A unified framework for prediction of liver steatosis dynamics in response to different diet and drug interventions.

BACKGROUND & AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common metabolic disorder, characterized by the accumulation of excess fat in the liver, and is a driving factor for various severe liver diseases. These multi-factorial and multi-timescale changes are observed in different clinical studies, but these studies have not been integrated into a unified framework. In this study, we aim to present such a unified framework in the form of a dynamic mathematical model. METHODS: For model training and validation, we collected data for dietary or drug-induced interventions aimed at reducing or increasing liver fat. The model was formulated using ordinary differential equations (ODEs) and the mathematical analysis, model simulation, model formulation and the model parameter estimation were all performed in MATLAB. RESULTS: Our mathematical model describes accumulation of fat in the liver and predicts changes in lipid fluxes induced by both dietary and drug interventions. The model is validated using data from a wide range of drug and dietary intervention studies and can predict both short-term (days) and long-term (weeks) changes in liver fat. Importantly, the model computes the contribution of each individual lipid flux to the total liver fat dynamics. Furthermore, the model can be combined with an established bodyweight model, to simulate even longer scenarios (years), also including the effects of insulin resistance and body weight. To help prepare for corresponding eHealth applications, we also present a way to visualize the simulated changes, using dynamically changing lipid droplets, seen in images of liver biopsies. CONCLUSION: In conclusion, we believe that the minimal model presented herein might be a useful tool for future applications, and to further integrate and understand data regarding changes in dietary and drug induced changes in ectopic TAG in the liver. With further development and validation, the minimal model could be used as a disease progression model for steatosis.

Tissue pharmacokinetics of antisense oligonucleotides.

Pharmacokinetics (PK) of antisense oligonucleotides (ASOs) is characterized by rapid distribution from plasma to tissue and slow terminal plasma elimination driven by re-distribution from tissue. Quantitative understanding of tissue PK and RNA knockdown for various ASO chemistries, conjugations, and administration routes is critical for successful drug discovery. Here, we report concentration-time and RNA knockdown profiles for a gapmer ASO with locked nucleic acid ribose chemistry in mouse liver, kidney, heart, and lung after subcutaneous and intratracheal administration. Additionally, the same ASO with liver targeting conjugation (galactosamine-N-acetyl) is evaluated for subcutaneous administration. Data indicate that exposure and knockdown differ between tissues and strongly depend on administration route and conjugation. In a second study, we show that tissue PK is similar between the three different ribose chemistries locked nucleic acid, constrained ethyl and 2'-O-methoxyethyl, both after subcutaneous and intratracheal administration. Further, we show that the half-life in mouse liver may vary with ASO sequence. Finally, we report less than dose-proportional increase in liver concentration in the dose range of 3-30 µmol/kg. Overall, our studies contribute pivotal data to support design and interpretation of ASO in vivo studies, thereby increasing the probability of delivering novel ASO therapies to patients.

Injectable Biodegradable Silica Depot for Controlled Subcutaneous Delivery of Antisense Oligonucleotides with beyond Monthly Administration.

Single-stranded antisense oligonucleotides (ASOs) are typically administered subcutaneously once per week or monthly. Less frequent dosing would have strong potential to improve patient convenience and increase adherence and thereby for some diseases result in more optimal therapeutic outcomes. Several technologies are available to provide sustained drug release via subcutaneous (SC) administration. ASOs have a high aqueous solubility and require relatively high doses, which limits the options available substantially. In the present work, we show that an innovative biodegradable, nonporous silica-based matrix provides zero-order release in vivo (rats) for at least 4 weeks for compositions with ASO loads of up to about 100 mg/mL (0.5 mL injection) without any sign of initial burst. This implies that administration beyond once monthly can be feasible. For higher drug loads, substantial burst release was observed during the first week. The concentrations of unconjugated ASO levels in the liver were found to be comparable to corresponding bolus doses. Additionally, infusion using a minipump shows a higher liver exposure than SC bolus administration at the same dose level and, in addition, clear mRNA knockdown and circulating protein reduction comparable to SC bolus dosing, hence suggesting productive liver uptake for a slow-release administration.

