Performance of longitudinal item response theory models in shortened or partial assessments.

This work evaluates the performance of longitudinal item response (IR) theory models in shortened assessments using an existing model for part II and III of the MDS-UPDRS score. Based on the item information content, the assessment was reduced by removal of items in multiple increments and the models' ability to recover the item characteristics of the remaining items at each level was evaluated. This evaluation was done for both simulated and real data. The metric of comparison in both cases was the item information function. For real data, the impact of shortening on the estimated disease progression and drug effect was also studied. In the simulated data setting, the item characteristics did not differ between the full and the shortened assessments down to the lowest level of information remaining; indicating a considerable independence between items. In contrast when reducing the assessment in a real data setting, a substantial change in item information was observed for some of the items. Disease progression and drug effect estimates also decreased in the reduced assessments. These changes indicate a shift in the measured construct of the shortened assessment and warrant caution when comparing results from a partial assessment with results from the full assessment.

Stabilization of Ostwald ripening in low molecular weight amino lipid nanoparticles for systemic delivery of siRNA therapeutics.

Lipid nanoparticles (LNPs) represent the most clinically advanced technology for the systemic delivery of therapeutic siRNA in vivo. Toward this end, a novel class of LNPs comprising low molecular weight (MW) ionizable amino lipids having asymmetric architecture was recently reported.1 LNPs of these amino lipids, termed asymmetric LNPs, were shown to be highly efficacious and well tolerated in vivo; advances were enabled by improved endosomal escape, coupled with enhanced amino lipid metabolism and clearance. In this work, we show that, in contrast to their desirable pharmacological performance, asymmetric LNPs present a significant pharmaceutical developability challenge, namely physical instability limiting extended shelf life. Using orthogonal characterization methods, we identify the mechanism of LNP instability as Ostwald ripening and establish it to be driven predominantly by the asymmetric amino lipid component. Through rational optimization of LNP physical and macromolecular properties, we are able to significantly attenuate or entirely eliminate the Ostwald ripening instability. Modulation of LNP size, for example, effectively halts particle growth. Similarly, optimization of LNP macromolecular packing through deliberate selection of structurally matched colipids significantly diminishes the rate of ripening. This later experimental observation is substantiated by molecular dynamics simulations of LNP self-assembly, which establish a quantitative dependence of LNP macromolecular order on colipid structure. In totality, the experimental and molecular dynamics outcomes of this work support the rational design of LNP physical and chemical properties leading to effective Ostwald ripening stabilization and enable the advance of asymmetric LNPs as a clinic-ready platform for siRNA therapeutics.

Comparison of Two Methods for Determining Item Characteristic Functions and Latent Variable Time-Course for Pharmacometric Item Response Models.

There are examples in the literature demonstrating different approaches to defining the item characteristic functions (ICF) and characterizing the latent variable time-course within a pharmacometrics item response theory (IRT) framework. One such method estimates both the ICF and latent variable time-course simultaneously, and another method establishes the ICF first then models the latent variable directly. To date, a direct comparison of the "simultaneous" and "sequential" methodologies described in this work has not yet been systematically investigated. Item parameters from a graded response IRT model developed from Parkinson's Progression Marker Initiative (PPMI) study data were used as simulation parameters. Each method was evaluated under the following conditions: (i) with and without drug effect and (ii) slow progression rate with smaller sample size and rapid progression rate with larger sample size. Overall, the methods performed similarly, with low bias and good precision for key parameters and hypothesis testing for drug effect. The ICF parameters were well determined when the model was correctly specified, with an increase in precision in the scenario with rapid progression. In terms of drug effect, both methods had large estimation bias for the slow progression rate; however, this bias can be considered small relative to overall progression rate. Both methods demonstrated type 1 error control and similar discrimination between model with and without drug effect. The simultaneous method was slightly more precise than the sequential method while the sequential method was more robust towards longitudinal model misspecification and offers practical advantages in model building.

Assessing the heterogeneity level in lipid nanoparticles for siRNA delivery: size-based separation, compositional heterogeneity, and impact on bioperformance.

A primary consideration when developing lipid nanoparticle (LNP) based small interfering RNA (siRNA) therapeutics is formulation polydispersity or heterogeneity. The level of heterogeneity of physicochemical properties within a pharmaceutical batch could greatly affect the bioperformance, quality, and ability of a manufacturer to consistently control and reproduce the formulations. This article studied the heterogeneity in the size, composition, and in vitro performance of siRNA containing LNPs, by conducting preparative scale fractionation using a sephacryl S-1000 based size-exclusion chromatography (SEC) method. Eight LNPs with size in the range of 60-190 nm were first evaluated by the SEC method for size polydispersity characterization, and it was found that LNPs in the range of 60-150 nm could be well-resolved. Two LNPs (LNP A and LNP B) with similar bulk properties were fractionated, and fractions were studied in-depth for potential presence of polydispersity in size, composition, and in vitro silencing, as well as cytotoxicity. LNP A was deemed to be monodisperse following results of a semipreparative SEC fractionation that showed similar size, chemical composition, in vitro silencing activity, and cytotoxicity across the fractions. Therefore, LNP A represents a relatively homogeneous formulation and offers less of a challenge in its pharmaceutical development. In contrast, LNP B fractions were shown to be significantly more polydisperse in size distribution. Interestingly, LNP B SEC fractions also exhibited profound compositional variations (e.g., 5 fold difference in N/P ratio and 3 fold difference in lipid composition) along with up to 40 fold differences in the in vitro silencing activity. The impact of LNP size and formulation composition on in vitro performance is also discussed. The present results demonstrate the complexity and potential for presence of heterogeneity in LNP-based siRNA drug products. This underscores the need for tools that yield a detailed characterization of LNP formulations. This capability in tandem with the pursuit of improved formulation and process design can lead to more facile development of LNP-based siRNA pharmaceuticals of higher quality.

