Table 3.

Data purpose matrix for correlates of protection data for Group B Streptococcus vaccines

	Vaccine objective
	Clinical development	Regulatory and licensure	Vaccine policy and introduction
Key stakeholder/audience User of the CoP data	Academic researchers Manufacturers/developers (pharma and biotech, PPPs) Funders and donors Consortium members	NRAs WHO vaccines pre-Q Manufacturers/developers (pharma and biotech, PPPs) Funders and donors	WHO, SAGE, GNN RITAGs NITAGs Ministries of Health/Finance Industry/manufacturers Health care workers Gavi
Data purpose: What do the stakeholders use the CoP data for? What decisions are made using the CoP data?	Identify biomarker of interest and establish association with outcome of interest e.g early onset vs late onset disease Use CoP to advance vaccine development by informing Go/No-go decisions Identify promising candidates for support Attract investment in promising vaccine candidates for late-stage development Design clinical study to demonstrate effectiveness based upon CoP: protocol approval in advance of vaccine licensure.	Defining pathway to licensure in the absence of clinical efficacy for neonatal invasive GBS disease. Conditional approval of vaccine in the absence of demonstrated clinical efficacy/effectiveness against the desired clinical endpoint Definition of endpoints for phase IV evaluation if part of regulatory approval requirement. Approval of clinical study to demonstrate effectiveness based upon CoP; protocol approval in advance of vaccine licensure. CoP to persuade regulators that if achieved by vaccine would prevent early- and late-onset disease in infants (already framework agreed with FDA, concern remains about derivation of CoP)	Speeding up implementation or reducing ‘dead time’ between vaccine approval and policy recommendation: Inform study design of phase 4 effectiveness study including validation of CoP as predictive biomarker (may be supported by Gavi) Define strategy for licensing second-generation vaccines using CoP alone FVVA – now published and a framework for new data to feed into for value proposition and policy decision-making Beyond direct protection: Ancillary data about wider clinical benefits for health economic models Aspirational but useful for stronger prioritisation? Info may not be on label? (data to feed into FVVA)
Data requirements: - What CoP data (what biomarker for what outcome) - When and where (sample site) to collect CoP data - How to measure and validate the CoP data Format or form of communication that enables decision-making	For a defined biomarker e.g. anti-capsular IgG Serum samples at delivery and up to 90 days post birth Rectovaginal swabs Cord and maternal blood at delivery GBS strain Quantitive measurement of Ab responses and association with GBS disease. Functional antibody responses Evaluation of data for derivation of CoP using harmonised assay to allow for: - Universal CoP (geographically diverse populations studied) - Bridging for different valencies of vaccines Support developing international reference standards (lessons learnt from PCV)	Harmonised data collected from representative populations across multiple geographies, serotypes to create aggregate CoP TPP refinement: Single dose agreed but CoP could help understand need for booster and booster scheduling.	Phase IV post licensure studies to support vaccine introduction: Vaccine probe studies to observe prevention of carriage or acquisition (including serotype replacement, adult disease in addition to preterm labour and stillbirth as an outcome of vaccine use). Linkage of CoP with reduction of acquisition during pregnancy important: Small risk of vaccine driving replacement disease. Epidemiological studies across representative geographical locations required: burden data is still lacking for many geographies: 90% infant death due first 24 h – data often missed. Epi studies across representative geographical locations required: burden data still lacking for many geographies: good epidemiological data exist for SA and some other African countries, India, UK, USA. Epidemiological data gaps in Latin America, NZ, AUS. Need to establish what epidemiological data are seen to be sufficient in regions/countries.

NRA National regulatory authority, SAGE Scientific Advisory Group of Experts, GNN Global NITAG network, RITAG Regional Immunisation Technical Advisory Group, NITAG National Immunisation Technical Advisory Group, FVVA Full Value Vaccine Assessment.