Cross Stream Bioanalytics

We increase the return on investment of Quantitative System Pharmacology (QSP)
by enabling QSP scientists to distill complex biomodels
into simpler ones, without sacrificing precision.

Model With Confidence
Model What Matters
Find Your Relevon

Mathematical models are the primary engine of scientific progress in all disciplines, and QSP is no exception. Models allow QSP scientists to:

• Reason about data and mechanisms
• Understand complex processes
• Design controllers and interventions
• Identify knowledge gaps

All models simplify some aspects of reality. Appropriate abstractions answer specific questions, and are "as simple as possible, but no simpler" to paraphrase Einstein. Effective science demands the right tools (which usually means using the right models). Cross Stream Bioanalytics pioneers Explainable AI (XAI) methods for precision modeling in Quantitative Systems Pharmacology (QSP).

The relevon also provides deep insight into the system, rather than a black box that mimics one phenomenon but likely does not extrapolate to others. You are thus far more likely to understand what has gone wrong with a late-phase failure and be able to tweak it appropriately.

Our methods, built on decades of expertise in Information Geometry, allow us to perform all the tasks of a traditional QSP analysis in a fraction of the time and cost. These include:

• XAI enabling fit-to-purpose QSP models
• Data-, Target- and Mechanism-driven
• Explainable Hypothesis Generation
• Optimal Experimental Design
• Intervention design and target selection
• Rigorous Uncertainty Quantification
• Rapid Virtual Population Generation
• Bifurcation analysis
• Fill knowledge gaps
  • Mechanism inference
  • Unexplained data
  • Incomplete Theories