Efficacy and safety of pelacarsen in lowering Lp(a) in healthy Japanese subjects.

BACKGROUND: Pelacarsen is a liver-targeted antisense oligonucleotide that potently lowers lipoprotein(a) [Lp(a)] levels. Its safety and efficacy in diverse populations has not been extensively studied. OBJECTIVE: To assess the effect of pelacarsen, including monthly dosing of 80 mg, in subjects of Japanese ancestry. METHODS: A randomized double-blind, placebo-controlled, study was performed in 29 healthy Japanese subjects treated with single ascending doses (SAD) of pelacarsen 20, 40 and 80 mg subcutaneously or multiple doses (MD) of pelacarsen 80 mg monthly for 4 doses. The primary objective was to assess the safety and tolerability in healthy Japanese subjects; secondary objectives to assess the pharmacokinetics of pelacarsen; and exploratory objective to determine the effect of pelacarsen on plasma Lp(a) levels. RESULTS: No serious adverse events or clinically relevant abnormalities in any laboratory parameters were noted. In the MD cohort, mean plasma concentrations of pelacarsen peaked at ∼4 hours and declined in a bi-exponential manner thereafter. In the SAD cohorts, the placebo-corrected least-square mean (PCLSM) percent changes in Lp(a) at Day 30 were: -55.4% (p=0.0008), -58.9% (p=0.0003) and -73.7% (p<0.0001) for the 20 mg, 40 mg, and 80 mg pelacarsen-treated groups, respectively. In the MD cohort, the PCLSM at Days 29, 85, 113, 176 and 204 were -84.0% (p=0.0003), -106.2% (p<0.0001), -70.0 (p<0.0001), -80.0% (p=0.0104) and -55.8% (p=0.0707), respectively. CONCLUSIONS: Pelacarsen demonstrates an acceptable safety and tolerability profile and potently lowers plasma levels of Lp(a) in healthy Japanese subjects, including with the 80 mg monthly dose being evaluated in the Lp(a) HORIZON trial.

Translational Population-Pharmacodynamic Modeling of a Novel Long-Acting siRNA Therapy, Inclisiran, for the Treatment of Hypercholesterolemia.

Inclisiran is a novel N-acetylgalactosamine (GalNAc) conjugated small-interfering ribonucleic acid (siRNA) therapy designed to specifically target proprotein convertase subtilisin/kexin type 9 (PCSK9) mRNA in the liver for the treatment of hypercholesterolemia. Inclisiran's GalNAc attachment results in a rapid uptake into the liver, and thus a short plasma half-life, but long duration of effects on PCSK9 inhibition and low-density lipoprotein cholesterol (LDL-C) lowering. The effects on PCSK9 inhibition and consequent LDL-C reduction are sustained for more than 6 months following a single subcutaneous (s.c.) dose, despite inclisiran being detectable in the plasma only for up to 48 hours. A kinetic-pharmacodynamic (K-PD) model was developed to characterize inclisiran's dose-related LDL-C lowering effects and to evaluate the impact of intrinsic and extrinsic factors on LDL-C lowering. To accommodate the long duration of action, the K-PD model incorporated an effect compartment which represents the liver. Inclisiran concentration in the liver leads to decreased production of the PCSK9 protein and allow recycling of more LDL-C receptors on the hepatocyte cell surface, which results in a reduction of circulating LDL-C. The analysis of covariates identified PCSK9 and LDL-C baseline levels as important factors for the effects of LDL-C lowering. Observations and modeling and simulation results demonstrated that PCSK9 and LDL-C reductions are achieved rapidly after dosing and sustained when patients are treated with a 300 mg s.c. dose once every 6 months.

Effective Visual Communication for the Quantitative Scientist.

Effective visual communication is a core competency for pharmacometricians, statisticians, and, more generally, any quantitative scientist. It is essential in every step of a quantitative workflow, from scoping to execution and communicating results and conclusions. With this competency, we can better understand data and influence decisions toward appropriate actions. Without it, we can fool ourselves and others and pave the way to wrong conclusions and actions. The goal of this tutorial is to convey this competency. We posit three laws of effective visual communication for the quantitative scientist: have a clear purpose, show the data clearly, and make the message obvious. A concise "Cheat Sheet," available on https://graphicsprinciples.github.io, distills more granular recommendations for everyday practical use. Finally, these laws and recommendations are illustrated in four case studies.

How can we make better graphs? An initiative to increase the graphical expertise and productivity of quantitative scientists.

Graphics are at the core of exploring and understanding data, communicating results and conclusions, and supporting decision-making. Increasing our graphical expertise can significantly strengthen our impact as professional statisticians and quantitative scientists. In this article, we present a concerted effort to improve the way we create graphics at Novartis. We provide our vision and guiding principles, before describing seven work packages in more detail. The actions, principles, and experiences laid out in this paper are applicable generally, also beyond drug development, which is our field of work. The purpose of this article is to share our experiences and help foster the use of good graphs in pharmaceutical statistics and beyond. A Graphics Principles "Cheat Sheet" is available online at https://graphicsprinciples.github.io/.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 2: An introduction to the simulation exercise and overview of results.