Population Pharmacokinetics of Vericiguat in Patients With Heart Failure With Reduced Ejection Fraction: An Integrated Analysis.

Vericiguat, a novel stimulator of soluble guanylate cyclase (sGC), is indicated for the treatment of patients following a hospitalization for heart failure or need for outpatient intravenous diuretics, with symptomatic chronic heart failure and ejection fraction less than 45%. Pharmacokinetic (PK) data from the phase II trial SOCRATES-REDUCED (Soluble Guanylate Cyclase Stimulator in Heart Failure Study) and the phase III trial VICTORIA (Vericiguat Global Study in Patients With Heart Failure With Reduced Ejection Fraction) were used to characterize vericiguat PK. A total of 8,092 concentration records from 2,321 participants (362 from SOCRATES-REDUCED and 1,959 from VICTORIA) were utilized for the development of the population PK model. The final PK model was a one-compartment model with first-order absorption and linear elimination. Baseline body weight and time-varying body weight were identified as statistically significant covariates affecting apparent clearance (CL/F) and volume of distribution, respectively. Age, sex, race, bilirubin, estimated glomerular filtration rate, and albumin did not affect vericiguat PK. Baseline disease-related factors, such as left ventricular ejection fraction, New York Heart Association (NYHA) class, and N-terminal pro B-type natriuretic peptide, also did not influence vericiguat PK. Since vericiguat is a titrated drug, the impact of vericiguat PK on the titration to and maintenance of the target dose in VICTORIA was assessed. The distribution of steady-state doses in VICTORIA was similar across CL/F quartiles, suggesting that the ability to reach and maintain dosing at the target 10-mg dose was not related to vericiguat exposure.

Understanding effect site pharmacology of uprifosbuvir, a hepatitis C virus nucleoside inhibitor: Case study of a multidisciplinary modeling approach in drug development.

Uprifosbuvir is a uridine nucleoside monophosphate prodrug inhibitor of the hepatitis C virus NS5B RNA polymerase. To quantitatively elucidate key metabolic pathways, assess the link between unmeasurable effect site concentrations and viral load reduction, and evaluate the influence of intrinsic and extrinsic factors on pharmacokinetics and pharmacodynamics, a model-informed drug development (MIDD) framework was initiated at an early stage. Originally scoped as a modeling effort focused on minimal physiologically based pharmacokinetic and covariate analyses, this project turned into a collaborative effort focused on gaining a deeper understanding of the data from drug metabolism, biopharmaceutics, pharmacometrics, and clinical pharmacology perspectives. This article presents an example of the practical execution of a MIDD-based, cooperative multidisciplinary modeling approach, creating a model that grows along with the team's integrated knowledge. Insights gained from this process could be used in forming optimal collaborations between disciplines in drug development for other investigative compounds.

The development of an in vitro assay to screen lipid based nanoparticles for siRNA delivery.

In order to rapidly screen and select lead candidates for in vivo evaluation of lipid nanoparticles (LNPs) for systemic small interfering RNA (siRNA) delivery, an in vitro assay amenable to high-throughput screening (HTS) is developed. The strategy is to mimic the in vivo experience of LNPs after systemic administration, such as interactions with serum components, exposure to endosomal pH environments, and interactions with endosomal membrane lipids. It is postulated that the amount of siRNA released from LNPs after going through these treatments can be used as a screening tool to rank order the effectiveness of siRNA delivery by lipid nanoparticles in vivo. LNPs were incubated with 50% serum from different species (i.e. mouse, rat, or rhesus) at 37°C. The resulting samples were then reacted with anionic, endosomal-mimicking lipids at different pHs. The amount of siRNA released from LNPs was determined using spectrophotometry employing the fluorescent indicator SYBR Gold. Our results indicated that the amount of siRNA liberated was highly dependent upon the species of serum used and the pH to which it was exposed. LNPs treated with mouse serum showed higher levels of siRNA release, as did those subjected to endosomal pH (6.0), compared to physiological pH. Most interestingly, a good correlation between the amount of siRNA released and the in vivo efficacy was observed. In conclusion, an in vitro siRNA release assay was developed to screen and rank order LNPs for in vivo evaluation.