A multi-scale digital twin for adiposity-driven insulin resistance in humans: diet and drug effects.

BACKGROUND: The increased prevalence of insulin resistance is one of the major health risks in society today. Insulin resistance involves both short-term dynamics, such as altered meal responses, and long-term dynamics, such as the development of type 2 diabetes. Insulin resistance also occurs on different physiological levels, ranging from disease phenotypes to organ-organ communication and intracellular signaling. To better understand the progression of insulin resistance, an analysis method is needed that can combine different timescales and physiological levels. One such method is digital twins, consisting of combined mechanistic mathematical models. We have previously developed a model for short-term glucose homeostasis and intracellular insulin signaling, and there exist long-term weight regulation models. Herein, we combine these models into a first interconnected digital twin for the progression of insulin resistance in humans. METHODS: The model is based on ordinary differential equations representing biochemical and physiological processes, in which unknown parameters were fitted to data using a MATLAB toolbox. RESULTS: The interconnected twin correctly predicts independent data from a weight increase study, both for weight-changes, fasting plasma insulin and glucose levels, and intracellular insulin signaling. Similarly, the model can predict independent weight-change data in a weight loss study with the weight loss drug topiramate. The model can also predict non-measured variables. CONCLUSIONS: The model presented herein constitutes the basis for a new digital twin technology, which in the future could be used to aid medical pedagogy and increase motivation and compliance and thus aid in the prevention and treatment of insulin resistance.

Plasma Pharmacokinetics of N-Acetylgalactosamine-Conjugated Small-Interfering Ribonucleic Acids (GalNAc-Conjugated siRNAs).

Small-interfering ribonucleic acids (siRNAs) with N-acetylgalactosamine (GalNAc) conjugation for improved liver uptake represent an emerging class of drugs that modulate liver-expressed therapeutic targets. The pharmacokinetics of GalNAc-siRNAs are characterized by a rapid distribution from plasma to tissue (hours) and a long terminal plasma half-life, analyzed in the form of the antisense strand, driven by redistribution from tissue (weeks). Understanding how clinical pharmacokinetics relate to the dose and type of siRNA chemical stabilizing method used is critical, e.g., to design studies, to investigate safety windows, and to predict the pharmacokinetics of new preclinical assets. To this end, we collected and analyzed pharmacokinetic data from the literature regarding nine GalNAc-siRNAs. Based on this analysis, we showed that the clinical plasma pharmacokinetics of GalNAc-siRNAs are approximately dose proportional and similar between chemical stabilizing methods. This holds for both the area under the concentration-time curve (AUC) and the maximum plasma concentration (Cmax). Corresponding rat and monkey pharmacokinetic data for a subset of the nine GalNAc-siRNAs show dose-proportional Cmax, supra-dose-proportional AUC, and similar pharmacokinetics between chemical stabilizing methods​. Together, the animal and human pharmacokinetic data indicate that plasma clearance divided by bioavailability follows allometric principles and scales between species with an exponent of 0.75. Finally, the clinical plasma concentration-time profiles can be empirically described by standard one-compartment kinetics with first-order absorption up to 24 h after subcutaneous dosing, and by three-compartment kinetics with first-order absorption in general. To describe the system more mechanistically, we report a corrected and unambiguously defined version of a previously published physiologically based pharmacokinetic model.

Integrated experimental-computational analysis of a HepaRG liver-islet microphysiological system for human-centric diabetes research.

