Comparison of different methods for predicting customized drug dosage in superovulation stage of in-vitro fertilization

In-vitro fertilization (IVF) is one of the highly pursued assisted reproductive technologies (ARTs) worldwide. Superovulation is the most crucial stage in IVF, since it involves injection of hormones externally to stimulate development and maturation of multiple oocytes. A model for the follicular dynamics as a function of injected hormones and patient characteristics has been developed and validated in our previous studies. Using the same model as a predictive tool along with the application of optimal control principles; the optimal dose and frequency of medication customized for each patient is predicted. The objective of successful superovulation is to obtain maximum number of mature oocytes/follicles within a particular size range, which is translated into mathematical form by using concepts from normal distribution. The problem is solved by different optimal control methods like the maximum principle and discretized non-linear programming. The results from both the approaches are compared and their advantages are discussed.