A systems-based mathematical modelling framework for investigating the effect of drugs on solid tumours

Area of Science:

• Computational biology
• Systems biology
• Pharmacodynamics

Background:

• Drug effects in solid tumors are complex due to transport and non-linear cellular signaling.
• Existing systems frameworks struggle to address cellular complexities in tumor drug response.

Purpose of the Study:

• To develop a flexible modeling framework for simulating drug effects on solid tumors.
• To investigate how different intracellular signaling mechanisms influence tumor cell response to drugs.

Main Methods:

• Developed a skeletal modeling framework integrating interstitial drug transport, intracellular signal processing, and cell population dynamics.
• Incorporated modular intracellular signaling descriptions, including monostable and bistable switch models.
• Analyzed the impact of various drug stimuli and key parameters on tumor cell killing.

Main Results:

• The model successfully integrates drug transport and cellular response mechanisms.
• Both monostable and bistable intracellular signaling modules exhibited similar trends in cell killing.
• Identified key parameters influencing drug efficacy within the tumor microenvironment.

Conclusions:

• A predictive systems platform was created, capable of incorporating additional cellular complexity.
• Qualitatively different intracellular signaling models can produce similar responses to simple drug stimuli.
• Validation of intracellular models requires careful consideration of diverse drug stimuli.