A Europe-based large pharma company engaged in development of novel antibody therapeutics against Rheumatoid Arthritis (RA), was analyzing the data to demonstrate the advantage of longitudinal meta-analysis over conventional meta-analysis that uses end-of-study (EOS) data, toward facilitating more effective Model Informed Drug Development (MIDD) decisions.
Client’s requirement
The client approached Excelra to develop a Model Based Meta Analysis (MBMA)-ready dataset, by curating all the existing scientific evidence around the efficacy of marketed biologics for RA.
- The curated dataset should have summary time-course response on clinical outcomes used in late stage clinical trials.
- The data should also cover information about prior and concomitant medications including:
- Respective category-wise percentage of patients (with response status to medications)
- Baseline patient characteristics and sample size including N in statistical analysis
Our approach
In line with the specified requirements, Excelra’s Clinical Data Services group used a robust scientific curation methodology coupled with systematic literature review (SLR), to synthesize data on existing therapeutics for performing model based meta-analysis (MBMA).
