-ene (mono/di)ol via the C1 and C2 carbons without taking into account the binding of RuBP to the magnesium ion. Calculations of Gibbs free energies confirm the equal probability of the formation of 2,3-enediol and 1,2-enol. Quantum-chemical modeling of enolization and carboxylation reactions supports the important role of the bridging water molecule and diphosphate groups, which provide proton transfer and lower reaction barriers. The results show that carbon dioxide fixation can occur without a magnesium ion, and binding with C1 can have a lower barrier (~12 kcal/mol) than with C2 (~23 kcal/mol).

Biocompatible Ir(III) Complexes as Oxygen Sensors for Phosphorescence Lifetime Imaging.

Synthesis of biocompatible near infrared phosphorescent complexes and their application in bioimaging as triplet oxygen sensors in live systems are still challenging areas of organometallic chemistry. We have designed and synthetized four novel iridium [Ir(N^C)2(N^N)]+ complexes (N^C-benzothienyl-phenanthridine based cyclometalated ligand; N^N-pyridin-phenanthroimidazol diimine chelate), decorated with oligo(ethylene glycol) groups to impart these emitters' solubility in aqueous media, biocompatibility, and to shield them from interaction with bio-environment. These substances were fully characterized using NMR spectroscopy and ESI mass-spectrometry. The complexes exhibited excitation close to the biological "window of transparency", NIR emission at 730 nm, and quantum yields up to 12% in water. The compounds with higher degree of the chromophore shielding possess low toxicity, bleaching stability, absence of sensitivity to variations of pH, serum, and complex concentrations. The properties of these probes as oxygen sensors for biological systems have been studied by using phosphorescence lifetime imaging experiments in different cell cultures. The results showed essential lifetime response onto variations in oxygen concentration (2.0-2.3 µs under normoxia and 2.8-3.0 µs under hypoxia conditions) in complete agreement with the calibration curves obtained "in cuvette". The data obtained indicate that these emitters can be used as semi-quantitative oxygen sensors in biological systems.

Comparative quantitative systems pharmacology modeling of anti-PCSK9 therapeutic modalities in hypercholesterolemia.

Since the discovery of proprotein convertase subtilisin/kexin type 9 (PCSK9) as an attractive target in the treatment of hypercholesterolemia, multiple anti-PCSK9 therapeutic modalities have been pursued in drug development. The objective of this research is to set the stage for the quantitative benchmarking of two anti-PCSK9 pharmacological modality classes, monoclonal antibodies (mAbs) and small interfering RNA (siRNA). To this end, we developed an integrative mathematical model of lipoprotein homeostasis describing the dynamic interplay between PCSK9, LDL-cholesterol (LDL-C), VLDL-cholesterol, HDL-cholesterol (HDL-C), apoB, lipoprotein a [Lp(a)], and triglycerides (TGs). We demonstrate that LDL-C decreased proportionally to PCSK9 reduction for both mAb and siRNA modalities. At marketed doses, however, treatment with mAbs resulted in an additional ∼20% LDL-C reduction compared with siRNA. We further used the model as an evaluation tool and determined that no quantitative differences were observed in HDL-C, Lp(a), TG, or apoB responses, suggesting that the disruption of PCSK9 synthesis would provide no additional effects on lipoprotein-related biomarkers in the patient segment investigated. Predictive model simulations further indicate that siRNA therapies may reach reductions in LDL-C levels comparable to those achieved with mAbs if the current threshold of 80% PCSK9 inhibition via siRNA could be overcome.

Urinary glucose excretion after dapagliflozin treatment: An exposure-response modelling comparison between Japanese and non-Japanese patients diagnosed with type 1 diabetes mellitus.

AIMS: To assess the dapagliflozin exposure-response relationship in Japanese and non-Japanese patients with type 1 diabetes mellitus (T1DM) and investigate if a dose adjustment is required in Japanese patients. MATERIALS AND METHODS: Data from two clinical studies were used to develop a non-linear mixed effects model describing the relationship between dapagliflozin exposure (area under the concentration curve) and response (24-hour urinary glucose excretion [UGE]) in Japanese and non-Japanese patients with T1DM. The effects of patient-level characteristics (covariates; identified using a stepwise procedure) on response was also assessed. Simulations were performed using median-normalized covariate values. RESULTS: Data from 84 patients were included. Average self-monitored blood glucose (SMBG) at day 7, change from baseline in total insulin dose at day 7, and baseline estimated glomerular filtration rate (eGFR) all had a significant effect on 24-hours UGE, with SMBG being the most influential. Dapagliflozin systemic exposure for matching doses and baseline eGFR was similar between Japanese and non-Japanese patients; however, higher SMBG and a greater reduction in total insulin dose was observed in the Japanese population. When the significant covariates were included, the model fit the data well for both populations, and accurately predicted exposure-response in the Japanese and non-Japanese populations, in agreement with the observed data. CONCLUSIONS: There was no difference in dapagliflozin exposure-response in Japanese and non-Japanese patients with T1DM once differences in renal function, glycaemic control and insulin dose reductions between studies were considered. Therefore, no dose adjustment is recommended in Japanese patients with T1DM.

