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- 2012 AIChE Annual Meeting
- Computing and Systems Technology Division
- Control In Medicine and Biology
- (744e) Optimal Control for Predicting Drug Dosage in Superovulation Stage of in Vitro Fertilization
A model for the follicle growth dynamics and number as a function of the injected hormones and patient characteristics is developed. The modeling basics are adapted from batch crystallization moment model, since moments are representatives of specific properties like number, shape and size of the particles under consideration. Based on this model, the dosage of the hormones to stimulate multiple ovulation or follicle growth is predicted by using the theory of optimal control. The objective of successful superovulation is to obtain maximum number of mature oocytes/follicles within a particular size range. Using the mathematical model involving follicle growth dynamics and the optimal control theory, optimal dose and frequency of medication is predicted for obtaining the desired result. The model will be modified to consider the sources of uncertainty due to patient’s age, previous medical history, suitability of medicine and protocol used. The optimal drug delivery regime predicted in the presence of uncertainty will be compared to the current dosage regime predicted.
Thus, a phenomenon currently based on trial and error will get a supportive basis to start with. This will aid as a predictive tool for medical professionals and provide them with a specific dosage strategy for a patient. This will bring down the probability of failure, decrease cost of complex monitoring and excess medication. Thus, it will decrease the overall cost of IVF treatment for the patient as well as the physician.