Master of Science
Dr. Masahiro Sakagami
Dr. Jürgen Venitz
Dr. Patricia Slattum
There has been a desire to accurately interpret the inhaled pharmacokinetic (PK) profiles of drugs in humans to aid successful inhaled drug and product developments. However, challenges are layered, as 1) the drug dose delivered to the lung (DTL) from inhalers is a portion of the formulated dose but rarely determined; 2) lung delivery and regional deposition differ, depending on drug, formulation and inhaler; 3) drugs are not only absorbed from the lung but may also be from the gastrointestinal (GI) tract; and 4) in addition to absorption into the systemic circulation, multiple non-absorptive processes also eliminate drugs from the lung, such as mucociliary clearance, metabolism, phagocytosis and tissue binding. Hence, this thesis project aims to develop new lung disposition model-based analyses to derive the meaningful kinetic descriptors for lung disposition from inhaled PK profiles in humans.
Two approaches, curve fitting- and moment-based approaches, were developed. Both approaches modeled the kinetics of lung disposition rate-controlled by absorption (ka) and non-absorptive loss (knal), assuming no contribution of GI absorption. An exhaustive literature review found necessary data sets for three drugs, tobramycin, calcitonin and ciprofloxacin. In the curve fitting-based approach, each inhaled PK profile was fitted to the lung disposition model, while the DTL was obtained from corresponding -scintigraphic lung deposition and the kinetic parameters of systemic disposition were fixed by separate intravenous PK profile model analysis. In the moment analysis-based approach, the mean lung residence times (MLRT) and the DTL-based bioavailability (FL) were estimated and used to determine the ka and knal values in the lung disposition model, given FL = MLRTka = ka/(ka+knal). The ka and knal values were successfully derived for all the three drugs delivered by dry powder inhalers (DPIs) and/or nebulizers (NEB) through both approaches. Their “goodness-of-fit” was reasonably satisfactory.
The ka values appeared to be primarily described by partition-based diffusion affected by the three hydrophilic drug’s molecular weight. In contrast, the knal values differed, yet appeared to become plausible, with a notion of additional non-absorptive confoundedness due to lung tissue binding (tobramycin) and metabolism (calcitonin), in addition to mucociliary clearance. The ka and knal values derived by the two approaches were comparable in majority of the cases.
The success of these PK modeling analyses enabled further attempts to identify most influential attributes by simulation. The systemic PK and lung exposure profiles were predicted by simulation upon ±20 % changes in each of the DTL, ka and knal values to examine changes in the systemic PK metrics (Cmax, AUC and Tmax) and local lung exposure metrics (AUClung and LRT0.5). For all three drugs, the Cmax and AUC changes were identical to changes in the DTL without changing the Tmax. In contrast, impacts of the ka and knal changes differed between drugs, depending on the relative contribution of the rate constant to their sum (ka+knal). It appeared that the major contributor of the sum (ka+knal) was that rate-controlling the kinetics of lung disposition.
In conclusion, this thesis project has successfully proposed two new approaches of curve fitting and moment-based analysis by accurately deriving the kinetic descriptors of lung disposition (ka and knal) for three drugs from the inhaled PK profiles in humans. Their applications were extended to predict likely changes in the systemic PK and local lung exposure metrics by simulation. While attempts should continue with more drugs, these approaches are believed to be useful in identifying critical attributes to determine the lung disposition kinetics and thus predicting the lung kinetic behavior and systemic PK profiles of new drug entities in humans.
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