Comparison of the urinary glucose excretion contributions of SGLT2 and SGLT1: A quantitative systems pharmacology analysis in healthy individuals and patients with type 2 diabetes treated with SGLT2 inhibitors.

AIM: To develop a quantitative drug-disease systems model to investigate the paradox that sodium-glucose co-transporter (SGLT)2 is responsible for >80% of proximal tubule glucose reabsorption, yet SGLT2 inhibitor treatment results in only 30% to 50% less reabsorption in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: A physiologically based four-compartment model of renal glucose filtration, reabsorption and excretion via SGLT1 and SGLT2 was developed as a system of ordinary differential equations using R/IQRtools. SGLT2 inhibitor pharmacokinetics and pharmacodynamics were estimated from published concentration-time profiles in plasma and urine and from urinary glucose excretion (UGE) in healthy people and people with T2DM. RESULTS: The final model showed that higher renal glucose reabsorption in people with T2DM versus healthy people was associated with 54% and 28% greater transporter capacity for SGLT1 and SGLT2, respectively. Additionally, the analysis showed that UGE is highly dependent on mean plasma glucose and estimated glomerular filtration rate (eGFR) and that their consideration is critical for interpreting clinical UGE findings. CONCLUSIONS: Quantitative drug-disease system modelling revealed mechanistic differences in renal glucose reabsorption and UGE between healthy people and those with T2DM, and clearly showed that SGLT2 inhibition significantly increased glucose available to SGLT1 downstream in the tubule. Importantly, we found that the findings of lower than expected UGE with SGLT2 inhibition are explained by the shift to SGLT1, which recovered additional glucose (~30% of total).

Synthesis of benzannelated sultams by intramolecular Pd-catalyzed arylation of tertiary sulfonamides.

A new and efficient approach to five- and six-membered benzannelated sultams by intramolecular C-arylation of tertiary 1-(methoxycarbonyl)methanesulfonamides under palladium catalysis is described. In case of the α-toluenesulfonamide derivative, an unexpected formation of a 2,3-diarylindole was observed under the same conditions.

A tutorial for model-based evaluation and translation of cardiovascular safety in preclinical trials.

Assessment of drug-induced effects on the cardiovascular (CV) system remains a critical component of the drug discovery process enabling refinement of the therapeutic index. Predicting potential drug-related unintended CV effects in the preclinical stage is necessary for first-in-human dose selection and preclusion of adverse CV effects in the clinical stage. According to the current guidelines for small molecules, nonclinical CV safety assessment conducted via telemetry analyses should be included in the safety pharmacology core battery studies. However, the manual for quantitative evaluation of the CV safety signals in animals is available only for electrocardiogram parameters (i.e., QT interval assessment), not for hemodynamic parameters (i.e., heart rate, blood pressure, etc.). Various model-based approaches, including empirical pharmacokinetic-toxicodynamic analyses and systems pharmacology modeling could be used in the framework of telemetry data evaluation. In this tutorial, we provide a comprehensive workflow for the analysis of nonclinical CV safety on hemodynamic parameters with a sequential approach, highlight the challenges associated with the data, and propose respective solutions, complemented with a reproducible example. The work is aimed at helping researchers conduct model-based analyses of the CV safety in animals with subsequent translation of the effect to humans seamlessly and efficiently.

Mathematical modeling in autoimmune diseases: from theory to clinical application.

