Purpose of Review The pharmacokinetic (PK) and pharmacodynamic (PD) profile of antibody-drug conjugates (ADCs) is complex due to combined large- and small-molecule features, and traditional in vivo PK/PD studies are time-consuming and costly. In recent years, there has been growing emphasis on leveraging in vitro data to predict in vivo behaviors. This review aims to illustrate examples of such approaches in ADC development, describe the key methodologies employed, and discuss both the limitations of current in vitro parameters and the emergence of novel in vitro testing systems. Recent Findings In vitro to in vivo extrapolation (IVIVE) serves as the predominant strategy for predicting the in vivo behavior of ADCs using in vitro parameters. These approaches are widely utilized to predict the distribution of ADCs and their components, evaluate clinical efficacy and optimize dosing regimens, provide mechanistic insights for drug design optimization, and assess drug-drug interaction(DDI) risks. Methodologically, IVIVE is implemented through two primary approaches. First, via strict physiological scaling, where the parameters are extrapolated to organism-level values, and second, by directly utilizing the in vitro parameters as model inputs. Meanwhile, allometric scaling provides an addition empirical translation approach. Nevertheless, due to the unique mechanisms of action and structural complexity of ADCs, parameters obtained from traditional in vitro assays may deviate from actual in vivo conditions. The advancements in novel in vitro technologies, such as organ-on-a-chip and 3D organoid systems, have helped bridge the gap. Studies have demonstrated that integrating data derived from these advanced in vitro systems into predictive models can significantly enhance model performance and translational reliability. Summary In the development of ADCs, predicting the in vivo behavior based on in vitro parameters has become an important supportive strategy. This review systematically summarizes how in vitro parameters are used to predict the in vivo PK/PD properties, assess DDI risks, and guide the optimization of drug design, drawing on published research examples to illustrate the application and outcomes. Furthermore, allometric scaling, though empirical, complements as a translational tool. While traditional in vitro systems still have constraints, the advancement of novel in vitro technologies will further enhance the accuracy of such predictive methods. Graphical Abstract

Translational Approaches for Human Pharmacokinetics and Pharmacodynamics Prediction of Antibody-drug Conjugates: Bridging Complexity from Bench to Bedside

期刊论文
发表日期：

2026年2月17日

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Wenhang Xu,
Chaohsuan Pan,
Qingfeng He,
Xiao Zhu,
Xiaoqiang Xiang

摘要

Purpose of Review

The pharmacokinetic (PK) and pharmacodynamic (PD) profile of antibody-drug conjugates (ADCs) is complex due to combined large- and small-molecule features, and traditional in vivo PK/PD studies are time-consuming and costly. In recent years, there has been growing emphasis on leveraging in vitro data to predict in vivo behaviors. This review aims to illustrate examples of such approaches in ADC development, describe the key methodologies employed, and discuss both the limitations of current in vitro parameters and the emergence of novel in vitro testing systems.

Recent Findings

In vitro to in vivo extrapolation (IVIVE) serves as the predominant strategy for predicting the in vivo behavior of ADCs using in vitro parameters. These approaches are widely utilized to predict the distribution of ADCs and their components, evaluate clinical efficacy and optimize dosing regimens, provide mechanistic insights for drug design optimization, and assess drug-drug interaction(DDI) risks. Methodologically, IVIVE is implemented through two primary approaches. First, via strict physiological scaling, where the parameters are extrapolated to organism-level values, and second, by directly utilizing the in vitro parameters as model inputs. Meanwhile, allometric scaling provides an addition empirical translation approach. Nevertheless, due to the unique mechanisms of action and structural complexity of ADCs, parameters obtained from traditional in vitro assays may deviate from actual in vivo conditions. The advancements in novel in vitro technologies, such as organ-on-a-chip and 3D organoid systems, have helped bridge the gap. Studies have demonstrated that integrating data derived from these advanced in vitro systems into predictive models can significantly enhance model performance and translational reliability.

Summary

In the development of ADCs, predicting the in vivo behavior based on in vitro parameters has become an important supportive strategy. This review systematically summarizes how in vitro parameters are used to predict the in vivo PK/PD properties, assess DDI risks, and guide the optimization of drug design, drawing on published research examples to illustrate the application and outcomes. Furthermore, allometric scaling, though empirical, complements as a translational tool. While traditional in vitro systems still have constraints, the advancement of novel in vitro technologies will further enhance the accuracy of such predictive methods.

Graphical Abstract