Understanding the suitability of established antibiotics for oral inhalation from a pharmacokinetic perspective: an integrated model-based investigation based on rifampicin, ciprofloxacin and tigecycline in vivo data.

BACKGROUND: Treating pulmonary infections by administering drugs via oral inhalation represents an attractive alternative to usual routes of administration. However, the local concentrations after inhalation are typically not known and the presumed benefits are derived from experiences with drugs specifically optimized for inhaled administration. OBJECTIVES: A physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model was developed to elucidate the pulmonary PK for ciprofloxacin, rifampicin and tigecycline and link it to bacterial PK/PD models. An exemplary sensitivity analysis was performed to potentially guide drug optimization regarding local efficacy for inhaled antibiotics. METHODS: Detailed pulmonary tissue, endothelial lining fluid and systemic in vivo drug concentration-time profiles were simultaneously measured for all drugs in rats after intravenous infusion. Using this data, a PBPK/PD model was developed, translated to humans and adapted for inhalation. Simulations were performed comparing potential benefits of oral inhalation for treating bronchial infections, covering intracellular pathogens and bacteria residing in the bronchial epithelial lining fluid. RESULTS: The PBPK/PD model was able to describe pulmonary PK in rats. Often applied optimization parameters for orally inhaled drugs (e.g. high systemic clearance and low oral bioavailability) showed little influence on efficacy and instead mainly increased pulmonary selectivity. Instead, low permeability, a high epithelial efflux ratio and a pronounced post-antibiotic effect represented the most impactful parameters to suggest a benefit of inhalation over systemic administration for locally acting antibiotics. CONCLUSIONS: The present work might help to develop antibiotics for oral inhalation providing high pulmonary concentrations and fast onset of exposure coupled with lower systemic drug concentrations.

Population Pharmacokinetics of Busulfan and Its Metabolite Sulfolane in Patients with Myelofibrosis Undergoing Hematopoietic Stem Cell Transplantation.

For patients with myelofibrosis, allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the only curative treatment to date. Busulfan-based conditioning regimens are commonly used, although high inter-individual variability (IIV) in busulfan drug exposure makes individual dose selection challenging. Since data regarding the IIV in patients with myelofibrosis are sparse, this study aimed to develop a population pharmacokinetic (PopPK) model of busulfan and its metabolite sulfolane in patients with myelofibrosis. The influence of patient-specific covariates on the pharmacokinetics of drug and metabolite was assessed using non-linear mixed effects modeling in NONMEM®. We obtained 523 plasma concentrations of busulfan and its metabolite sulfolane from 37 patients with myelofibrosis. The final model showed a population clearance (CL) and volume of distribution (Vd) of 0.217 L/h/kg and 0.82 L/kg for busulfan and 0.021 L/h/kg and 0.65 L/kg for its metabolite. Total body weight (TBW) and a single-nucleotide polymorphism of glutathione-S-transferase A1 (GSTA1 SNP) displayed a significant impact on volume of distribution and metabolite clearance, respectively. This is the first PopPK-model developed to describe busulfan's pharmacokinetics in patients with myelofibrosis. Incorporating its metabolite sulfolane into the model not only allowed the characterization of the covariate relationship between GSTA1 and the clearance of the metabolite but also improved the understanding of busulfan's metabolic pathway.

Pharmacokinetics and Pharmacodynamics of Tedizolid.

Tedizolid is an oxazolidinone antibiotic with high potency against Gram-positive bacteria and currently prescribed in bacterial skin and skin-structure infections. The aim of the review was to summarize and critically review the key pharmacokinetic and pharmacodynamic aspects of tedizolid. Tedizolid displays linear pharmacokinetics with good tissue penetration. In in vitro susceptibility studies, tedizolid exhibits activity against the majority of Gram-positive bacteria (minimal inhibitory concentration [MIC] of ≤ 0.5 mg/L), is four-fold more potent than linezolid, and has the potential to treat pathogens being less susceptible to linezolid. Area under the unbound concentration-time curve (fAUC) related to MIC (fAUC/MIC) was best correlated with efficacy. In neutropenic mice, fAUC/MIC of ~ 50 and ~ 20 induced bacteriostasis in thigh and pulmonary infection models, respectively, at 24 h. The presence of granulocytes augmented its antibacterial effect. Hence, tedizolid is currently not recommended for immunocompromised patients. Clinical investigations with daily doses of 200 mg for 6 days showed non-inferiority to twice-daily dosing of linezolid 600 mg for 10 days in patients with acute bacterial skin and skin-structure infections. In addition to its use in skin and skin-structure infections, the high pulmonary penetration makes it an attractive option for respiratory infections including Mycobacterium tuberculosis. Resistance against tedizolid is rare yet effective antimicrobial surveillance and defining pharmacokinetic/pharmacodynamic targets for resistance suppression are needed to guide dosing strategies to suppress resistance development.

