Sex-Based Determinants of Metabolic Regulation for Predicting Disease Risk and Pharmacological Responses

Project lead

Sex differences critically shape the expression and activity of drug-metabolizing enzymes, giving rise to distinct metabolic profiles. These sex-dependent variations influence not only drug absorption, distribution, metabolism, and elimination, but also therapeutic efficacy and the likelihood of adverse drug reactions. Consequently, men and women often exhibit marked disparities in drug exposure, treatment outcomes, and adverse event incidence, ultimately affecting disease onset, progression, and therapeutic responsiveness. Nevertheless, such sex-related differences remain insufficiently recognized in clinical practice, leading some patients to receive suboptimal treatment strategies during early pharmacotherapy. As precision medicine advances, there is a growing need for predictive frameworks capable of prospectively identifying and characterizing these sex-specific differences to support more accurate drug selection and dose refinement.

The present study aims to systematically delineate how sex-specific factors and metabolic profiles influence pharmacokinetic and pharmacodynamic processes, and to uncover their mechanistic roles in disease progression and therapeutic outcomes. Building on these insights, we seek to develop a multidimensional modeling framework capable of prospectively predicting sex-related differences in drug response. To achieve this, we will integrate clinical drug concentration monitoring, metabolomics, proteomics, and genomics with high-dimensional association analyses, network reconstruction, and AI-driven modeling to construct high-fidelity virtual patient models. These models will enable precise simulation of sex-based variations in drug exposure–response dynamics and support the identification of potential differences in drug tolerance and individualized therapeutic windows. The framework has been validated using several drugs with well-documented sex differences, including immunosuppressants and cardiovascular therapies.

By modeling sex-specific differences in drug exposure, metabolic processing, and pharmacological effects, this study will provide a robust means of capturing the influence of sex on drug metabolism and pharmacodynamics, enabling earlier recognition of sex-dependent disparities in disease risk and therapeutic response. Through the integration of physiological-pharmacological mechanisms with advanced computational methodologies, this research aims to deliver clinically actionable predictive tools for sex-specific metabolic regulation, thereby improving early identification of high-risk individuals and informing the optimization of individualized therapeutic strategies.

Team

Xiang Chen

Luyao Han

Mingfeng Li

Qiang Zhang

Na Zhang

Hangjia Bai

Hao Liu

Feiyu Guo