Effective dose window for containing tumor burden under tolerable level.

Area of Science:

• Mathematical oncology
• Cancer therapy modeling
• Tumor dynamics

Background:

• Maximum-tolerated dose (MTD) can promote drug resistance by eliminating sensitive cells.
• Adaptive therapy (AT) and dose modulation aim to control resistant populations by preserving sensitive cells.
• Individual patient variability complicates dose optimization for competitive stress.

Purpose of the Study:

• To introduce a mathematical model-driven approach for identifying an effective dose window (EDW).
• To define EDW as a dose range that maintains sufficient sensitive cells and controls tumor volume below a tolerable threshold (TTV).
• To explore patient-specific EDWs and minimal effective doses (MEDs) for cancer containment.

Main Methods:

• Developed a mathematical model of intratumor cell competition.
• Derived EDW based on TTV and competitive strength.
• Applied optimal control theory to determine the minimal dose for cancer containment.
• Validated the approach using longitudinal data from melanoma patients, including identifiability analysis.

Main Results:

• Demonstrated the existence of an EDW for cancer treatment.
• Identified patient-specific EDWs and minimal doses for melanoma patients with identifiable parameters.
• Showed that tumor volume can be contained at TTV using continuous dosing or AT within the EDW.
• Confirmed that the lower bound of the EDW approximates the MED for tumor containment.

Conclusions:

• An effective dose window (EDW) offers a strategy to manage cancer by balancing cell populations and tumor burden.
• Patient-specific EDWs and minimal effective doses (MEDs) can be deduced using mathematical modeling and real patient data.
• The EDW concept provides a framework for optimizing adaptive therapy and other dose modulation strategies to prevent resistance and control tumor growth.