Microphysiological systems (MPS) are powerful tools for emulating human physiology and replicating disease progression in vitro. MPS could be better predictors of human outcome than current animal models, but mechanistic interpretation and in vivo extrapolation of the experimental results remain significant challenges. Here, we address these challenges using an integrated experimental-computational approach. This approach allows for in silico representation and predictions of glucose metabolism in a previously reported MPS with two organ compartments (liver and pancreas) connected in a closed loop with circulating medium. We developed a computational model describing glucose metabolism over 15 days of culture in the MPS. The model was calibrated on an experiment-specific basis using data from seven experiments, where HepaRG single-liver or liver-islet cultures were exposed to both normal and hyperglycemic conditions resembling high blood glucose levels in diabetes. The calibrated models reproduced the fast (i.e. hourly) variations in glucose and insulin observed in the MPS experiments, as well as the long-term (i.e. over weeks) decline in both glucose tolerance and insulin secretion. We also investigated the behaviour of the system under hypoglycemia by simulating this condition in silico, and the model could correctly predict the glucose and insulin responses measured in new MPS experiments. Last, we used the computational model to translate the experimental results to humans, showing good agreement with published data of the glucose response to a meal in healthy subjects. The integrated experimental-computational framework opens new avenues for future investigations toward disease mechanisms and the development of new therapies for metabolic disorders.

Digital twin predicting diet response before and after long-term fasting.

Today, there is great interest in diets proposing new combinations of macronutrient compositions and fasting schedules. Unfortunately, there is little consensus regarding the impact of these different diets, since available studies measure different sets of variables in different populations, thus only providing partial, non-connected insights. We lack an approach for integrating all such partial insights into a useful and interconnected big picture. Herein, we present such an integrating tool. The tool uses a novel mathematical model that describes mechanisms regulating diet response and fasting metabolic fluxes, both for organ-organ crosstalk, and inside the liver. The tool can mechanistically explain and integrate data from several clinical studies, and correctly predict new independent data, including data from a new study. Using this model, we can predict non-measured variables, e.g. hepatic glycogen and gluconeogenesis, in response to fasting and different diets. Furthermore, we exemplify how such metabolic responses can be successfully adapted to a specific individual's sex, weight, height, as well as to the individual's historical data on metabolite dynamics. This tool enables an offline digital twin technology.

A case-study of model-informed drug development of a novel PCSK9 anti sense oligonucleotide. Part 1: First time in man to phase II.

Here, we show model-informed drug development (MIDD) of a novel antisense oligonucleotide, targeting PCSK9 for treatment of hypocholesteremia. The case study exemplifies use of MIDD to analyze emerging data from an ongoing first-in-human study, utility of the US Food and Drug Administration MIDD pilot program to accelerate timelines, innovative use of competitor data to set biomarker targets, and use of MIDD to optimize sample size and dose selection, as well as to accelerate and de-risk a phase IIb study. The focus of the case-study is on the cross-functional collaboration and other key MIDD enablers that are critical to maximize the value of MIDD, rather than the technical application of MIDD.

Cross-Species Translation of Biophase Half-Life and Potency of GalNAc-Conjugated siRNAs.

Small interfering RNAs (siRNAs) with N-acetylgalactosamine (GalNAc) conjugation for improved liver uptake represent an emerging class of drugs to treat liver diseases. Understanding how pharmacokinetics and pharmacodynamics translate is pivotal for in vivo study design and human dose prediction. However, the literature is sparse on translational data for this modality, and pharmacokinetics in the liver is seldom measured. To overcome these difficulties, we collected time-course biomarker data for 11 GalNAc-siRNAs in various species and applied the kinetic-pharmacodynamic modeling approach to estimate the biophase (liver) half-life and the potency. Our analysis indicates that the biophase half-life is 0.6-3 weeks in mouse, 1-8 weeks in monkey, and 1.5-14 weeks in human. For individual siRNAs, the biophase half-life is 1-8 times longer in human than in mouse, and generally 1-3 times longer in human than in monkey. The analysis indicates that the siRNAs are more potent in human than in mouse and monkey.

Inhibition of SGLT2 Preserves Function and Promotes Proliferation of Human Islets Cells In Vivo in Diabetic Mice.

