Use of Compartmental Modeling and Retinol Isotope Dilution to Determine Vitamin A Stores in Young People with Sickle Cell Disease Before and After Vitamin A Supplementation

BACKGROUND

Suboptimal plasma retinol concentrations have been documented in US children with sickle cell disease (SCD) hemoglobin SS type (SCD-HbSS), but little is known about vitamin A kinetics and stores in SCD.

OBJECTIVES

The objectives were to quantify vitamin A total body stores (TBS) and whole-body retinol kinetics in young people with SCD-HbSS and use retinol isotope dilution (RID) to predict TBS in SCD-HbSS and healthy peers as well as after vitamin A supplementation in SCD-HbSS subjects.

METHODS

Composite plasma [13C10]retinol response data collected from 22 subjects with SCD-HbSS for 28 d after isotope ingestion were analyzed using population-based compartmental modeling ("super-subject" approach); TBS and retinol kinetics were quantified for the group. TBS was also calculated for the same individuals using RID, as well as for healthy peers (n = 20) and for the subjects with SCD-HbSS after 8 wk of daily vitamin A supplements (3.15 or 6.29 μmol retinol/d [900 or 1800 μg retinol activity equivalents/d]).

RESULTS

Model-predicted group mean TBS for subjects with SCD-HbSS was 428 μmol, equivalent to ∼11 mo of stored vitamin A; vitamin A disposal rate was 1.3 μmol/d. Model-predicted TBS was similar to that predicted by RID at 3 d postdosing (mean, 389 μmol; ∼0.3 μmol/g liver); TBS predictions at 3 compared with 28 d were not significantly different. Mean TBS in healthy peers was similar (406 μmol). RID-predicted TBS for subjects with SCD-HbSS was not significantly affected by vitamin A supplementation at either dose.

CONCLUSIONS

Despite differences in plasma retinol concentrations, TBS was the same in subjects with SCD-HbSS compared with healthy peers. Because 56 d of vitamin A supplementation at levels 1.2 to 2.6 times the Recommended Dietary Allowance did not increase TBS in these subjects with SCD-HbSS, further work will be needed to understand the effects of SCD on retinol metabolism. This trial was registered as NCT03632876 at clinicaltrials.gov.

Populations of in silico myocytes and tissues reveal synergy of multiatrial-predominant K+ -current block in atrial fibrillation

BACKGROUND AND PURPOSE

Pharmacotherapy of atrial fibrillation (AF), the most common cardiac arrhythmia, remains unsatisfactory due to low efficacy and safety concerns. New therapeutic strategies target atrial-predominant ion-channels and involve multichannel block (poly)therapy. As AF is characterized by rapid and irregular atrial activations, compounds displaying potent antiarrhythmic effects at fast and minimal effects at slow rates are desirable. We present a novel systems pharmacology framework to quantitatively evaluate synergistic anti-AF effects of combined block of multiple atrial-predominant K⁺ currents (ultra-rapid delayed rectifier K⁺ current, I_Kur , small conductance Ca²⁺ -activated K⁺ current, I_KCa , K_2P 3.1 2-pore-domain K⁺ current, I_K2P ) in AF.

EXPERIMENTAL APPROACH

We constructed experimentally calibrated populations of virtual atrial myocyte models in normal sinus rhythm and AF-remodelled conditions using two distinct, well-established atrial models. Sensitivity analyses on our atrial populations was used to investigate the rate dependence of action potential duration (APD) changes due to blocking I_Kur , I_K2P or I_KCa and interactions caused by blocking of these currents in modulating APD. Block was simulated in both single myocytes and one-dimensional tissue strands to confirm insights from the sensitivity analyses and examine anti-arrhythmic effects of multi-atrial-predominant K⁺ current block in single cells and coupled tissue.

KEY RESULTS

In both virtual atrial myocytes and tissues, multiple atrial-predominant K⁺ -current block promoted favourable positive rate-dependent APD prolongation and displayed positive rate-dependent synergy, that is, increasing synergistic antiarrhythmic effects at fast pacing versus slow rates.

CONCLUSION AND IMPLICATIONS

Simultaneous block of multiple atrial-predominant K⁺ currents may be a valuable antiarrhythmic pharmacotherapeutic strategy for AF.

Utility of a Bayesian Mathematical Model to Predict the Impact of Immunogenicity on Pharmacokinetics of Therapeutic Proteins

The impact of an anti-drug antibody (ADA) response on pharmacokinetic (PK) of a therapeutic protein (TP) requires an in-depth understanding of both PK parameters and ADA characteristics. The ADA and PK bioanalytical assays have technical limitations due to high circulating levels of TP and ADA, respectively, hence, significantly hindering the interpretation of this assessment. The goal of this study was to develop a population-based modeling and simulation approach that can identify a more relevant PK parameter associated with ADA-mediated clearance. The concentration-time data from a single dose PK study using five monoclonal antibodies were modeled using a non-compartmental analysis (NCA), one-compartmental, and two-compartmental Michaelis-Menten kinetic model (MMK). A novel PK parameter termed change in clearance time of the TP (α) derived from the MMK model could predict variations in α much earlier than the time points when ADA could be bioanalytically detectable. The model could also identify subjects that might have been potentially identified as false negative due to interference of TP with ADA detection. While NCA and one-compartment models can estimate loss of exposures, and changes in clearance, the two-compartment model provides this additional ability to predict that loss of exposure by means of α. Modeling data from this study showed that the two-compartment model along with the conventional modeling approaches can help predict the impact of ADA response in the absence of relevant ADA data.

The Impact of Uncertainty in Barrett's Esophagus Progression Rates on Hypothetical Screening and Treatment Decisions

BACKGROUND

Estimates for the annual progression rate from Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) vary widely. In this explorative study, we quantified how this uncertainty affects the estimates of effectiveness and efficiency of screening and treatment for EAC.

DESIGN

We developed 3 versions of the University of Washington / Microsimulation Screening Analysis-EAC model. The models differed with respect to the annual progression rate from BE to EAC (0.12% or 0.42%) and the possibility of spontaneous regression of dysplasia (yes or no). All versions of the model were calibrated to the observed Surveillance, Epidemiology, and End Results esophageal cancer incidence rates from 1998 to 2009. To identify the impact of natural history, we estimated the incidence and deaths prevented as well as numbers needed to screen (NNS) and treat (NNT) of a one-time perfect screening at age 65 years that detected all prevalent BE cases, followed by a perfect treatment intervention.

RESULTS

Assuming a perfect screening and treatment intervention for all patients with BE, the maximum EAC mortality reduction (64%-66%) and the NNS per death prevented (470-510) were similar across the 3 model versions. However, 3 times more people needed to be treated to prevent 1 death (24 v. 8) in the 0.12% regression model compared with the 0.42% progression model. Restricting treatment to those with dysplasia or only high-grade dysplasia resulted in smaller differences in NNT (2-3 to prevent one EAC case) but wider variation in effectiveness (mortality reduction of 15%-24%).

CONCLUSION

The uncertainty in the natural history of the BE to EAC sequence influenced the estimates of effectiveness and efficiency of BE screening and treatment considerably. This uncertainty could seriously hamper decision making about implementing BE screening and treatment interventions.