Development of a Minimal Physiologically-Based Pharmacokinetic Model to Simulate Lung Exposure in Humans Following Oral Administration of Ivermectin for COVID-19 Drug Repurposing

SARS-CoV-2 utilizes the IMPα/β1 heterodimer to enter host cell nuclei after gaining cellular access through the ACE2 receptor. Ivermectin has shown antiviral activity by inhibiting the formation of the importin-α (IMPα) and IMPβ1 subunits as well as dissociating the IMPα/β1 heterodimer and has in vitro efficacy against SARS-CoV-2. Plasma and lung ivermectin concentrations vs. time profiles in cattle were used to determine the apparent plasma to lung tissue partition coefficient of ivermectin. This coefficient, together with a simulated geometric mean plasma profile of ivermectin from a published population pharmacokinetic model, was utilized to develop a minimal physiologically-based pharmacokinetic (mPBPK) model. The mPBPK model accurately described the simulated ivermectin plasma concentration profile in humans. The mPBPK model was also used to simulate human lung exposure to ivermectin after 12, 30, and 120 mg oral doses. The simulated ivermectin lung exposures reached a maximum concentration of 772 ng/mL, far less than the estimated 1750 ng/mL IC50 reported for ivermectin against SARS-CoV-2 in vitro. Further studies of ivermectin either reformulated for inhaled delivery or in combination with other antivirals with differing mechanisms of action is needed to assess its therapeutic potential.Fil: Jermain, Brian. University of North Carolina; Estados UnidosFil: Hanafin, Patrick O.. University of North Carolina; Estados UnidosFil: Cao, Yanguang. University of North Carolina; Estados UnidosFil: Lifschitz, Adrian Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; ArgentinaFil: Lanusse, Carlos Edmundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; ArgentinaFil: Rao, Gauri G.. University of North Carolina; Estados Unido

Insights Into Patient Variability During Ivacaftor-Lumacaftor Therapy in Cystic Fibrosis

Background: The advent of cystic fibrosis transmembrane conductance regulator protein (CFTR) modulators like ivacaftor have revolutionised the treatment of cystic fibrosis (CF). However, due to the plethora of variances in disease manifestations in CF, there are inherent challenges in unified responses under CFTR modulator treatment arising from variability in patient outcomes. The pharmacokinetic (PK) data available for ivacaftor-lumacaftor cystic fibrosis (CF) transmembrane conductance regulator (CFTR) modulator drug combination is limited. Methods: Secondary objectives were to identify (1) patient characteristics and (2) the interactions between ivacaftor-lumacaftor responsible for interindividual variability (IIV). Results: Peak plasma concentrations (Cmax) of ivacaftor - lumacaftor were >10 fold lower than expected compared to label information. The one-way ANOVA indicated that the patient site had an effect on Cmax values of ivacaftor metabolites ivacaftor-M1, ivacaftor-M6, and lumacaftor (p < 0.001, p < 0.001, and p < 0.001, respectively). The Spearman’s rho test indicated that patient weight and age have an effect on the Cmax of lumacaftor (p = 0.003 and p < 0.001, respectively) and ivacaftor metabolite M1 (p = 0.020 and p < 0.001, respectively). Age (p < 0.001) was found to effect on Cmax of ivacaftor M6 and on Tmax of ivacaftor M1 (p = 0.026). A large impact of patient characteristics on the IIV of PK parameters Cmax and Tmax, was observed among the CF patients. Conclusion: Understanding the many sources of variability can help reduce this individual patient variability and ensure consistent patient outcomes

A Mechanism‐based Pharmacokinetic Model of Remdesivir Leveraging Interspecies Scaling to Simulate COVID‐19 Treatment in Humans

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak initiated the global COVID-19 pandemic resulting in 42.9 million confirmed infections and >1.1 million deaths worldwide as of October 26, 2020. Remdesivir is a broad-spectrum nucleotide prodrug shown to be effective against enzootic coronaviruses. The pharmacokinetics (PK) of remdesivir in plasma have recently been described. However, the distribution of its active metabolite nucleoside triphosphate (NTP) to the site of pulmonary infection is unknown in humans. Our objective was to use existing in vivo mouse PK data for remdesivir and its metabolites to develop a mechanism-based model to allometrically scale and simulate the human PK of remdesivir in plasma and NTP in lung homogenate. Remdesivir and GS-441524 concentrations in plasma and total phosphorylated nucleoside concentrations in lung homogenate from Ces1c-/- mice administered 25 or 50 mg/kg of remdesivir subcutaneously were simultaneously fit to estimate PK parameters. The mouse PK model was allometrically scaled to predict human PK parameters to simulate the clinically recommended 200 mg loading dose followed by 100 mg daily maintenance doses administered as 30-minute intravenous infusions. Simulations of unbound remdesivir concentrations in human plasma were below 2.48 μM, the 90% maximal inhibitory concentration for SARS-CoV-2 inhibition in vitro. Simulations of NTP in lung were below high efficacy in vitro thresholds. We have identified a need for alternative dosing strategies to achieve more efficacious concentrations of NTP in human lung, perhaps by reformulating remdesivir for direct pulmonary delivery

Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients

Polymyxin B (PMB) has reemerged as a last-line therapy for infections caused by multidrug-resistant gram-negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction-based and simulation-based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two-compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model-informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill