Adaptive control methods for the dose individualisation of anticancer agents

Numerous studies have found a clear relationship between systemic exposure and the toxicity or (more rarely) the efficacy of anticancer agents. Moreover, the clearance of most of these drugs differs widely between patients. These findings, combined with the narrow therapeutic index of anticancer drugs, suggest that patient outcome would be improved if doses were individualised to achieve a target systemic exposure. Bayesian maximum a posteriori probability (MAP) forecasting is an efficient and robust method for the optimisation of drug therapy, but its use for anticancer drugs is not yet extensive. The aim of this paper is to review the application of population pharmacokinetics and MAP to anticancer drugs and to evaluate whether and when MAP Bayesian estimation improves the clinical benefit of anticancer chemotherapy. For each drug, the relationships between pharmacokinetic variables [e.g. plasma concentration or the area under the concentration-time curve] and pharmacodynamic effects are described. Secondly, the methodologies employed are considered and, finally, the results are analysed in terms of predictive performance as well as, where possible, the impact on clinical end-points. Some studies were retrospective and intended only to evaluate individual pharmacokinetic parameter values using very few blood samples. Among the prospective trials, a few studied the pharmacokinetic/pharmacodynamic relationships which provided the basis for routine pharmacokinetic monitoring. Others were performed in clinical context where MAP Bayesian estimation was used to determine maximum tolerated systemic exposure (e.g. for carboplatin, topotecan, teniposide) or for pharmacokinetic monitoring (e.g. for methotrexate or platinum compounds). Indeed, its flexibility in blood sampling times makes this technique much more applicable than other limited sampling strategies. These examples demonstrate that individual dose adjustment helps manage toxicity. The performance of pharmacokinetic monitoring is linked to the methodology used at each step of its design and application. Moreover, a limitation to the use of pharmacokinetic monitoring for certain anticancer drugs has been the difficulty in obtaining pharmacokinetic or pharmacodynamic data. Recent progress in analytical methods, as well as the development of noninvasive methods (such as positron emission tomography) for evaluating the effects of chemotherapy, will help to define pharmacokinetic-pharmacodynamic relationships. Bayesian estimation is the strategy of choice for performing pharmacokinetic studies, as well as ensuring that a given patient benefits from the desired systemic exposure. Together, these methods could contribute to improving cancer chemotherapy in terms of patient outcome and survival.