- Identifying an appropriate modeling strategy for your program
- Implementing and simulating E-R, PK/PD and QSP models
- Fitting preclinical and clinical data to guide dose selection and dose escalation
Pharmacodynamic modeling
The pharmacodynamics (PD) of a drug refers to its effect on the body. For small molecules and antibodies, PD is driven by exposure of the drug at its site of action and binding to its target receptor. For cell and immunotherapies, PD is driven by engraftment, expansion and persistence of dosed cells. The onset of a functional therapeutic response can be delayed and may depend on sufficient accumulation of a drug at the site of action. PK/PD models that account for the disposition of a drug and its biological response can help researchers identify optimal dose and dosing regimens and relate biomarker dynamics to efficacy.
Exposure-response analysis
Exposure response (E-R) analysis uses mathematical models to relate the concentration of a drug to biomarkers of efficacy. Often, simple functional forms such as Emax or Hill functions are used to model a continuous response, or a logistic or multinomial logistic function to model a categorical response. When coupled with a PK model for drug disposition, E-R analysis can simulate the expected response in a preclinical or clinical setting for different doses and dosing scenarios. Model fitting to preclinical data can help translate results to a clinical setting and inform clinical dose selection and dose escalation strategies.
Binding and inhibition models
For drugs targeting a specific enzyme, more sophisticated mechanistic models of target binding and inhibition that account for target expression levels and in vivo turnover can be used to predict dynamic changes in substrate or enzyme product levels. Incorporating the specific mechanism - such as competitive versus non-competitive inhibition - can help drive drug design by simulating candidate molecules with different biochemical properties.
Quantitative systems pharmacology (QSP) models
Building upon mechanistic models, QSP models are larger in scope and size and incorporate detailed biological mechanisms. QSP models are implemented as systems of coupled ordinary differential equations (ODEs) that mathematically represent the disease biology and drug-disease interaction. Often constructed as platform models, QSP models can be used as hypothesis generating tools, or used to model multiple classes of therapeutics and combinations of drugs
How we can help
Quantilogix can support your program in the following ways:
We are committed to help accelerate your R&D pipeline by providing high quality, cost-effective modeling support for startups and small biotechs with limited in house resources.