Contact Us

SLR & Meta-Analysis

An extension of our clinical trial outcomes data services, we curate safety and efficacy outcomes data from published clinical trials. These datasets can be used for network meta-analysis (NMA) to estimate the comparative efficacy and safety of some interventions. Starting from your research question, Excelra assembles disparate trial outcome data into an evidence network to assess data readiness and statistical analysis feasibility.

UNLOCKING INTELLIGENCE FROM CLINICAL TRIAL LITERATURE

A comparison of relevant competing interventions is fundamental to evidence-based decision-making. When direct comparisons are unavailable from clinical trials, Excelra conducts a systematic literature review of outcomes data for indirect treatment comparisons (ITC) and network meta-analysis (NMA), as well as for mixed-treatment comparisons, to assess the comparative effectiveness of healthcare interventions.

Starting from your research question, Excelra strategizes to develop networks of evidence and conducts a meta-analysis of disparate published trial outcomes data to fulfil the objective with the right choice of model (fixed or random-effects), and the right approach (frequentist vs. Bayesian), followed by model validation for evaluation of homogeneity and consistency, and development of a scientific report for publication or regulatory submission.

Typical problems we can solve for our partners

  • Estimate the comparative effectiveness of assets with competitors (particularly when H2H data is not available)
  • Inform what the efficacy landscape might be in early clinical phases
  • Support your evidence generation/development
  • Identify any potential early signals for adverse event reporting
  • Focus on the inputs needed for health economic modeling and HTA submissions
  • Support content for dossiers and payer submissions (such as humanistic, clinical and economic burden of illness)
  • Identify any potential evidence gaps
  • Evidence surveillance – understand real world outcomes by reviewing information from social media, pharmacovigilance feeds, market intelligence updates and more
  • Support identification of clinical endpoints, comparators and outcomes for future research/studies