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
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
中文摘要
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英文摘要
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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