Exploring trade-offs in drug administration for cancer treatment: A multi-criteria optimisation approach

This study addresses the combination of immunotherapy and chemotherapy in cancer treatment, recognising its promising effectiveness but highlighting the challenges of complex interactions between these therapeutic modalities. The central objective is to determine guidelines for the optimal administration of drugs, using an optimal control model that considers interactions in tumour dynamics, including cancer cells, the immune system, and therapeutic agents. The optimal control model is transformed into a multi-objective optimisation problem with treatment constraints. This is achieved by introducing adjustable trade-offs, allowing personalised adaptations in drug administration to achieve an optimal balance between established objectives. Various optimisation problems are addressed, considering two and three simultaneous objectives, such as optimising the number of cancer cells and the density of effector cells at the final treatment time. The diverse combinations presented reflect the model's flexibility in the face of multi-objective optimisation, providing a range of approaches to meet specific medical needs. The analysis of Pareto optimal fronts in in silico investigation offers an additional resource for decision-makers, enabling a more effective determination of the optimal administration of cytotoxic and immunotherapeutic agents. By leveraging an optimal control model, we have demonstrated the effectiveness of considering interactions in tumour dynamics, including the integration of immunotherapy and chemotherapy. Our findings underscore the importance of tailored treatment plans to achieve optimal outcomes, showcasing the versatility of our approach in addressing individual patient needs. The insights gained from our analysis offer valuable guidance for future research and clinical practice, paving the way for more effective and personalised cancer therapies.