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Feasibility of predicting regional lung exposure from systemic pharmacokinetic data of generic OIDPs via population pharmacokinetic modeling and non-compartmental approaches

Feasibility of predicting regional lung exposure from systemic pharmacokinetic data of generic OIDPs via population pharmacokinetic modeling and non-compartmental approaches
通过群体药代动力学模型和非房室方法根据仿制药 OIDP 的全身药代动力学数据预测局部肺暴露的可行性
批准号:
10797284
负责人:
Jurgen Bernd Bulitta
金额:
$25.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-01 至 2025-06-30

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Project Summary/Abstract Chronic respiratory tract diseases such as asthma are common and significantly affect the quality of patient lives. While effective and safe asthma medications are urgently needed, they pose a significant financial burden for patients. Moreover, the current regulatory pathway, the so-called “weight-of-evidence” approach, carries a considerable economic risk for generic drug developers. This presents an impediment for bringing cost-effective, safe and efficacious generic orally inhaled drug products (OIDPs) to the market. Therefore, systematically evaluating novel approaches that can reliably support the development and regulatory assessment of generic OIDPs is essential. This project will leverage innovative modeling and simulation strategies to evaluate whether population pharmacokinetic (PK) modeling and non-compartmental analysis (NCA) approaches based on plasma concentrations allow reliable conclusions on the bioequivalence of two OIDPS in the lung. Active pharmaceutical ingredients (APIs) with a range of physicochemical properties that are used in OIDPs will be studied through computer simulations. In Task 1, this project will develop lung physiologically-based PK (PBPK) models that can simulate both the local drug exposure profiles at different regions of the lung and plasma drug concentration profiles. These PBPK models will contain five or more lung compartments, reflecting the 23 physiological generations of the lung. Inhaled drug deposition in various lung regions will be implemented as a function of the particle size distribution. Further, the lung PBPK models will account for the total lung dose, dissolution kinetics, permeation, perfusion, as well as (for the upper airways) mucociliary clearance. These lung PBPK models will be used to simulate realistic plasma PK datasets for Test and Reference OIDPs with systematically varied properties, in the presence and absence of charcoal to block oral absorption. Simulated local drug exposure profiles at various regions of the lung will serve as the therapeutically relevant, true, pulmonary comparators. Studies in Task 2 will use the PBPK-simulated drug exposure profiles in plasma as relevant inputs. The main goal of this task is to probe whether, and with which level of granularity, population PK can detect differences in regional pulmonary exposure by modeling plasma concentration-time profiles of Test and Reference OIDPs. In addition to modeling pulmonary absorption via population PK, the less complex NCA with established and novel parameters (e.g. partial AUCs during the absorption phase) will be applied using the same data sets. This will allow one to compare the capabilities, strengths, weaknesses, and robustness of both approaches for detecting differences in regional pulmonary exposure. In Task 3, key findings across all simulated APIs, OIDPs, conditions, and study designs will be summarized to create robust and generalizable conclusions to support PK approaches and potential BE criteria for lung BE testing. In Task 4, the report, simulated datasets, PBPK, population PK and NCA models and results will be made available in an electronic database to the FDA.
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Novel Strategies for Antibiotic Combinations to Combat Gram-negative Superbugs
Novel Strategies for Antibiotic Combinations to Combat Gram-negative Superbugs
Combating resistant superbugs by understanding the molecular determinants of target site penetration and binding
  • 批准号:
    10219080
  • 项目类别:
  • 资助金额:
    $110.77万
  • 财政年份:
    2018
  • 负责人:
    Jurgen Bernd Bulitta
  • 依托单位:
Combating resistant superbugs by understanding the molecular determinants of target site penetration and binding
  • 批准号:
    9761971
  • 项目类别:
  • 资助金额:
    $113.46万
  • 财政年份:
    2018
  • 负责人:
    Jurgen Bernd Bulitta
  • 依托单位:
海外基金