RUDI: Resolving Unclassified Variants to Improve Estimates of Disease Incidence and Prevalence

What is RUDI?

Meet RUDI—a workflow that combines genetics and epidemiologic modeling of large-scale genomic data to classify variants of unknown significance to better estimate the incidence and prevalence of rare genetic diseases.  

Built for pharma and biotech teams developing therapies for rare genetic diseases, RUDI uses a training set of well-characterized variants to construct a model that predicts the function of variants of unknown significance, then uses variant frequencies in a specific population to evaluate incidence. 

What RUDI Helps You Accomplish:

• Focus enrollment where it’s most likely to succeed 
  • RUDI supports targeted enrollment strategies, leading to shortened timelines and reduced costs and enabling more efficient patient identification. 
• Evidence-driven site strategy 
  • Optimize clinical site selection for locations most likely to encounter patients with the targeted disorder. 
• Right-Size and prioritize the addressable patient population 
  • Produce better prevalence and incidence estimates across key populations, leveraging data to inform patient population size and strategy. 
• Reuse and refresh as data evolves 
  • RUDI serves as a reusable analytic framework that can be refreshed as new data emerges. The model can also integrate company proprietary data. 

How RUDI Works – Translating Evidence into Direction: 

1. Learn from what’s known: RUDI starts with well-characterized variants to build a model. 
2. Predict what’s unknown: The model predicts functional impact for variants of unknown significance. 
3. Connect variants to populations: RUDI determines frequencies of pathogenic and predicted pathogenic variants within specific populations using allele frequency databases. 
4. Estimate incidence and prevalence: Variant frequencies inform incidence and prevalence estimates to support strategic decisions.