Inferring pulmonary exposure based on clinical PK data: accuracy and precision of model-based deconvolution methods.

Determining and understanding the target-site exposure in clinical studies remains challenging. This is especially true for oral drug inhalation for local treatment, where the target-site is identical to the site of drug absorption, i.e., the lungs. Modeling and simulation based on clinical pharmacokinetic (PK) data may be a valid approach to infer the pulmonary fate of orally inhaled drugs, even without local measurements. In this work, a simulation-estimation study was systematically applied to investigate five published model structures for pulmonary drug absorption. First, these models were compared for structural identifiability and how choosing an inadequate model impacts the inference on pulmonary exposure. Second, in the context of the population approach both sequential and simultaneous parameter estimation methods after intravenous administration and oral inhalation were evaluated with typically applied models. With an adequate model structure and a well-characterized systemic PK after intravenous dosing, the error in inferring pulmonary exposure and retention times was less than twofold in the majority of evaluations. Whether a sequential or simultaneous parameter estimation was applied did not affect the inferred pulmonary PK to a relevant degree. One scenario in the population PK analysis demonstrated biased pulmonary exposure metrics caused by inadequate estimation of systemic PK parameters. Overall, it was demonstrated that empirical modeling of intravenous and inhalation PK datasets provided robust estimates regarding accuracy and bias for the pulmonary exposure and pulmonary retention, even in presence of the high variability after drug inhalation.

Towards a Quantitative Mechanistic Understanding of Localized Pulmonary Tissue Retention-A Combined In Vivo/In Silico Approach Based on Four Model Drugs.

Increasing affinity to lung tissue is an important strategy to achieve pulmonary retention and to prolong the duration of effect in the lung. As the lung is a very heterogeneous organ, differences in structure and blood flow may influence local pulmonary disposition. Here, a novel lung preparation technique was employed to investigate regional lung distribution of four drugs (salmeterol, fluticasone propionate, linezolid, and indomethacin) after intravenous administration in rats. A semi-mechanistic model was used to describe the observed drug concentrations in the trachea, bronchi, and the alveolar parenchyma based on tissue specific affinities (Kp) and blood flows. The model-based analysis was able to explain the pulmonary pharmacokinetics (PK) of the two neutral and one basic model drugs, suggesting up to six-fold differences in Kp between trachea and alveolar parenchyma for salmeterol. Applying the same principles, it was not possible to predict the pulmonary PK of indomethacin, indicating that acidic drugs might show different pulmonary PK characteristics. The separate estimates for local Kp, tracheal and bronchial blood flow were reported for the first time. This work highlights the importance of lung physiology- and drug-specific parameters for regional pulmonary tissue retention. Its understanding is key to optimize inhaled drugs for lung diseases.

Impact of Inaccurate Documentation of Sampling and Infusion Time in Model-Informed Precision Dosing.

BACKGROUND: Routine clinical TDM data is often used to develop population pharmacokinetic (PK) models, which are applied in turn for model-informed precision dosing. The impact of uncertainty in documented sampling and infusion times in population PK modeling and model-informed precision dosing have not yet been systematically evaluated. The aim of this study was to investigate uncertain documentation of (i) sampling times and (ii) infusion rate exemplified with two anti-infectives. METHODS: A stochastic simulation and estimation study was performed in NONMEM® using previously published population PK models of meropenem and caspofungin. Uncertainties, i.e. deviation between accurate and planned sampling and infusion times (standard deviation (SD) ± 5 min to ± 30 min) were added randomly in R before carrying out the simulation step. The estimation step was then performed with the accurate or planned times (replacing real time points by scheduled study values). Relative bias (rBias) and root mean squared error (rRMSE) were calculated to determine accuracy and precision of the primary and secondary PK parameters on the population and individual level. The accurate and the misspecified (using planned sampling times) model were used for Bayesian forecasting of meropenem to assess the impact on PK/PD target calculations relevant to dosing decisions. RESULTS: On the population level, the estimates of the proportional residual error (prop.-err.) and the interindividual variability (IIV) on the central volume of distribution (V1) were most affected by erroneous records in the sampling and infusion time (e.g. rBias of prop.-err.: 75.5% vs. 183% (meropenem) and 10.1% vs. 109% (caspofungin) for ± 5 vs. ± 30 min, respectively). On the individual level, the rBias of the planned scenario for the typical values V1, Q and V2 increased with increasing uncertainty in time, while CL, AUC and elimination half-life were least affected. Meropenem as a short half-life drug (~1 h) was more affected than caspofungin (~ 9-11 h). The misspecified model provided biased PK/PD target information (e.g. falsely overestimated time above MIC (T > MIC) when true T > MIC was <0.4 and thus patients at risk of undertreatment), while the accurate model gave precise estimates of the indices across all simulated patients. CONCLUSIONS: Even 5-minute-uncertainties caused bias and significant imprecision of primary population and individual PK parameters. Thus, our results underline the importance of accurate documentation of time.