Advanced Analytics (AA):
Exploring advanced methods to support therapeutic innovation that do not align with traditional methods
- Quantifying the value of the product through other range of approaches such as surrogate threshold effect, incorporating real-world evidence through three-level Bayesian hierarchical model, model-based NMAs
(MBNMA), and propensity score matching analysis - Conduct target product profile (TPP) or assumptions-based early analysis to underscore the future potential of a product
- Incorporating real world evidence to trial evidence strengthening the value of a product
- Support innovation in trial design using synthetic control arms
- Survival analysis including parametric, flexible parametric (spline), landmark responders, Frailty and Poisson analysis to support the long-term value of a product
- Conduct utility analysis as an input to economic models
- Statistical analysis plan development and real-world evidence data synthesis through various statistical methods/analytical procedures
- Sample size calculations and epidemiological synthesis of longitudinal
data - Conduct meta-analysis of economic evidence, RWE evidence, and evidence from both aggregate data and individual patient data