Lu En-Hsuan, Rusyn Ivan, Chiu Weihsueh A
Interdisciplinary Faculty of Toxicology and Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA.
J Toxicol Environ Health B Crit Rev. 2025 Jan 2;28(1):28-62. doi: 10.1080/10937404.2024.2412571. Epub 2024 Oct 10.
Regulatory dose-response assessments traditionally rely on data and default assumptions. New Approach Methods (NAMs) present considerable opportunities to both augment traditional dose-response assessments and accelerate the evaluation of new/data-poor chemicals. This review aimed to determine the potential utilization of NAMs through a unified conceptual framework that compartmentalizes derivation of toxicity values into five sequential Key Dose-response Modules (KDMs): (1) point-of-departure (POD) determination, (2) test system-to-human (e.g. inter-species) toxicokinetics and (3) toxicodynamics, (4) human population (intra-species) variability in toxicodynamics, and (5) toxicokinetics. After using several "traditional" dose-response assessments to illustrate this framework, a review is presented where existing NAMs, including , , and approaches, might be applied across KDMs. Further, the false dichotomy between "traditional" and NAMs-derived data sources is broken down by organizing dose-response assessments into a matrix where each KDM has Tiers of increasing precision and confidence: Tier 0: Default/generic values, Tier 1: Computational predictions, Tier 2: Surrogate measurements, and Tier 3: Direct measurements. These findings demonstrated that although many publications promote the use of NAMs in KDMs (1) for POD determination and (5) for human population toxicokinetics, the proposed matrix of KDMs and Tiers reveals additional immediate opportunities for NAMs to be integrated across other KDMs. Further, critical needs were identified for developing NAMs to improve dosimetry and quantify test system and human population toxicodynamics. Overall, broadening the integration of NAMs across the steps of dose-response assessment promises to yield higher throughput, less animal-dependent, and more science-based toxicity values for protecting human health.
传统的监管剂量反应评估依赖于数据和默认假设。新方法(NAMs)为增强传统剂量反应评估以及加速新的/数据匮乏化学品的评估提供了大量机会。本综述旨在通过一个统一的概念框架来确定NAMs的潜在用途,该框架将毒性值的推导划分为五个连续的关键剂量反应模块(KDMs):(1)起始点(POD)确定,(2)测试系统到人类(如种间)毒代动力学和(3)毒效动力学,(4)人群(种内)毒效动力学变异性,以及(5)毒代动力学。在使用几种“传统”剂量反应评估来说明该框架之后,本文对现有NAMs(包括[具体方法1]、[具体方法2]和[具体方法3]方法)可能如何应用于各个KDMs进行了综述。此外,通过将剂量反应评估组织成一个矩阵,打破了“传统”和NAMs衍生数据源之间的错误二分法,其中每个KDM都有精度和置信度不断提高的层级:第0层:默认/通用值,第1层:计算预测,第2层:替代测量,以及第3层:直接测量。这些结果表明,尽管许多出版物提倡在KDMs(1)中使用NAMs进行POD确定以及在(5)中用于人群毒代动力学,但所提出的KDMs和层级矩阵揭示了NAMs在其他KDMs中整合的更多直接机会。此外,确定了开发NAMs以改进剂量测定并量化测试系统和人群毒效动力学的关键需求。总体而言,在剂量反应评估的各个步骤中扩大NAMs的整合有望产生更高的通量、更少依赖动物且更基于科学的毒性值,以保护人类健康。