Across projects, the work typically sits at the interface of biology, mathematics, and strategy, with recurring themes in experiment design, questions around combinations and sequencing, mechanistic models and virtual populations, uncertainty quantification, model simplification, and tailored methods. Most projects to date have involved oncology and immunology indications, but the same methods can be applied to other complex diseases, where mechanism and heterogeneity play a central role. 

Engagements are scoped to the specific questions, data, and constraints of each project rather than to a fixed modeling template.

More detail can be found on the Services page.

“Quercus” is the Latin name for the oak. The name also recalls a literary reference from a fictional novel described by Vladimir Nabokov in which a single oak observes events, large and small, over centuries, while an author-like observer sits in the upper branches with an apparatus, watching and collecting impressions.

For Quercus Insights, the oak image reflects a way of working:

• paying attention to both small details and large patterns

• integrating information from multiple vantage points over time

• using quantitative “apparatus” (models, analyses, virtual populations) to observe, probe, and organize complex systems.

The goal is not to impose a particular framework on a problem, but to find a vantage point from which the relevant structure becomes clear and testable.

Our working style is collaborative, decision-focused, and fit-for-purpose. We work in partnership with the teams towards shared goals. 

A full description is provided on the Approach page.

Quercus Insights is led by Irina Kareva, PhD, MBA, a quantitative biologist with experience in

• industry pharmacometrics and quantitative systems pharmacology, including PK/PD, disease modeling, and virtual populations

• theoretical and mathematical biology, with extensive peer-reviewed work in experiment design, combination therapy, and heterogeneous response dynamics

This background allows the practice to move comfortably between mechanism, data, and decision-making, while remaining pragmatic about timelines, resources, and the level of uncertainty that is acceptable at different stages of development.

While the practice is designed to be broadly applicable across complex disease and therapy development, Quercus Insights has a particular interest in problems where evolutionary and ecological ideas are central. This includes resistance and adaptation in oncology, evolution-guided therapy design, and concepts related to “evolutionary tumor boards” as explored in the literature.

Quercus Insights does not operate clinical tumor boards, but is familiar with the modeling frameworks and published experience underlying evolution-based, adaptive treatment strategies. We would be interested in collaborating with teams who wish to explore analogous approaches in preclinical models, virtual populations, or the design of future adaptive studies.