An Optimal Control Framework for the Automated Design of Personalized Cancer Treatments

Area of Science:

• Computational oncology
• Systems biology
• Control theory applications in medicine

Background:

• Personalized cancer treatment remains a challenge, necessitating advanced computational strategies.
• Control theory offers a robust framework for therapy design and optimization.
• Existing clinical practices often overlook individual physiological heterogeneity.

Purpose of the Study:

• Introduce the Control Theory for Therapy Design (CT4TD) framework for personalized cancer treatment.
• Develop optimized therapeutic strategies by integrating patient-specific pharmacokinetic (PK) and pharmacodynamic (PD) models.
• Adapt and adjust cancer therapies based on individual patient data and treatment responses.

Main Methods:

• Employing optimal control theory on patient-specific PK/PD models.
• Utilizing the dCRAB/RedCRAB optimization algorithm for scalability and efficiency.
• Developing personalized administration strategies to achieve target drug concentrations and minimize toxicity.
• Adjusting ongoing therapies using simplified cancer population dynamics models to control tumor burden.

Main Results:

• CT4TD enables optimized, personalized drug administration strategies at diagnosis.
• The framework allows for dynamic adjustment of therapies using longitudinal patient data.
• Demonstrated efficacy in a proof-of-principle application to Imatinib treatment for Chronic Myeloid Leukemia.
• Optimized strategies showed patient-specific diversification and improvements over standard regimens.

Conclusions:

• CT4TD provides a scalable and robust computational framework for personalized cancer therapy.
• The approach effectively integrates PK/PD modeling and control theory for optimized treatment outcomes.
• CT4TD has broad applicability across various cancer therapies and administration protocols.
• This framework represents a significant advancement in supporting clinical decision-making for personalized cancer treatment.