Serum AZD7442 (tixagevimab-cilgavimab) concentrations and IC values predict SARS-CoV-2 neutralising antibody titres.

Objectives: The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) necessitates rapid methods for assessing monoclonal antibody (mAb) potency against emerging variants. Authentic virus neutralisation assays are considered the gold standard for measuring virus-neutralising antibody (nAb) titres in serum. However, authentic virus-based assays pose inherent practical challenges for measuring nAb titres against emerging SARS-CoV-2 variants (e.

In vivo mRNA expression of a multi-mechanistic mAb combination protects against Staphylococcus aureus infection.

Single monoclonal antibodies (mAbs) can be expressed in vivo through gene delivery of their mRNA formulated with lipid nanoparticles (LNPs). However, delivery of a mAb combination could be challenging due to the risk of heavy and light variable chain mispairing. We evaluated the pharmacokinetics of a three mAb combination against Staphylococcus aureus first in single chain variable fragment scFv-Fc and then in immunoglobulin G 1 (IgG1) format in mice.

Application of Modelling and Simulation Approaches to Predict Pharmacokinetics of Therapeutic Monoclonal Antibodies in Pediatric Population.

Ethical regulations and limited paediatric participants are key challenges that contribute to a median delay of 6 years in paediatric mAb approval. To overcome these barriers, modelling and simulation methodologies have been adopted to design optimized paediatric clinical studies and reduce patient burden. The classical modelling approach in paediatric pharmacokinetic studies for regulatory submissions is to apply body weight-based or body surface area-based allometric scaling to adult PK parameters derived from a popPK model to inform the paediatric dosing regimen.

A workflow for the joint modeling of longitudinal and event data in the development of therapeutics: Tools, statistical methods, and diagnostics.

Clinical trials investigate treatment endpoints that usually include measurements of pharmacodynamic and efficacy biomarkers in early-phase studies and patient-reported outcomes as well as event risks or rates in late-phase studies. In recent years, a systematic trend in clinical trial data analytics and modeling has been observed, where retrospective data are integrated into a quantitative framework to prospectively support analyses of interim data and design of ongoing and future studies of novel therapeutics. Joint modeling is an advanced statistical methodology that allows for the investigation of clinical trial outcomes by quantifying the association between baseline and/or longitudinal biomarkers and event risk.