Orally administered drugs are subject to a number of barriers impacting bioavailability (Foral), causing challenges during drug and formulation development. Physiologically-based pharmacokinetic (PBPK) modelling can help during drug and formulation development by providing quantitative predictions through a systems approach. The performance of three available PBPK software packages (GI-Sim, Simcyp®, and GastroPlus™) were evaluated by comparing simulated and observed pharmacokinetic (PK) parameters. Since the availability of input parameters was heterogeneous and highly variable, caution is required when interpreting the results of this exercise. Additionally, this prospective simulation exercise may not be representative of prospective modelling in industry, as API information was limited to sparse details. 43 active pharmaceutical ingredients (APIs) from the OrBiTo database were selected for the exercise. Over 4000 simulation output files were generated, representing over 2550 study arm-institution-software combinations and approximately 600 human clinical study arms simulated with overlap. 84% of the simulated study arms represented administration of immediate release formulations, 11% prolonged or delayed release, and 5% intravenous (i.v.). Higher percentages of i.v. predicted area under the curve (AUC) were within two-fold of observed (52.9%) compared to per oral (p.o.) (37.2%), however, Foral and relative AUC (Frel) between p.o. formulations and solutions were generally well predicted (64.7% and 75.0%). Predictive performance declined progressing from i.v. to solution and immediate release tablet, indicating the compounding error with each layer of complexity. Overall performance was comparable to previous large-scale evaluations. A general overprediction of AUC was observed with average fold error (AFE) of 1.56 over all simulations. AFE ranged from 0.0361 to 64.0 across the 43 APIs, with 25 showing overpredictions. Discrepancies between software packages were observed for a few APIs, the largest being 606, 171, and 81.7-fold differences in AFE between SimCYP and GI-Sim, however average performance was relatively consistent across the three software platforms.

IMI - oral biopharmaceutics tools project - evaluation of bottom-up PBPK prediction success part 1: Characterisation of the OrBiTo database of compounds.

Predicting oral bioavailability (Foral) is of importance for estimating systemic exposure of orally administered drugs. Physiologically-based pharmacokinetic (PBPK) modelling and simulation have been applied extensively in biopharmaceutics recently. The Oral Biopharmaceutical Tools (OrBiTo) project (Innovative Medicines Initiative) aims to develop and improve upon biopharmaceutical tools, including PBPK absorption models. A large-scale evaluation of PBPK models may be considered the first step. Here we characterise the OrBiTo active pharmaceutical ingredient (API) database for use in a large-scale simulation study. The OrBiTo database comprised 83 APIs and 1475 study arms. The database displayed a median logP of 3.60 (2.40-4.58), human blood-to-plasma ratio of 0.62 (0.57-0.71), and fraction unbound in plasma of 0.05 (0.01-0.17). The database mainly consisted of basic compounds (48.19%) and Biopharmaceutics Classification System class II compounds (55.81%). Median human intravenous clearance was 16.9L/h (interquartile range: 11.6-43.6L/h; n=23), volume of distribution was 80.8L (54.5-239L; n=23). The majority of oral formulations were immediate release (IR: 87.6%). Human Foral displayed a median of 0.415 (0.203-0.724; n=22) for IR formulations. The OrBiTo database was found to be largely representative of previously published datasets. 43 of the APIs were found to satisfy the minimum inclusion criteria for the simulation exercise, and many of these have significant gaps of other key parameters, which could potentially impact the interpretability of the simulation outcome. However, the OrBiTo simulation exercise represents a unique opportunity to perform a large-scale evaluation of the PBPK approach to predicting oral biopharmaceutics.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 3: Identifying gaps in system parameters by analysing In Silico performance across different compound classes.

Three Physiologically Based Pharmacokinetic software packages (GI-Sim, Simcyp® Simulator, and GastroPlus™) were evaluated as part of the Innovative Medicine Initiative Oral Biopharmaceutics Tools project (OrBiTo) during a blinded "bottom-up" anticipation of human pharmacokinetics. After data analysis of the predicted vs. measured pharmacokinetics parameters, it was found that oral bioavailability (Foral) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. Foral was also underpredicted for acidic compounds, suggesting overestimation of impact of ionisation on permeation, lack of information on intestinal transporters, or underestimation of solubilisation of weak acids due to less than optimal intestinal model pH settings or underestimation of bile micelle contribution. Foral was overpredicted for weak bases, suggesting inadequate models for precipitation or lack of in vitro precipitation information to build informed models. Relative bioavailability was underpredicted for both high logP compounds as well as poorly water-soluble compounds, suggesting inadequate models for solubility/dissolution, underperforming bile enhancement models and/or lack of biorelevant solubility measurements. These results indicate areas for improvement in model software, modelling approaches, and generation of applicable input data. However, caution is required when interpreting the impact of drug-specific properties in this exercise, as the availability of input parameters was heterogeneous and highly variable, and the modellers generally used the data "as is" in this blinded bottom-up prediction approach.

Forecasting oral absorption across biopharmaceutics classification system classes with physiologically based pharmacokinetic models.

OBJECTIVES: The aim of this study was (1) to determine how closely physiologically based pharmacokinetic (PBPK) models can predict oral bioavailability using a priori knowledge of drug-specific properties and (2) to examine the influence of the biopharmaceutics classification system class on the simulation success. METHODS: Simcyp Simulator, GastroPlus™ and GI-Sim were used. Compounds with published Biowaiver monographs (bisoprolol (BCS I), nifedipine (BCS II), cimetidine (BCS III), furosemide (BCS IV)) were selected to ensure availability of accurate and reproducible data for all required parameters. Simulation success was evaluated with the average fold error (AFE) and absolute average fold error (AAFE). Parameter sensitivity analysis (PSA) to selected parameters was performed. KEY FINDINGS: Plasma concentration-time profiles after intravenous administration were forecast within an AAFE < 3. The addition of absorption processes resulted in more variability in the prediction of the plasma profiles, irrespective of biopharmaceutics classification system (BCS) class. The reliability of literature permeability data was identified as a key issue in the accuracy of predicting oral drug absorption. CONCLUSION: For the four drugs studied, it appears that the forecasting accuracy of the PBPK models is related to the BCS class (BCS I > BCS II, BCS III > BCS IV). These results will need to be verified with additional drugs.

Deconvolution and IVIVC: Exploring the Role of Rate-Limiting Conditions.

In vitro-in vivo correlations (IVIVCs) play an important role in formulation development and drug approval. At the heart of IVIVC is deconvolution, the method of deriving an in vivo "dissolution profile" for comparison with in vitro dissolution data. IVIVCs are generally believed to be possible for highly permeable and highly soluble compounds with release/dissolution as the rate-limiting step. In this manuscript, we apply the traditional deconvolution methods, Wagner-Nelson and numerical deconvolution, to profiles simulated using a simplified small intestine absorption and transit model. Small intestinal transit, dissolution, and absorption rate constants are varied across a range of values approximately covering those observed in the literature. IVIVC plots and their corresponding correlation coefficients are analyzed for each combination of parameters to determine the applicability of the deconvolution methods under a range of rate-limiting conditions. For highly absorbed formulations, the correlation coefficients obtained during IVIVC are comparable for both methods and steadily decline with decreasing dissolution rate and increasing transit rate. The applicability of numerical deconvolution to IVIVC is not greatly affected by absorption rate, whereas the applicability of Wagner-Nelson falls when dissolution rate overcomes absorption rate and absorption becomes the rate-limiting step. The discrepancy between the expected and deconvolved input arises from the violation of a key assumption of deconvolution that the unknown input and unit impulse enter the system in the same location.

A lifelong model for the female reproductive cycle with an antimüllerian hormone treatment to delay menopause.

A system of 16 non-linear, delay differential equations with 66 parameters is developed to model hormonal regulation of the menstrual cycle of a woman from age 20 to 51. This mechanistic model predicts changes in follicle numbers and reproductive hormones that naturally occur over that time span. In particular, the model illustrates the decline in the pool of primordial follicles from age 20 to menopause as reported in the biological literature. Also, model simulations exhibit a decrease in antimüllerian hormone (AMH) and inhibin B and an increase in FSH with age corresponding to the experimental data. Model simulations using the administration of exogenous AMH show that the transfer of non-growing primordial follicles to the active state can be slowed enough to provide more follicles for development later in life and to cause a delay in the onset of menopause as measured by the number of primordial follicles remaining in the ovaries. Other effects of AMH agonists and antagonists are investigated in the setting of this model.

Dynamics and bifurcation of a model for hormonal control of the menstrual cycle with inhibin delay.

A system of 13 ordinary differential equations with 42 parameters is presented to model hormonal regulation of the menstrual cycle. For an excellent fit to clinical data, the model requires a 36 h time delay for the effect of inhibin on the synthesis of follicle stimulating hormone. Biological and mathematical reasons for this delay are discussed. Bifurcations with respect to changes in three important parameters are examined. One parameter represents the level of estradiol adequate for significant synthesis of luteinizing hormone. Bifurcation diagrams with respect to this parameter reveal an interval of parameter values for which a unique stable periodic solution exists and this solution represents a menstrual cycle during which ovulation occurs. The second parameter measures mass transfer between the first two stages of ovarian development and is indicative of healthy follicular growth. The third parameter is the time delay. Changes in the second parameter and the time delay affect the size of the uniqueness interval defined with respect to the first parameter. Saddle-node, transcritical and degenerate Hopf bifurcations are studied.