Simulation-Based Pharmacokinetics Sampling Design for Evaluating Correlates of Prevention Efficacy of Passive HIV Monoclonal Antibody Prophylaxis.

population PK analysis sample size determination sampling of PK time-points study adherence two-compartment PK model

Journal

Statistics in biopharmaceutical research
ISSN: 1946-6315
Titre abrégé: Stat Biopharm Res
Pays: United States
ID NLM: 101507745

Informations de publication

Date de publication:
2022
Historique:
entrez: 23 1 2023
pubmed: 24 1 2023
medline: 24 1 2023
Statut: ppublish

Résumé

We address sampling design of population pharmacokinetics (popPK) experiments in the context of two ongoing phase 2b efficacy trials that evaluate the efficacy of VRC01 (vs. placebo) in reducing the rate of HIV infection among 4625 participants. Blood samples are collected at up to 22 study visits from all participants for immediate HIV diagnosis as the primary trial outcome, and stored for future outcome-dependent marker measurements. A key secondary objective of the trials is to evaluate correlates of prevention efficacy among a sub-cohort of VRC01 recipients in terms of whether the current value of VRC01 serum concentration is associated with the instantaneous rate of HIV infection. To accomplish this, concentrations on a daily grid are estimated via non-linear mixed effects popPK modeling of observed 4-weekly concentrations. Given the impracticality of measuring concentrations in all stored blood samples, we devised a simulation-based sampling design framework to evaluate the impact of sub-cohort sample sizes (

Identifiants

pubmed: 36684526
doi: 10.1080/19466315.2021.1919196
pmc: PMC9856202
mid: NIHMS1757617
doi:

Types de publication

Journal Article

Langues

eng

Pagination

611-625

Subventions

Organisme : NIAID NIH HHS
ID : R37 AI054165
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI068614
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI068618
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI068635
Pays : United States

Déclaration de conflit d'intérêts

Disclosure statement No potential conflicts of interest were disclosed.

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Auteurs

Lily Zhang (L)

Vaccine and Infectious Disease Division, Fred Hutchinson Research Center, Seattle, USA.

Peter B Gilbert (PB)

Vaccine and Infectious Disease Division, Fred Hutchinson Research Center, Seattle, USA.
Department of Biostatistics, University of Washington, Seattle, USA.

Edmund Capparelli (E)

Department of Pediatrics, University of California, San Diego, USA.

Yunda Huang (Y)

Vaccine and Infectious Disease Division, Fred Hutchinson Research Center, Seattle, USA.
Department of Global Health, University of Washington, Seattle, USA.

Classifications MeSH