Pharmacokinetics and Pharmacodynamics of TAK-164 Antibody Drug Conjugate Coadministered with Unconjugated Antibody

效力 药代动力学 抗体-药物偶联物 药理学 药效学 抗体 分布(数学) 化学 药品 结合 单克隆抗体 医学 免疫学 体外 生物化学 数学分析 数学
作者
Bruna Menezes,Eshita Khera,Melissa C. Calopiz,Michael D. Smith,Michelle L. Ganno,Cornelius Cilliers,Adnan O. Abu‐Yousif,Jennifer J. Linderman,Greg M. Thurber
出处
期刊:Aaps Journal [Springer Nature]
卷期号:24 (6) 被引量:3
标识
DOI:10.1208/s12248-022-00756-4
摘要

The development of new antibody-drug conjugates (ADCs) has led to the approval of 7 ADCs by the FDA in 4 years. Given the impact of intratumoral distribution on efficacy of these therapeutics, coadministration of unconjugated antibody with ADC has been shown to improve distribution and efficacy of several ADCs in high and moderately expressed tumor target systems by increasing tissue penetration. However, the benefit of coadministration in low expression systems is less clear. TAK-164, an ADC composed of an anti-GCC antibody (5F9) conjugated to a DGN549 payload, has demonstrated heterogeneous distribution and bystander killing. Here, we evaluated the impact of 5F9 coadministration on distribution and efficacy of TAK-164 in a primary human tumor xenograft mouse model. Coadministration was found to improve the distribution of TAK-164 within the tumor, but it had no significant impact (increase or decrease) on efficacy. Experimental and computational evidence indicates that this was not a result of tumor saturation, increased binding to perivascular cells, or compensatory bystander effects. Rather, the cellular potency of DGN549 was matched with the single-cell uptake of TAK-164 making its IC50 close to its equilibrium binding affinity (KD), and as such, coadministration dilutes total DGN549 in cells below the maximum cytotoxic concentration, thereby offsetting an increased number of targeted cells with decreased ability to kill each cell. These results provide new insights on matching payload potency to ADC delivery to help identify when increasing tumor penetration is beneficial for improving ADC efficacy and demonstrate how mechanistic simulations can be leveraged to design clinically effective ADCs.
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