For better quality of life (QoL) for the cancer patients, metronomic chemotherapy (MCT) would be the rational option instead of conventional chemotherapy. However, in view of the recent arguments regarding the accumulation of toxicity in MCT, it is worthwhile to examine the role of pathophysiological constraints in retarding the curative potential of MCT. Drug application is stopped upon attaining a certain high level of toxicity and subsequent resumption is possible once the toxicity drops below a certain low level. Large delays in subsequent drug administration can thus effectively handle toxicity and it may retard the therapeutic potential due to excessive tumour growth in the absence of drug. Small delays, on the other hand, may result in inoperable pathophysiological states resulting in poor QoL. It is argued that only the intervention of domain knowledge of an expert oncologist with respect to drug administration decision can in fact clinch the trade-off issues arising out of the situation in favour of a sustainable QoL. A mathematical model that may act as a general guideline to tackle the trade-off issues in cancer treatment is provided. Rigorous simulation exercises are required to establish the concept of MCT in the backdrop of conventional cancer treatment practices.

During the last few decades, conventional practices in medicine including oncology focus their interests towards the reductionism of molecular detailing and at the analytical level population-based assessment with stochastic principles, technically called 'evidence-based medicine', is generally practiced. Due to fluctuations in physiological parameters, the analysis and prediction of a therapeutic outcome in cancer on an individual level is uncertain. In recent times the well accepted opinion is that cancer should be looked upon as a systems disorder. This makes a paradigm shift - from a fragmented to a systems approach, linear to nonlinear methodology and from genome to physiome based analysis to understand the cancer. In the arena of systems biology, different groups have different views, namely, bottom-up (mechanistic), top-down (operational) and middle-out (rational). With respect to cancer each has a special relevance to serve the specific objectivity. In this article we have reviewed the views of the different schools, recent developments and controversies associated with the uncertainties in prediction of the therapeutic outcome of cancer. Recent advances in dynamical science and control theory may provide suitable analytical tools for capturing the uncertainties associated with cancer therapy through the development of middle-out rationalist (MORA) views.

Analytical models of tumor growth in the presence and absence of drug is important for studying the dynamics of treatment in oncology. In this paper, a time-variant state-space model is investigated. The model captures the inherent nonlinearity of the system. Physiological constraints of the system are considered in the model and controllability of the tumor load is examined. If it is possible to find a sequence of drug doses that can drive the tumor load to any arbitrary negligibly small final condition from any arbitrary initial condition in a given number of days without affecting the physiological state of the patient, the tumor is said to be controllable. Drug administration strategies like maximum tolerated dose, metronomic chemotherapy in the presence and absence of immunotherapy have been examined. It is found that low yet prolonged continuous dosing of drug along with tuning of biological factors may be a better workable strategy for positive treatment outcome.

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Different experimental models have substantially established that the anti-angiogenic (AAG)group of drugs are able to control the growth of tumor mass by cutting down the nutritive supply to the cancer cells. The mechanism of action of this group of drugs acts on the cells of the vascular endothelium. Recently, different AAG drugs have been in clinical trials. Initial clinical trials showed that application of AAG drugs produced different sorts of toxicity in patients,so calibration of the doses and drug application schedules are very important at present.Hence, development of analytical models would definitely help in this respect, particularly atthe individual level. The analytical model presented here may help to make a judicious choice of drug doses and drug schedule to control the growth of the tumor system under the condition of malignancy.