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The hypothalamic-pituitary-adrenal (HPA) axis is a major system maintaining body homeostasis by regulating the neuroendocrine and sympathetic nervous systems as well modulating immune function. Recent work has shown that the complex dynamics of this system accommodate several stable steady states, one of which corresponds to the hypocortisol state observed in patients with chronic fatigue syndrome (CFS). At present these dynamics are not formally considered in the development of treatment strategies. Here we use model-based predictive control (MPC) methodology to estimate robust treatment courses for displacing the HPA axis from an abnormal hypocortisol steady state back to a healthy cortisol level. This approach was applied to a recent model of HPA axis dynamics incorporating glucocorticoid receptor kinetics. A candidate treatment that displays robust properties in the face of significant biological variability and measurement uncertainty requires that cortisol be further suppressed for a short period until adrenocorticotropic hormone levels exceed 30% of baseline. Treatment may then be discontinued, and the HPA axis will naturally progress to a stable attractor defined by normal hormone levels. Suppression of biologically available cortisol may be achieved through the use of binding proteins such as CBG and certain metabolizing enzymes, thus offering possible avenues for deployment in a clinical setting. Treatment strategies can therefore be designed that maximally exploit system dynamics to provide a robust response to treatment and ensure a positive outcome over a wide range of conditions. Perhaps most importantly, a treatment course involving further reduction in cortisol, even transient, is quite counterintuitive and challenges the conventional strategy of supplementing cortisol levels, an approach based on steady-state reasoning.

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A dynamic systems model was used to generate parameters describing a phenotype of Hypothalamic–Pituitary–Adrenal (HPA) behavior in a sample of 36 patients with chronic fatigue syndrome (CFS) and/ or fibromyalgia (FM) and 36 case-matched healthy controls. Altered neuroendocrine function, particularly in relation to somatic symptoms and poor sleep quality, may contribute to the pathophysiology of these disorders. Blood plasma was assayed for cortisol and ACTH every 10 min for 24 h. The dynamic model was specified with an ordinary differential equation using three parameters: (1) ACTH-adrenal signaling, (2) inhibitory feedback, and (3) non-ACTH influences. The model was ‘‘personalized’’ by estimating an individualized set of parameters from each participant’s data. Day and nighttime parameters were assessed separately. Two nocturnal parameters (ACTH-adrenal signaling and inhibitory feedback) significantly differentiated the two patient subgroups (“fatigue-predominant” patients with CFS only versus ‘‘pain-predominant’’ patients with FM and comorbid chronic fatigue) from controls (allp’s < .05), whereas daytime parameters and diurnal/nocturnal slopes did not. The same nocturnal parameters were significantly associated with somatic symptoms among patients (p’s < .05). There was a significantly different pattern of association between nocturnal non-ACTH influences and sleep quality among patients versus controls (p < .05). Although speculative, the finding that patient somatic symptoms decreased when more cortisol was produced per unit ACTH, is consistent with cortisol’s anti-inflammatory and sleep-modulatory effects. Patients’ HPA systems may compensate by promoting more rapid or sustained cortisol production. Mapping “behavioral phenotypes” of stress–arousal systems onto symptom clusters may help disentangle the pathophysiology of complex disorders with frequent comorbidity.