Polycystic Ovary Syndrome and the Imperative for Personalized Dosing: Bridging the Gap Between Phenotypic Heterogeneity and Individualized Pharmacotherapy

Abstract

Polycystic ovary syndrome (PCOS) is a prevalent, complex endocrinopathy associated with reproductive, metabolic and psychological manifestations, and available treatment is still largely empirical and “one size fits all”. This is a narrative review of the pathophysiological and clinical spectrum of PCOS and current therapeutic approaches with a personalized dosing approach. The Rotterdam criteria (A-D) describe and illustrate a very broad spectrum of phenotypes in women with PCOS that are characterized by different degrees of androgen excess, ovulatory dysfunction, and metabolic risk, but current guidelines for treatment for metformin, ovulation induction agents, combined oral contraceptive, anti-androgens, inositols, and emerging GLP 1 receptor agonists or SGLT2 inhibitors do not cover this spectrum. There are multiple validated biomarkers that contribute to disease expression and drug response (such as HOMA IR, anti Müllerian hormone, total testosterone, sex hormone binding globulin, free androgen index) but do not form part of the dose selection or dose titration protocols. The lack of phenotype stratified dose-finding trials, no biomarker-guided titration algorithms, low level of attention to ethnic and anthropometric considerations and no clinically used AI tools to assist with dose optimisation are all critical gaps across domains. These gaps will be addressed with a set of four pillars: a phenotypic drug selection, biomarker-based dose titration, pharmacogenomic profiling in treatment resistant cases, and the creation of AI-supported clinical decision tools. The use of adequately powered PCOS phenotype-stratified randomised trials and real-world, inclusive datasets, within the framework of this strategy, represents a realistic way to move towards precision-based care and minimise treatment failure, side effects and long term cardiometabolic risk in the large PCOS patient population.