Quercus Insights supports drug discovery and development programs at the interface of biology, mathematics, and strategy. Typical engagements includes:

• experiment design and data collection strategy

• framing and analyzing questions around combinations, sequencing, and resistance

• development of fit-for-purpose mechanistic models and virtual populations

• simplification and documentation of existing models

• creation of tailored methods when standard approaches are insufficient to answer the question

Projects are scoped around specific questions, data, and constraints, rather than around a fixed modeling template.

For more detail, see the Services page.

Most engagements are with early-stage and growing organizations, including:

• start-ups that have promising mechanisms and limited experiment slots, but no internal modeling group

• small quantitative teams within larger organizations needing support on specific problems

• academic–industry collaborations where quantitative methods can help connect hypotheses, experiments, and potential therapeutic strategies

For more on how we support early-stage teams, see For Startups.

Across projects, the approach is consistent: 

• Start from decisions and constraints

• Design studies with an eye for what they can and cannot tell us

• Use mechanistic models as tools, not products

• Make assumptions and methods explicit so they can be scrutinized and re-used

For more detail, see the Approach page.

Initial discussions are brief and exploratory. They focus on understanding:

• the current stage of the program

• the main decisions and constraints over the next 6–18 months

• whether there is a well-posed role for quantitative support at this time

If it appears that Quercus Insights can add value, a small, clearly defined first engagement, such as an experiment design review, a focused “puzzle” consultation, or a compact modeling exercise, can be scoped.