Abstract
We determine an optimal protocol for temozolomide using population variability and dynamic optimization techniques inspired by artificial intelligence. We use a Pharmacokinetics/Pharmacodynamics (PK/PD) model based on Faivre and coauthors (Faivre, et al., 2013) for the pharmacokinetics of temozolomide, as well as the pharmacodynamics of its efficacy. For toxicity, which is measured by the nadir of the normalized absolute neutrophil count, we formalize the myelosuppression effect of temozolomide with the physiological model of Panetta and coauthors (Panetta, et al., 2003). We apply the model to a population with variability as given in Panetta and coauthors (Panetta, et al., 2003). Our optimization algorithm is a variant in the class of Monte-Carlo tree search algorithms. We do not impose periodicity constraint on our solution. We set the objective of tumor size minimization while not allowing more severe toxicity levels than the standard Maximum Tolerated Dose (MTD) regimen. The protocol we propose achieves higher efficacy in the sense that –compared to the usual MTD regimen– it divides the tumor size by approximately 7.66 after 336 days –the 95% confidence interval being [7.36–7.97]. The toxicity is similar to MTD. Overall, our protocol, obtained with a very flexible method, gives significant results for the present case of temozolomide and calls for further research mixing operational research or artificial intelligence and clinical research in oncology.
Highlights
One of the salient features of treatments in oncology is the persistent gap prevailing between standard drug regimens, corresponding to the official recommendation, and the actual drug regimens that are applied at bedside
Atkinson et al [4] perform a retrospective study on the drug regimens that have been administered to patients with metastatic renal cell cancer
The pharmacokinetics is identical for all patients, as in panel B of Fig 1 for the administration of the Maximum Tolerated Dose (MTD) protocol
Summary
One of the salient features of treatments in oncology is the persistent gap prevailing between standard drug regimens, corresponding to the official recommendation, and the actual drug regimens that are applied at bedside. Atkinson et al [4] perform a retrospective study on the drug regimens that have been administered to patients with metastatic renal cell cancer. They conclude that in a significant number of cases, alternative protocols have been administered at bedside due to the patient reaction to the standard protocol. These alternative regimens are found to deliver in some cases more favorable outcomes than the standard protocol. This gap between official recommendations and actual prescriptions.
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