Dapagliflozin is a sodium-glucose co-transporter 2 (SGLT2) inhibitor used for the treatment of diabetes. This study examines the effects of dapagliflozin on human islets, focusing on alpha and beta cell composition in relation to function in vivo, following treatment of xeno-transplanted diabetic mice. Mouse beta cells were ablated by alloxan, and dapagliflozin was provided in the drinking water while controls received tap water. Body weight, food and water intake, plasma glucose, and human C-peptide levels were monitored, and intravenous arginine/glucose tolerance tests (IVarg GTT) were performed to evaluate islet function. The grafted human islets were isolated at termination and stained for insulin, glucagon, Ki67, caspase 3, and PDX-1 immunoreactivity in dual and triple combinations. In addition, human islets were treated in vitro with dapagliflozin at different glucose concentrations, followed by insulin and glucagon secretion measurements. SGLT2 inhibition increased the animal survival rate and reduced plasma glucose, accompanied by sustained human C-peptide levels and improved islet response to glucose/arginine. SGLT2 inhibition increased both alpha and beta cell proliferation (Ki67+glucagon+ and Ki67+insulin+) while apoptosis was reduced (caspase3+glucagon+ and caspase3+insulin+). Alpha cells were fewer following inhibition of SGLT2 with increased glucagon/PDX-1 double-positive cells, a marker of alpha to beta cell transdifferentiation. In vitro treatment of human islets with dapagliflozin had no apparent impact on islet function. In summary, SGLT2 inhibition supported human islet function in vivo in the hyperglycemic milieu and potentially promoted alpha to beta cell transdifferentiation, most likely through an indirect mechanism.

Mathematical Model Predicts that Acceleration of Diabetic Wound Healing is Dependent on Spatial Distribution of VEGF-A mRNA (AZD8601).

INTRODUCTION: Pharmacologic approaches for promoting angiogenesis have been utilized to accelerate healing of chronic wounds in diabetic patients with varying degrees of success. We hypothesize that the distribution of proangiogenic drugs in the wound area critically impacts the rate of closure of diabetic wounds. To evaluate this hypothesis, we developed a mathematical model that predicts how spatial distribution of VEGF-A produced by delivery of a modified mRNA (AZD8601) accelerates diabetic wound healing. METHODS: We modified a previously published model of cutaneous wound healing based on coupled partial differential equations that describe the density of sprouting capillary tips, chemoattractant concentration, and density of blood vessels in a circular wound. Key model parameters identified by a sensitivity analysis were fit to data obtained from an in vivo wound healing study performed in the dorsum of diabetic mice, and a pharmacokinetic model was used to simulate mRNA and VEGF-A distribution following injections with AZD8601. Due to the limited availability of data regarding the spatial distribution of AZD8601 in the wound bed, we performed simulations with perturbations to the location of injections and diffusion coefficient of mRNA to understand the impact of these spatial parameters on wound healing. RESULTS: When simulating injections delivered at the wound border, the model predicted that injections delivered on day 0 were more effective in accelerating wound healing than injections delivered at later time points. When the location of the injection was varied throughout the wound space, the model predicted that healing could be accelerated by delivering injections a distance of 1-2 mm inside the wound bed when compared to injections delivered on the same day at the wound border. Perturbations to the diffusivity of mRNA predicted that restricting diffusion of mRNA delayed wound healing by creating an accumulation of VEGF-A at the wound border. Alternatively, a high mRNA diffusivity had no effect on wound healing compared to a simulation with vehicle injection due to the rapid loss of mRNA at the wound border to surrounding tissue. CONCLUSIONS: These findings highlight the critical need to consider the location of drug delivery and diffusivity of the drug, parameters not typically explored in pre-clinical experiments, when designing and testing drugs for treating diabetic wounds. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12195-021-00678-9.

An oral antisense oligonucleotide for PCSK9 inhibition.

