22 research outputs found
Use of the anterior-posterior chest diameter in CT: reduction in radiation dose?
Vascular Biology and Interventio
Increased accuracy in computed tomography coronary angiography; a new body surface area adapted protocol
Vascular Biology and Interventio
Gated myocardial SPECT imaging; true additional value in AMI?
Vascular Biology and Interventio
2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.
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Interaction between thrombin potential and age on early clinical outcome in patients hospitalized for COVID-19
Long-term satellite tracking reveals variable seasonal migration strategies of basking sharks in the north-east Atlantic
From Target Selection to the Minimum Acceptable Biological Effect Level for Human Study: Use of Mechanism-based PK/PD Modeling to Design Safe and Efficacious Biologics
In this paper, two applications of mechanism-based modeling are presented with their utility from candidate selection to first-in-human dosage selection. The first example is for a monoclonal antibody against a cytomegalovirus glycoprotein complex, which involves an antibody binding model and a viral load model. The model was used as part of a feasibility analysis prior to antibody generation, setting the specifications for the affinity needed to achieve a desired level of clinical efficacy. The second example is a pharmacokinetic–pharmacodynamic model based on a single-dose pharmacology study in cynomolgus monkey using data on pharmacokinetics, receptor occupancy, and the dynamics of target cell depletion and recovery. The model was used to estimate the MABEL, here defined as the minimum acceptable biological effect level against which a dose is selected for a first-in-human study. From these applications, we demonstrate that mechanism-based PK/PD binding models are useful for predicting human response to biologics compounds. Especially, such models have the ability to integrate preclinical and clinical, in vitro and in vivo information and facilitate rational decision making during various stages of drug discovery and translational research