The research & development (R&D) of novel therapeutic agents for the treatment of autoimmune diseases is challenged by highly complex pathogenesis and multiple etiologies of these conditions. The number of targeted therapies available on the market is limited, whereas the prevalence of autoimmune conditions in the global population continues to rise. Mathematical modeling of biological systems is an essential tool which may be applied in support of decision-making across R&D drug programs to improve the probability of success in the development of novel medicines. Over the past decades, multiple models of autoimmune diseases have been developed. Models differ in the spectra of quantitative data used in their development and mathematical methods, as well as in the level of "mechanistic granularity" chosen to describe the underlying biology. Yet, all models strive towards the same goal: to quantitatively describe various aspects of the immune response. The aim of this review was to conduct a systematic review and analysis of mathematical models of autoimmune diseases focused on the mechanistic description of the immune system, to consolidate existing quantitative knowledge on autoimmune processes, and to outline potential directions of interest for future model-based analyses. Following a systematic literature review, 38 models describing the onset, progression, and/or the effect of treatment in 13 systemic and organ-specific autoimmune conditions were identified, most models developed for inflammatory bowel disease, multiple sclerosis, and lupus (5 models each). ≥70% of the models were developed as nonlinear systems of ordinary differential equations, others - as partial differential equations, integro-differential equations, Boolean networks, or probabilistic models. Despite covering a relatively wide range of diseases, most models described the same components of the immune system, such as T-cell response, cytokine influence, or the involvement of macrophages in autoimmune processes. All models were thoroughly analyzed with an emphasis on assumptions, limitations, and their potential applications in the development of novel medicines.

Model-Based Assessment of the Reference Values of CAVI in Healthy Russian Population and Benchmarking With CAVI0.

BACKGROUND: Cardio-ankle vascular index (CAVI) and its modified version (CAVI0) are promising non-invasive markers of arterial stiffness, extensively evaluated primarily in the Japanese population. In this work, we performed a model-based analysis of the association between different population characteristics and CAVI or CAVI0 values in healthy Russian subjects and propose a tool for calculating the range of reference values for both types of indices. METHODS: The analysis was based on the data from 742 healthy volunteers (mean age 30.4 years; 73.45% men) collected from a multicenter observational study. Basic statistical analysis [analysis of variance, Pearson's correlation (r), significance tests] and multivariable linear regression were performed in R software (version 4.0.2). Tested covariates included age, sex, BMI, blood pressure, and heart rate (HR). RESULTS: No statistically significant difference between healthy men and women were observed for CAVI and CAVI0. In contrast, both indices were positively associated with age (r = 0.49 and r = 0.43, P < 0.001), however, with no clear distinction between subjects of 20-30 and 30-40 years old. Heart rate and blood pressure were also identified as statistically significant predictors following multiple linear regression modeling, but with marginal clinical significance. Finally, the algorithm for the calculation of the expected ranges of CAVI in healthy population was proposed, for a given age category, HR and pulse pressure (PP) values. CONCLUSIONS: We have evaluated the quantitative association between various population characteristics, CAVI, and CAVI0 values and established a method for estimating the subject-level reference CAVI and CAVI0 measurements.

Effectiveness of dapagliflozin as an insulin adjunct in type 1 diabetes: a semi-mechanistic exposure-response model.

Introduction: Dapagliflozin-induced improvement of glycemic control in patients with inadequately controlled type 1 diabetes (T1D) is complicated by the delicate balance between blood glucose and exogenous insulin. In this work, we developed a semi-mechanistic population exposure-response model using pooled patient-level data to characterize the joint effect of dapagliflozin and insulin on average daily glucose concentrations and glycated hemoglobin (HbA1c) levels in patients with T1D. Methods: A non-linear mixed-effects model was developed in Monolix (Lixoft, France) and R software (R Project, www.r-project.org) using pooled patient-level data from phase 2 and phase 3 trials (NCT01498185, NCT02460978, NCT02268214). Results: Because of the apparent lack of association between bolus insulin dose and glucose concentrations measured by continuous glucose monitoring the model was able to capture the quantitative link between basal, but not bolus, insulin dose and plasma glucose. Even so, this association remained flat, with a 50% decrease in the basal insulin dose from pretreatment level, resulting in ∼5% increase in glucose exposure. Therefore, dapagliflozin efficacy was not significantly affected by the insulin dose adjustment, with 24-week HbA1c reduction on 10-mg dapagliflozin treatment changing from -0.5 [95% CI: -0.55, -0.45] to -0.42 [95%CI: -0.48, -0.36] after adjustment. At the same time, the analysis revealed ∼2-fold steeper slope of glucose-HbA1c relationship in dapagliflozin-treated patients vs. control group, suggesting the presence of additional dapagliflozin treatment-related benefits, not explained by the dapagliflozin-mediated ∼4% increase in plasma hemoglobin levels. Finally, the efficacy of 5 and 10-mg doses, represented by the mean HbA1c reduction at week 24 of dapagliflozin treatment, was shown to be notably greater than the 1- and 2.5-mg doses. Discussion: This research is an attempt to deconvolute and reconstruct dapagliflozin-HbA1c dose-response relationship in T1D by accounting for the drug's action on both daily insulin dose and plasma glucose on a subject-level. While the model is able to adequately capture the observed data, it also revealed that the variability in CGM is poorly approximated by the variability in insulin dose alone. Furthermore, the slope of CGM/HbA1c relationship may differ depending on the population and treatment scenarios. As such, a deeper dive into the physiological mechanisms is required to better quantify the intricate network of glycemic response under dapagliflozin treatment.

Optimization of the MACE endpoint composition to increase power in studies of lipid-lowering therapies-a model-based meta-analysis.

Aims: To develop a model-informed methodology for the optimization of the Major Adverse Cardiac Events (MACE) composite endpoint, based on a model-based meta-analysis across anti-hypercholesterolemia trials of statin and anti-PCSK9 drugs. Methods and results: Mixed-effects meta-regression modeling of stand-alone MACE outcomes was performed, with therapy type, population demographics, baseline and change over time in lipid biomarkers as predictors. Randomized clinical trials up to June 28, 2022, of either statins or anti-PCSK9 therapies were identified through a systematic review process in PubMed and ClinicalTrials.gov databases. In total, 54 studies (270,471 patients) were collected, reporting 15 different single cardiovascular events. Treatment-mediated decrease in low density lipoprotein cholesterol, baseline levels of remnant and high-density lipoprotein cholesterol as well as non-lipid population characteristics and type of therapy were identified as significant covariates for 10 of the 15 outcomes. The required sample size per composite 3- and 4-point MACE endpoint was calculated based on the estimated treatment effects in a population and frequencies of the incorporated events in the control group, trial duration, and uncertainty in model parameters. Conclusion: A quantitative tool was developed and used to benchmark different compositions of 3- and 4-point MACE for statins and anti-PCSK9 therapies, based on the minimum population size required to achieve statistical significance in relative risk reduction, following meta-regression modeling of the single MACE components. The approach we developed may be applied towards the optimization of the design of future trials in dyslipidemia disorders as well as in other therapeutic areas.

A mechanistic modeling platform of SGLT2 inhibition: Implications for type 1 diabetes.

Type 1 diabetes mellitus (T1DM) is an autoimmune disease characterized by abnormally high blood glucose concentrations due to dysfunction of the insulin-producing beta-cells in the pancreas. Dapagliflozin, an inhibitor of renal glucose reabsorption, has the potential to improve often suboptimal glycemic control in patients with T1DM through insulin-independent mechanisms and to partially mitigate the adverse effects associated with long-term insulin administration. In this work, we have adapted a systems pharmacology model of type 2 diabetes mellitus to describe the T1DM condition and characterize the effect of dapagliflozin on short- and long-term glycemic markers under various treatment scenarios. The developed platform serves as a quantitative tool for the in silico evaluation of the insulin-glucose-dapagliflozin crosstalk, optimization of the treatment regimens, and it can be further expanded to include additional therapies or other aspects of the disease.

Biocompatible Phosphorescent O2 Sensors Based on Ir(III) Complexes for In Vivo Hypoxia Imaging.

In this work, we obtained three new phosphorescent iridium complexes (Ir1-Ir3) of general stoichiometry [Ir(N^C)2(N^N)]Cl decorated with oligo(ethylene glycol) fragments to make them water-soluble and biocompatible, as well as to protect them from aggregation with biomolecules such as albumin. The major photophysical characteristics of these phosphorescent complexes are determined by the nature of two cyclometallating ligands (N^C) based on 2-pyridine-benzothiophene, since quantum chemical calculations revealed that the electronic transitions responsible for the excitation and emission are localized mainly at these fragments. However, the use of various diimine ligands (N^N) proved to affect the quantum yield of phosphorescence and allowed for changing the complexes' sensitivity to oxygen, due to the variations in the steric accessibility of the chromophore center for O2 molecules. It was also found that the N^N ligands made it possible to tune the biocompatibility of the resulting compounds. The wavelengths of the Ir1-Ir3 emission maxima fell in the range of 630-650 nm, the quantum yields reached 17% (Ir1) in a deaerated solution, and sensitivity to molecular oxygen, estimated as the ratio of emission lifetime in deaerated and aerated water solutions, displayed the highest value, 8.2, for Ir1. The obtained complexes featured low toxicity, good water solubility and the absence of a significant effect of biological environment components on the parameters of their emission. Of the studied compounds, Ir1 and Ir2 were chosen for in vitro and in vivo biological experiments to estimate oxygen concentration in cell lines and tumors. These sensors have demonstrated their effectiveness for mapping the distribution of oxygen and for monitoring hypoxia in the biological objects studied.

Evaluation of therapeutic strategies targeting BCAA catabolism using a systems pharmacology model.

Background: Abnormal branched-chained amino acids (BCAA) accumulation in cardiomyocytes is associated with cardiac remodeling in heart failure. Administration of branched-chain α-keto acid dehydrogenase (BCKD) kinase inhibitor BT2 has been shown to reduce cardiac BCAA levels and demonstrated positive effects on cardiac function in a preclinical setting. The current study is focused on evaluating the impact of BT2 on the systemic and cardiac levels of BCAA and their metabolites as well as activities of BCAA catabolic enzymes using a quantitative systems pharmacology model. Methods: The model is composed of an ordinary differential equation system characterizing BCAA consumption with food, disposal in the proteins, reversible branched-chain-amino-acid aminotransferase (BCAT)-mediated transamination to branched-chain keto-acids (BCKA), followed by BCKD-mediated oxidation. Activity of BCKD is regulated by the balance of BCKDK and protein phosphatase 2Cm (PP2Cm) activities, affected by BT2 treatment. Cardiac BCAA levels are assumed to directly affect left ventricular ejection fraction (LVEF). Biochemical characteristics of the enzymes are taken from the public domains, while plasma and cardiac BCAA and BCKA levels in BT2 treated mice are used to inform the model parameters. Results: The model provides adequate reproduction of the experimental data and predicts synchronous BCAA responses in the systemic and cardiac space, dictated by rapid BCAA equilibration between the tissues. The model-based simulations indicate maximum possible effect of BT2 treatment on BCAA reduction to be 40% corresponding to 12% increase in LVEF. Model sensitivity analysis demonstrates strong impact of BCKDK and PP2Cm activities as well as total BCKD and co-substrate levels (glutamate, ketoglutarate and ATP) on BCAA and BCKA levels. Conclusion: Model based simulations confirms using of plasma measurements as a marker of cardiac BCAA changes under BCKDK inhibition. The proposed model can be used for optimization of preclinical study design for novel compounds targeting BCAA catabolism.

A Physiology-Based Model of Bile Acid Distribution and Metabolism Under Healthy and Pathologic Conditions in Human Beings.

BACKGROUND & AIMS: Disturbances of the enterohepatic circulation of bile acids (BAs) are seen in a number of clinically important conditions, including metabolic disorders, hepatic impairment, diarrhea, and gallstone disease. To facilitate the exploration of underlying pathogenic mechanisms, we developed a mathematical model built on quantitative physiological observations across different organs. METHODS: The model consists of a set of kinetic equations describing the syntheses of cholic, chenodeoxycholic, and deoxycholic acids, as well as time-related changes of their respective free and conjugated forms in the systemic circulation, the hepatoportal region, and the gastrointestinal tract. The core structure of the model was adapted from previous modeling research and updated based on recent mechanistic insights, including farnesoid X receptor-mediated autoregulation of BA synthesis and selective transport mechanisms. The model was calibrated against existing data on BA distribution and feedback regulation. RESULTS: According to model-based predictions, changes in intestinal motility, BA absorption, and biotransformation rates affected BA composition and distribution differently, as follows: (1) inhibition of transintestinal BA flux (eg, in patients with BA malabsorption) or acceleration of intestinal motility, followed by farnesoid X receptor down-regulation, was associated with colonic BA accumulation; (2) in contrast, modulation of the colonic absorption process was predicted to not affect the BA pool significantly; and (3) activation of ileal deconjugation (eg, in patents with small intestinal bacterial overgrowth) was associated with an increase in the BA pool, owing to higher ileal permeability of unconjugated BA species. CONCLUSIONS: This model will be useful in further studying how BA enterohepatic circulation modulation may be exploited for therapeutic benefits.

Differentiating the Sodium-Glucose Cotransporter 1 Inhibition Capacity of Canagliflozin vs. Dapagliflozin and Empagliflozin Using Quantitative Systems Pharmacology Modeling.

The aim of this research was to differentiate dapagliflozin, empagliflozin, and canagliflozin based on their capacity to inhibit sodium-glucose cotransporter (SGLT) 1 and 2 in patients with type 2 diabetes using a previously developed quantitative systems pharmacology model of renal glucose filtration, reabsorption, and excretion. The analysis was based on pooled, mean study-level data on 24-hour urinary glucose excretion, average daily plasma glucose, and estimated glomerular filtration rate collected from phase I and II clinical trials of SGLT2 inhibitors. Variations in filtered glucose across clinical studies were shown to drive the apparent differences in the glucosuria dose-response relationships among the gliflozins. A normalized dose-response analysis demonstrated similarity of dapagliflozin and empagliflozin, but not canagliflozin. At approved doses, SGLT1 inhibition by canagliflozin but not dapagliflozin or empagliflozin contributed to ~ 10% of daily urinary glucose excretion.