Inhibitors of proprotein convertase subtilisin/kexin type 9 (PCSK9) reduce low-density lipoprotein (LDL) cholesterol and are used for treatment of dyslipidemia. Current PCSK9 inhibitors are administered via subcutaneous injection. We present a highly potent, chemically modified PCSK9 antisense oligonucleotide (ASO) with potential for oral delivery. Past attempts at oral delivery using earlier-generation ASO chemistries and transient permeation enhancers provided encouraging data, suggesting that improving potency of the ASO could make oral delivery a reality. The constrained ethyl chemistry and liver targeting enabled by N-acetylgalactosamine conjugation make this ASO highly potent. A single subcutaneous dose of 90 mg reduced PCSK9 by >90% in humans with elevated LDL cholesterol and a monthly subcutaneous dose of around 25 mg is predicted to reduce PCSK9 by 80% at steady state. To investigate the feasibility of oral administration, the ASO was coformulated in a tablet with sodium caprate as permeation enhancer. Repeated oral daily dosing in dogs resulted in a bioavailability of 7% in the liver (target organ), about fivefold greater than the plasma bioavailability. Target engagement after oral administration was confirmed by intrajejunal administration of a rat-specific surrogate ASO in solution with the enhancer to rats and by plasma PCSK9 and LDL cholesterol lowering in cynomolgus monkey after tablet administration. On the basis of an assumption of 5% liver bioavailability after oral administration in humans, a daily dose of 15 mg is predicted to reduce circulating PCSK9 by 80% at steady state, supporting the development of the compound for oral administration to treat dyslipidemia.

Hybrid modelling for stroke care: Review and suggestions of new approaches for risk assessment and simulation of scenarios.

Stroke is an example of a complex and multi-factorial disease involving multiple organs, timescales, and disease mechanisms. To deal with this complexity, and to realize Precision Medicine of stroke, mathematical models are needed. Such approaches include: 1) machine learning, 2) bioinformatic network models, and 3) mechanistic models. Since these three approaches have complementary strengths and weaknesses, a hybrid modelling approach combining them would be the most beneficial. However, no concrete approach ready to be implemented for a specific disease has been presented to date. In this paper, we both review the strengths and weaknesses of the three approaches, and propose a roadmap for hybrid modelling in the case of stroke care. We focus on two main tasks needed for the clinical setting: a) For stroke risk calculation, we propose a new two-step approach, where non-linear mixed effects models and bioinformatic network models yield biomarkers which are used as input to a machine learning model and b) For simulation of care scenarios, we propose a new four-step approach, which revolves around iterations between simulations of the mechanistic models and imputations of non-modelled or non-measured variables. We illustrate and discuss the different approaches in the context of Precision Medicine for stroke.

Distribution and biotransformation of therapeutic antisense oligonucleotides and conjugates.

Drug properties of antisense oligonucleotides (ASOs) differ significantly from those of traditional small-molecule therapeutics. In this review, we focus on ASO disposition, mainly as characterized by distribution and biotransformation, of nonconjugated and conjugated ASOs. We introduce ASO chemistry to allow the following in-depth discussion on bioanalytical methods and determination of distribution and elimination kinetics at low concentrations over extended periods of time. The resulting quantitative data on the parent oligonucleotide, and the identification and quantification of formed metabolites define the disposition. Proper quantitative understanding of disposition is pivotal for nonclinical to clinical predictions, supports communication with health agencies, and increases the probability of delivering optimal ASO therapy to patients.

Model-Based Analysis Reveals a Sustained and Dose-Dependent Acceleration of Wound Healing by VEGF-A mRNA (AZD8601).

Intradermal delivery of AZD8601, an mRNA designed to produce vascular endothelial growth factor A (VEGF-A), has previously been shown to accelerate cutaneous wound healing in a murine diabetic model. Here, we develop population pharmacokinetic and pharmacodynamic models aiming to quantify the effect of AZD8601 injections on the dynamics of wound healing. A dataset of 584 open wound area measurements from 131 mice was integrated from 3 independent studies encompassing different doses, dosing timepoints, and number of doses. Evaluation of several candidate models showed that wound healing acceleration is not likely driven directly by time-dependent VEGF-A concentration. Instead, we found that administration of AZD8601 induced a sustained acceleration of wound healing depending on the accumulated dose, with a dose producing 50% of the maximal effect of 92 µg. Simulations with this model showed that a single dose of 200 µg AZD8601 can reduce the time to reach 50% wound healing by up to 5 days.

