Randomized, controlled, proof-of-concept trial of gefapixant for endometriosis-related pain.

Objective: To evaluate the P2X3 receptor antagonist, gefapixant, for treating moderate-to-severe endometriosis-related pain.

Design: Randomized, double-blind, phase 2, and proof-of-concept trial.

Setting: Outpatients at hospitals, medical centers or clinical research sites.

Population pharmacokinetics of molnupiravir in adults with COVID-19: Lack of clinically important exposure variation across individuals.

Effective antiviral treatments for coronavirus disease 2019 (COVID-19) are needed to reduce the morbidity and mortality associated with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection, particularly in patients with risk factors for severe disease. Molnupiravir (MK-4482, EIDD-2801) is an orally administered, ribonucleoside prodrug of β-D-N4-hydroxycytidine (NHC) with submicromolar potency against SARS-CoV-2. A population pharmacokinetic (PopPK) analysis for molnupiravir exposure was conducted using 4202 NHC plasma concentrations collected in 1207 individuals from a phase I trial in healthy participants, a phase IIa trial in non-hospitalized participants with COVID-19, a phase II trial in hospitalized participants with COVID-19, and a phase II/III trial in non-hospitalized participants with COVID-19.

Population pharmacokinetic analysis of the P2X3-receptor antagonist gefapixant.

Gefapixant, a P2X3-receptor antagonist, demonstrated objective and subjective efficacy in individuals with refractory or unexplained chronic cough. We report a population pharmacokinetic (PopPK) analysis that characterizes gefapixant pharmacokinetics (PKs), quantifies between- and within-participant variability, and evaluates the impact of intrinsic and extrinsic factors on gefapixant exposure. The PopPK model was initially developed using PK data from six phase I studies.

Factors Influencing COVID-19 Risk: Insights From Molnupiravir Exposure-Response Modeling of Clinical Outcomes.

Molnupiravir (MOV) is an oral antiviral for the treatment of coronavirus disease 2019 (COVID-19) in outpatient settings. This analysis investigated the relationship between β-D-N4-hydroxycytidine (NHC) pharmacokinetics and clinical outcomes in patients with mild to moderate COVID-19 in the phase III part of the randomized, double-blind, placebo-controlled MOVe-OUT trial. Logistic regression models of the dependency of outcomes on exposures and covariates were constructed using a multistep process.

Operating characteristics of stepwise covariate selection in pharmacometric modeling.

Stepwise covariate modeling (SCM) is a widely used tool in pharmacometric analyses to identify covariates that explain between-subject variability (BSV) in exposure and exposure-response relationships. However, this approach has several potential weaknesses, including over-estimated covariate effect and incorrect selection of covariates due to collinearity. In this work, we investigated the operating characteristics (i.

Cryptic individual scaling relationships and the evolution of morphological scaling.

Morphological scaling relationships between organ and body size-also known as allometries-describe the shape of a species, and the evolution of such scaling relationships is central to the generation of morphological diversity. Despite extensive modeling and empirical tests, however, the modes of selection that generate changes in scaling remain largely unknown. Here, we mathematically model the evolution of the group-level scaling as an emergent property of individual-level variation in the developmental mechanisms that regulate trait and body size.