@article{gavina_reyes_olufsen_lenhart_ottesen_2023, title={Toward an optimal contraception dosing strategy}, volume={19}, ISSN={["1553-7358"]}, DOI={10.1371/journal.pcbi.1010073}, abstractNote={Anovulation refers to a menstrual cycle characterized by the absence of ovulation. Exogenous hormones such as synthetic progesterone and estrogen have been used to attain this state to achieve contraception. However, large doses are associated with adverse effects such as increased risk for thrombosis and myocardial infarction. This study utilizes optimal control theory on a modified menstrual cycle model to determine the minimum total exogenous estrogen/progesterone dose, and timing of administration to induce anovulation. The mathematical model correctly predicts the mean daily levels of pituitary hormones LH and FSH, and ovarian hormones E2, P4, and Inh throughout a normal menstrual cycle and reflects the reduction in these hormone levels caused by exogenous estrogen and/or progesterone. Results show that it is possible to reduce the total dose by 92% in estrogen monotherapy, 43% in progesterone monotherapy, and that it is most effective to deliver the estrogen contraceptive in the mid follicular phase. Finally, we show that by combining estrogen and progesterone the dose can be lowered even more. These results may give clinicians insights into optimal formulations and schedule of therapy that can suppress ovulation.}, number={4}, journal={PLOS COMPUTATIONAL BIOLOGY}, author={Gavina, Brenda Lyn A. and Reyes, V. Aurelio A. and Olufsen, Mette and Lenhart, Suzanne and Ottesen, Johnny}, year={2023}, month={Apr} }
 @article{geddes_ottesen_mehlsen_olufsen_2022, title={Postural orthostatic tachycardia syndrome explained using a baroreflex response model}, volume={19}, ISSN={["1742-5662"]}, DOI={10.1098/rsif.2022.0220}, abstractNote={Patients with postural orthostatic tachycardia syndrome (POTS) experience an excessive increase in heart rate (HR) and low-frequency (∼0.1 Hz) blood pressure (BP) and HR oscillations upon head-up tilt (HUT). These responses are attributed to increased baroreflex (BR) responses modulating sympathetic and parasympathetic signalling. This study uses a closed-loop cardiovascular compartment model controlled by the BR to predict BP and HR dynamics in response to HUT. The cardiovascular model predicts these quantities in the left ventricle, upper and lower body arteries and veins. HUT is simulated by letting gravity shift blood volume (BV) from the upper to the lower body compartments, and the BR control is modelled using set-point functions modulating peripheral vascular resistance, compliance, and cardiac contractility in response to changes in mean carotid BP. We demonstrate that modulation of parameters characterizing BR sensitivity allows us to predict the persistent increase in HR and the low-frequency BP and HR oscillations observed in POTS patients. Moreover, by increasing BR sensitivity, inhibiting BR control of the lower body vasculature, and decreasing central BV, we demonstrate that it is possible to simulate patients with neuropathic and hyperadrenergic POTS.}, number={193}, journal={JOURNAL OF THE ROYAL SOCIETY INTERFACE}, author={Geddes, Justen R. and Ottesen, Johnny T. and Mehlsen, Jesper and Olufsen, Mette S.}, year={2022}, month={Aug} }
 @article{williams_brady_gilmore_gremaud_tran_ottesen_mehlsen_olufsen_2019, title={Cardiovascular dynamics during head-up tilt assessed via pulsatile and non-pulsatile models}, volume={79}, ISSN={0303-6812 1432-1416}, url={http://dx.doi.org/10.1007/s00285-019-01386-9}, DOI={10.1007/s00285-019-01386-9}, abstractNote={This study develops non-pulsatile and pulsatile models for the prediction of blood flow and pressure during head-up tilt. This test is used to diagnose potential pathologies within the autonomic control system, which acts to keep the cardiovascular system at homeostasis. We show that mathematical modeling can be used to predict changes in cardiac contractility, vascular resistance, and arterial compliance, quantities that cannot be measured but are useful to assess the system's state. These quantities are predicted as time-varying parameters modeled using piecewise linear splines. Having models with various levels of complexity formulated with a common set of parameters, allows us to combine long-term non-pulsatile simulations with pulsatile simulations on a shorter time-scale. We illustrate results for a representative subject tilted head-up from a supine position to a [Formula: see text] angle. The tilt is maintained for 5 min before the subject is tilted back down. Results show that if volume data is available for all vascular compartments three parameters can be identified, cardiovascular resistance, vascular compliance, and ventricular contractility, whereas if model predictions are made against arterial pressure and cardiac output data alone, only two parameters can be estimated either resistance and contractility or resistance and compliance.}, number={3}, journal={Journal of Mathematical Biology}, publisher={Springer Science and Business Media LLC}, author={Williams, Nakeya D. and Brady, Renee and Gilmore, Steven and Gremaud, Pierre and Tran, Hien T. and Ottesen, Johnny T. and Mehlsen, Jesper and Olufsen, Mette S.}, year={2019}, month={May}, pages={987–1014} }
 @article{olsen_ottesen_smith_olufsen_2019, title={Parameter subset selection techniques for problems in mathematical biology}, volume={113}, ISSN={["1432-0770"]}, DOI={10.1007/s00422-018-0784-8}, abstractNote={Patient-specific models for diagnostics and treatment planning require reliable parameter estimation and model predictions. Mathematical models of physiological systems are often formulated as systems of nonlinear ordinary differential equations with many parameters and few options for measuring all state variables. Consequently, it can be difficult to determine which parameters can reliably be estimated from available data. This investigation highlights pitfalls associated with practical parameter identifiability and subset selection. The latter refer to the process associated with selecting a subset of parameters that can be identified uniquely by parameter estimation protocols. The methods will be demonstrated using five examples of increasing complexity, as well as with patient-specific model predicting arterial blood pressure. This study demonstrates that methods based on local sensitivities are preferable in terms of computational cost and model fit when good initial parameter values are available, but that global methods should be considered when initial parameter value is not known or poorly understood. For global sensitivity analysis, Morris screening provides results in terms of parameter sensitivity ranking at a much lower computational cost.}, number={1-2}, journal={BIOLOGICAL CYBERNETICS}, author={Olsen, Christian Haargaard and Ottesen, Johnny T. and Smith, Ralph C. and Olufsen, Mette S.}, year={2019}, month={Apr}, pages={121–138} }