Inhibition of the prostaglandin D2-GPR44/DP2 axis improves human islet survival and function.

AIMS/HYPOTHESIS: Inflammatory signals and increased prostaglandin synthesis play a role during the development of diabetes. The prostaglandin D2 (PGD2) receptor, GPR44/DP2, is highly expressed in human islets and activation of the pathway results in impaired insulin secretion. The role of GPR44 activation on islet function and survival rate during chronic hyperglycaemic conditions is not known. In this study, we investigate GPR44 inhibition by using a selective GPR44 antagonist (AZ8154) in human islets both in vitro and in vivo in diabetic mice transplanted with human islets. METHODS: Human islets were exposed to PGD2 or proinflammatory cytokines in vitro to investigate the effect of GPR44 inhibition on islet survival rate. In addition, the molecular mechanisms of GPR44 inhibition were investigated in human islets exposed to high concentrations of glucose (HG) and to IL-1ß. For the in vivo part of the study, human islets were transplanted under the kidney capsule of immunodeficient diabetic mice and treated with 6, 60 or 100 mg/kg per day of a GPR44 antagonist starting from the transplantation day until day 4 (short-term study) or day 17 (long-term study) post transplantation. IVGTT was performed on mice at day 10 and day 15 post transplantation. After termination of the study, metabolic variables, circulating human proinflammatory cytokines, and hepatocyte growth factor (HGF) were analysed in the grafted human islets. RESULTS: PGD2 or proinflammatory cytokines induced apoptosis in human islets whereas GPR44 inhibition reversed this effect. GPR44 inhibition antagonised the reduction in glucose-stimulated insulin secretion induced by HG and IL-1ß in human islets. This was accompanied by activation of the Akt-glycogen synthase kinase 3ß signalling pathway together with phosphorylation and inactivation of forkhead box O-1and upregulation of pancreatic and duodenal homeobox-1 and HGF. Administration of the GPR44 antagonist for up to 17 days to diabetic mice transplanted with a marginal number of human islets resulted in reduced fasting blood glucose and lower glucose excursions during IVGTT. Improved glucose regulation was supported by increased human C-peptide levels compared with the vehicle group at day 4 and throughout the treatment period. GPR44 inhibition reduced plasma levels of TNF-α and growth-regulated oncogene-α/chemokine (C-X-C motif) ligand 1 and increased the levels of HGF in human islets. CONCLUSIONS/INTERPRETATION: Inhibition of GPR44 in human islets has the potential to improve islet function and survival rate under inflammatory and hyperglycaemic stress. This may have implications for better survival rate of islets following transplantation.

PPARγ and PPARα synergize to induce robust browning of white fat in vivo.

OBJECTIVE: Peroxisome proliferator-activated receptors (PPARs) are key transcription factors that regulate adipose development and function, and the conversion of white into brown-like adipocytes. Here we investigated whether PPARα and PPARγ activation synergize to induce the browning of white fat. METHODS: A selection of PPAR activators was tested for their ability to induce the browning of both mouse and human white adipocytes in vitro, and in vivo in lean and obese mice. RESULTS: All dual PPARα/γ activators tested robustly increased uncoupling protein 1 (Ucp1) expression in both mouse and human adipocytes in vitro, with tesaglitazar leading to the largest Ucp1 induction. Importantly, dual PPARα/γ activator tesaglitazar strongly induced browning of white fat in vivo in both lean and obese male mice at thermoneutrality, greatly exceeding the increase in Ucp1 observed with the selective PPARγ activator rosiglitazone. While selective PPARγ activation was sufficient for the conversion of white into brown-like adipocytes in vitro, dual PPARα/γ activation was superior to selective PPARγ activation at inducing white fat browning in vivo. Mechanistically, the superiority of dual PPARα/γ activators is mediated at least in part via a PPARα-driven increase in fibroblast growth factor 21 (FGF21). Combined treatment with rosiglitazone and FGF21 resulted in a synergistic increase in Ucp1 mRNA levels both in vitro and in vivo. Tesaglitazar-induced browning was associated with increased energy expenditure, enhanced insulin sensitivity, reduced liver steatosis, and an overall improved metabolic profile compared to rosiglitazone and vehicle control groups. CONCLUSIONS: PPARγ and PPARα synergize to induce robust browning of white fat in vivo, via PPARγ activation in adipose, and PPARα-mediated increase in FGF21.

