(744e) Optimal Control for Predicting Drug Dosage in Superovulation Stage of in Vitro Fertilization | AIChE

(744e) Optimal Control for Predicting Drug Dosage in Superovulation Stage of in Vitro Fertilization

Authors 

Bhalerao, V., Jijamata Hospital, Nanded, India


In vitro fertilization (IVF) is one of the most highly pursued assisted reproductive technology worldwide. The IVF procedure is divided into four stages: Superovulation, Egg-retrieval, Insemination/Fertilization, Embryo transfer. Superovulation is the most crucial stage in IVF, since it involves external injection of hormones to stimulate development and maturation of multiple oocytes. The maximum amount of effort and money for IVF procedure goes into superovulation. Although numerous advancements have been made in IVF procedures, medication quality, etc little attention has been given to modifying the protocols based on a predictive model.

               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.

See more of this Session: Control In Medicine and Biology

See more of this Group/Topical: Computing and Systems Technology Division