It is essential that fertility treatment is individualized based on a thorough diagnostic work-up, with treatment tailored to the patients' requirements. This individualization should be kept in mind during the main decision points that occur before and during treatment. Treatment customization must include consideration of both the woman and her partner involved in the process together, including their collective treatment goals. Once treatment goals have been agreed and diagnostic evaluations performed, personalization based on patient characteristics, together with an understanding of treatment goals and patient preferences, enables the selection of appropriate treatments, protocols, products and their dosing. Following treatment initiation, monitoring and adaptation of product and dose can then ensure optimal outcomes. Currently, it is not possible to base treatment decisions on every characteristic of the patient and personalization is based on biomarkers that have been identified as the most relevant. However, in the future, the use of artificial intelligence coupled with continuous monitoring should enable greater individualization and improve outcomes. This review considers the current state-of-the-art related to decision points during individualized treatment of female infertility, before looking at future developments that might further assist in making individualized treatment decisions, including the use of computer-assisted decision making.
Keywords: ART; Gonadotropin; decision points; personalized medicine; treatment algorithm.