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NCT04852861COMPLETEDanonymous

COVID-19: Safety and Immunogenicity of a Reduced Dose of the BioNTech/Pfizer BNT162b2 Vaccine in a Healthy Population

Sponsor

Source record

Sciensano

Phase

Source record

Phase 4

Modality

AI-normalized

vaccine

Target

AI-normalized

SARS-CoV-2 Spike Protein Receptor Binding Domain (RBD)

Indication / condition

AI-normalized

Covid19

Intervention

Source record

immunogenicity after first and second dose

Source & freshness

Source record

NCT ID

NCT04852861

Original source

ClinicalTrials.gov

Source last updated

Mar 28, 2023

Ingested at

Jun 16, 2026

Internal sync

Jun 16, 2026

Model version

trialsignal-ai-v1

Normalized confidence

96%

Validation status

validated

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NCT ID

NCT04852861

Title

COVID-19: Safety and Immunogenicity of a Reduced Dose of the BioNTech/Pfizer BNT162b2 Vaccine in a Healthy Population

Sponsor

Sciensano

Status

COMPLETED

Phase

Phase 4

Condition raw

Covid19

Condition normalized

Covid19

Modality raw

vaccine

Modality normalized

vaccine

Target raw

SARS-CoV-2 Spike Protein Receptor Binding Domain (RBD)

Target normalized

SARS-CoV-2 Spike Protein Receptor Binding Domain (RBD)

Interventions

immunogenicity after first and second dose

Public preview

Source record

The REDU-VAC study, sponsored by Sciensano, evaluates the safety and immunogenicity of reduced doses of the BNT162b2 mRNA vaccine in a healthy population. Given the ongoing global demand for COVID-19 vaccinations and the potential for reduced dosing strategies to optimize vaccine distribution, this study may provide valuable insights into dose-sparing approaches. The results could influence future vaccination guidelines and market strategies, particularly in regions facing supply constraints. The competitive landscape includes other mRNA vaccines and emerging COVID-19 therapies, necessitating close monitoring of efficacy and safety data to maintain market position.

AI-generated analysis supports research triage only. Verify source records, publications, sponsor disclosures and IP databases before making diligence decisions. Model: trialsignal-ai-v1.

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