The development of optimal treatment regimens in tuberculosis (TB) remains challenging due to the need of combination therapy and possibility of pharmacodynamic (PD) interactions. Preclinical information about PD interactions needs to be used more optimally when designing early bactericidal activity (EBA) studies. In this work, we developed a translational approach which can allow for forward translation to predict efficacy of drug combination in EBA studies using the Multistate Tuberculosis Pharmacometric (MTP) and the General Pharmacodynamic Interaction (GPDI) models informed by in vitro static time‐kill data. These models were linked with translational factors to account for differences between the in vitro system and humans. Our translational MTP‐GPDI model approach was able to predict the EBA_{0–2 days}, EBA_{0–5 days}, and EBA_{0–14 days} from different EBA studies of rifampicin and isoniazid in monotherapy and combination. Our translational model approach can contribute to an optimal dose selection of drug combinations in early TB clinical trials.

中文翻译：

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在早期临床开发中选择结核病药物组合方案的转化模型知情方法。

由于需要联合治疗和药效学 (PD) 相互作用的可能性，结核病 (TB) 最佳治疗方案的开发仍然具有挑战性。在设计早期杀菌活性 (EBA) 研究时，需要更优化地使用有关 PD 相互作用的临床前信息。在这项工作中，我们开发了一种翻译方法，该方法可以使用多态结核药效学 (MTP) 和一般药效学相互作用 (GPDI) 模型，通过体外静态时间杀伤数据来预测 EBA 研究中药物组合的疗效. 这些模型与翻译因子相关联，以解释体外模型之间的差异系统和人。我们的转化 MTP-GPDI 模型方法能够从利福平和异烟肼单药和联合用药的不同 EBA 研究中预测 EBA _{0-2 天}、EBA _{0-5 天和}EBA _{0-14 天。}我们的转化模型方法有助于在早期结核病临床试验中对药物组合进行最佳剂量选择。