Bioequivalence Engine

BE studies are the cornerstone of generic drug approval. However, failures due to high variability or inappropriate designs can delay time-to-market by years.

What we do

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Study Design Optimisation

Craft crossover and replicate study designs tailored to specific drug characteristics and regulatory requirements.

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Scaled Average Bioequivalence (SABE) Implementation

Apply SABE methods for highly variable drugs to meet bioequivalence criteria effectively.

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Real-Time Simulation Tools

Utilize simulations to predict study outcomes and adjust parameters proactively.

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Historical Data Integration

Leverage existing data to inform study design and anticipate potential challenges.

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AI Integration

AI predictive models to estimate success probability and design optimality

Advanced Features

Built-in modules for outlier detection, carryover effect analysis, ANOVA modeling, and subject-by-formulation interaction testing.

Business Value

Decreases the likelihood of failed BE studies, accelerates FDA/EMA approval, and enhances ROI for generic and biosimilar development.