Deficiency of T-type voltage-gated calcium channels results in attenuated weight gain and improved endothelium-dependent dilatation of resistance vessels induced by a high-fat diet in mice.

The deletion of T-type Cav3.1 channels may reduce high-fat diet (HFD)-induced weight gain, which correlates positively with obesity and endothelial dysfunction. Therefore, experiments were designed to study the involvement of T-type Cav3.1 channels in HFD-induced endothelial dysfunction in mice. Wildtype (WT) and Cav3.1-/- mice were fed either a normal diet (ND) or an HFD for 8 weeks. Body composition was assessed, and thoracic aortae and mesenteric arteries were harvested for myography to assess endothelium-dependent responses. Changes in intracellular calcium were measured by fluorescence imaging, and behavior was assessed with the open-field test. Cav3.1-/- mice had attenuated HFD-induced weight gain and lower total fat mass compared with WT mice. Cav3.1-/- mice on an HFD had reduced plasma cholesterol levels compared with WT mice on the same diet. Increased feeding efficiency, independent of food intake, was observed in WT mice on an HFD compared with an ND, but no difference in feeding efficiency between diets was observed for Cav3.1-/- mice. Nitric oxide-dependent dilatation was increased in mesenteric arteries of Cav3.1-/- mice compared with WT mice on an HFD, with no difference observed in aortae. No differences in mouse locomotor activity were observed between the experimental groups. Mice on an HFD lacking T-type channels have reduced weight gain, lower total cholesterol levels, and increased dilatation of resistance vessels compared with WT mice on an HFD, suggesting that Cav3.1 deletion protects against endothelial dysfunction in resistance vessels but not in large conduit vessels.

ADME: Assessing Pharmacokinetic-Pharmacodynamic Parameters of Oligonucleotides.

We describe tactics to assess pharmacokinetic (PK) and pharmacodynamic (PD) parameters of oligonucleotides. The chapter includes recommendations on the design of single-dose preclinical PK studies, preclinical PKPD studies, and toxicological studies, and on best practice for scaling PK and PD parameters from animal to human. We focus on single-stranded oligonucleotides, but relevant differences to double-stranded RNAs are also addressed.

Inferring Half-Lives at the Effect Site of Oligonucleotide Drugs.

Knowledge of the kinetics of the active drug in biophase, that is, at the effect site, is fundamental to select dose and to reason about safety. Unfortunately, the kinetics is cumbersome to measure in vivo. We describe how dose-response-time (DRT) analysis estimates the biophase and the target-response half-lives from data of the circulating protein of the encoded messenger RNA for seven antisense oligonucleotides (ASOs) and four small interfering RNA (siRNA) drugs. The biophase half-lives were estimated with acceptable precision (relative standard error <26%). For ASOs, the estimates were similar to, or slightly longer than, the reported terminal plasma half-lives. Terminal plasma half-life was reported for only one siRNA, precluding any general comparison. The estimated half-lives of response were 0.5-12 days cross drugs and shorter than the biophase half-lives. We recommend DRT analysis when limited plasma pharmacokinetic data are available, or when the biophase half-life differs from the terminal plasma half-life.