There is an urgent need (recognized in FDA guidance, 2018) to optimize the dose of medicines given to patients for maximal drug efficacy and limited toxicity (precision dosing), which can be facilitated by quantitative systems pharmacology (QSP) models. Accurate quantification of proteins involved in drug clearance is essential to build and improve QSP models for any target population. Here we describe application of label-free proteomics in microsomes from 23 human livers to simultaneously quantify 188 enzymes and 66 transporters involved in xenobiotic disposition, including 17 cytochrome P450s (CYPs), 10 UDP-glucuronosyltransferases (UGTs), 7 ATP-binding cassette (ABC) transporters, and 11 solute carrier (SLC) transporters; six of these proteins are quantified for the first time. The methodology allowed quantification of thousands of proteins, allowing estimation of sample purity and understanding of global patterns of protein expression. There was overall good agreement with targeted quantification and enzyme activity data, where this was available. The effects of sex, age, genotype, and BMI on enzyme and transporter expression were assessed. Decreased expression of enzymes and transporters with increasing BMI was observed, but a tendency for older donors to have higher BMIs may have confounded this result. The effect of genotype on enzymes expression was, however, clear-cut, with CYP3A5*1/*3 genotype expressed 16-fold higher compared with its mostly inactive *3/*3 counterpart. Despite the complex, time-consuming data analysis required for label-free methodology, the advantages of label-free method make it a valuable approach to populate a broad range of system parameters simultaneously for target patients within pharmacology and toxicology models.