Investigating Mathematical Hormone Models for Human Ovulation

Author(s)

Vanessa Montano

Faculty Mentor(s)

Brandy Wiegers (Mathematics)

Abstract

Polycystic Ovarian Syndrome (PCOS) is a hormone related health condition that impacts 10% of people who ovulate. This can cause problems with regular ovulation, fertility, and other aspects of biological systems in people who ovulate. As such, having a solid mathematical hormone model could lead to better understanding of PCOS, its impacts, and treatment. Unfortunately, many of the methematical hormone models available were created many decades ago. In reviewing previous and more recent work, we see opportunities to update the models to make the more inclusive and accurate. This work started by verifying the ovulation model created by Chen and Ward, providing a base computational model that shows the interaction of hormones in charge of human ovulation. The presentation will focus on the corrections made to this model and plans for further investigation into PCOS. The ulitmate goal is to develope more personal treatment plans for women based on models that account for the diversity in age, race, and other factors that could impact the overall hormone model.

Keywords: Mathematical Modeling, Hormone Modeling, Mathematical Biology

Presentation

5 thoughts on “Investigating Mathematical Hormone Models for Human Ovulation”

  1. Thank you for the nice presentation. I was curious about the significance of the “peaks” in this model and what they represented in terms of PCOS.

    1. The peaks are when the hormones are at their highest. This is when the follicles that were chosen to continue their growth result in the one follicle that will release an egg, thus ovulating. For people that have PCOS, this peak is not as apparent or not present at all.

  2. What new parameters are you thinking of adding to the models? Also, what are your early predictions for the results of varying the amounts of LH and FSH?

  3. I enjoyed your presentation. I also appreciate how passionate you are about this topic. Basing research off of a personalized topic seems like a great way to stay motivated, interested, and to be excited for your end goals.

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