So happy that my group has formally stepped into the field of global proteomics - recently we have published a research article at the AAPS Journal, which we used a LC/MS based global proteomics approach to quantify the absolute abundance of several pharmacological targets involved in target-mediated drug disposition (TMDD) for small molecules (https://pubmed.ncbi.nlm.nih.gov/41495534/) 

TMDD class effect with remarkably similar nonlinear PK behaviors has been reported in several classes of small molecule drugs. We anticipated that the occurrence of TMDD class effect might be due to their target capacities falling within a specific range, where nonlinear PK mediated by target binding are more likely to be evident.  In line with our hypothesis, our proteomics result suggests that TMDD is more likely to be observed when a target's capacity is between 1000 nmol and 10000 nmol, which corresponds to nonlinear PK at doses of 1-10 mg for a compound with a molecular weight of 400 g/mol. 

Our study highlights the importance of early target quantification and provides valuable insights into predicting unusual nonlinear PK caused by TMDD. Additionally, this proteomics-based approach for quantifying absolute target capacity could serve as a valuable tool for both industry and academic researchers in investigating other pharmacological targets.

Big congratulations to my former student Min Xu, who worked extremely hard on this project and is the first author of the paper; as well as several other co-authors, including former member Thanh Bach, current lab members Xuanzhen Yuan, Peizhi Li, and our collaborator Dr. Haojie Zhu from U of Michigan. 

The data presented in our paper are absolutely precious. Why? Because it took tremendous effort to gather - the high-end LC/MS instruments in the proteomics core were broken twice… water pipe leakage from the ceiling damaged our vacuum concentrator and the samples in it… etc, etc, and we had to redo experiments, rerun samples, reprepare samples, switching DIA to DDA due to instrument change, switching software due to DIA/DDA change… 

So, this paper is not only special to Min, but also to the whole group, as it reminds us that valuable experimental data requires tremendous effort to obtain, and we should never take it for granted (we pharmacometricians often forget this part because usually data are directly fed to us). 

(An, 2/19/2026)