Assessing Dose-Exposure-Response Relationships of Miltefosine in Adults and Children using Physiologically-Based Pharmacokinetic Modeling Approach.

OBJECTIVES: Miltefosine is the first and only oral medication to be successfully utilized as an antileishmanial agent. However, the drug is associated with differences in exposure patterns and cure rates among different population groups e.g. ethnicity and age (i.e., children v adults) in clinical trials. In this work, mechanistic population physiologically-based pharmacokinetic (PBPK) models have been developed to study the dose-exposure-response relationship of miltefosine in in silico clinical trials and evaluate the differences in population groups, particularly children and adults. METHODS: The Simcyp population pharmacokinetics platform was employed to predict miltefosine exposure in plasma and peripheral blood mononuclear cells (PBMCs) in a virtual population under different dosing regimens. The cure rate of a simulation was based on the percentage of number of the individual virtual subjects with AUCd0-28 > 535 µg⋅day/mL in the virtual population. RESULTS: It is shown that both adult and paediatric PBPK models of miltefosine can be developed to predict the PK data of the clinical trials accurately. There was no significant difference in the predicted dose-exposure-response of the miltefosine treatment for different simulated ethnicities under the same dose regime and the dose-selection strategies determined the clinical outcome of the miltefosine treatment. A lower cure rate of the miltefosine treatment in paediatrics was predicted because a lower exposure of miltefosine was simulated in virtual paediatric in comparison with adult virtual populations when they received the same dose of the treatment. CONCLUSIONS: The mechanistic PBPK model suggested that the higher fraction of unbound miltefosine in plasma was responsible for a higher probability of failure in paediatrics because of the difference in the distribution of plasma proteins between adults and paediatrics. The developed PBPK models could be used to determine an optimal miltefosine dose regime in future clinical trials.

Understanding Discordance between In Vitro Dissolution, Local Gut and Systemic Bioequivalence of Budesonide in Healthy and Crohn's Disease Patients through PBPK Modeling.

The most common method for establishing bioequivalence (BE) is to demonstrate similarity of concentration-time profiles in the systemic circulation, as a surrogate to the site of action. However, similarity of profiles from two formulations in the systemic circulation does not imply similarity in the gastrointestinal tract (GIT) nor local BE. We have explored the concordance of BE conclusions for a set of hypothetical formulations based on budesonide concentration profiles in various segments of gut vs. those in systemic circulation using virtual trials powered by physiologically based pharmacokinetic (PBPK) models. The impact of Crohn's disease on the BE conclusions was explored by changing physiological and biological GIT attributes. Substantial 'discordance' between local and systemic outcomes of VBE was observed. Upper GIT segments were much more sensitive to formulation changes than systemic circulation, where the latter led to false conclusions for BE. The ileum and colon showed a lower frequency of discordance. In the case of Crohn's disease, a product-specific similarity factor might be needed for products such as Entocort® EC to ensure local BE. Our results are specific to budesonide, but we demonstrate potential discordances between the local gut vs. systemic BE for the first time.

Population PBPK modeling using parametric and nonparametric methods of the Simcyp Simulator, and Bayesian samplers.

Physiologically-based pharmacokinetic (PBPK) models usually include a large number of parameters whose values are obtained using in vitro to in vivo extrapolation. However, such extrapolations can be uncertain and may benefit from inclusion of evidence from clinical observations via parametric inference. When clinical interindividual variability is high, or the data sparse, it is essential to use a population pharmacokinetics inferential framework to estimate unknown or uncertain parameters. Several approaches are available for that purpose, but their relative advantages for PBPK modeling are unclear. We compare the results obtained using a minimal PBPK model of a canonical theophylline dataset with quasi-random parametric expectation maximization (QRPEM), nonparametric adaptive grid estimation (NPAG), Bayesian Metropolis-Hastings (MH), and Hamiltonian Markov Chain Monte Carlo sampling. QRPEM and NPAG gave consistent population and individual parameter estimates, mostly agreeing with Bayesian estimates. MH simulations ran faster than the others methods, which together had similar performance.

Mechanistic PBPK Modelling to Predict the Advantage of the Salt Form of a Drug When Dosed with Acid Reducing Agents.

Acid reducing agents (ARAs) reduce the dissolution rate of weakly basic drugs in the stomach potentially leading to lower bioavailability. Formulating the API as a rapidly dissolving salt is one strategy employed to reduce the impact of ARAs on dissolution of such drugs. In the present work, a model drug was selected with an immediate release formulation of the free base dosed in both the absence and presence of the ARA famotidine. In the latter case, bioavailability is restricted and several salt formulations were investigated. To simulate these drug products a mechanistic physiologically based pharmacokinetic (PBPK) model was built using the Simcyp Simulator, which illustrates the advantage of formulating an API as a salt compared to the free base form. The simulations use a mechanistic salt model utilising knowledge of the solubility product which was applied to predict the salt advantage. The developed PBPK model exemplifies that it can be critical to account for the surface pH and solubility when modelling the dissolution of low pKa bases and their salts in the gastric environment. In particular, the mechanistic salt model can be used to aid in screening and salt form selection where the aim is to mitigate effects of ARAs.

Tools and tactics for postdischarge medication management interventions.

PURPOSE: To identify interventions for organizational pharmacist-leaders and frontline pharmacy staff to optimize peri- and postdischarge medication management. SUMMARY: An evidence-based toolkit was systematically constructed on the basis of findings of 3 systematic overviews of systematic reviews. The interventions were reviewed by a technical expert panel and categorized as either tools or tactics. The identified tools are instruments such as diagrams, flow charts, lists, tables, and templates used in performing a distinct operation, whereas identified tactics reflect broader methods (eg, reduced dosing frequency). Tools and tactics were chosen on the basis of their potential to improve postdischarge medication management, with a focus on interventions led by pharmacy staff that may reduce hospital readmissions among older, sicker patients. Overall, 23 tools and 2 tactics were identified. The identified tools include items such as education, text messaging, and phone calls. The tactics identified are dose simplification and monetary incentives. Practical information has also been provided to facilitate implementation. CONCLUSION: Several tools and tactics are available to optimize peri- and postdischarge medication management. Organizational pharmacist-leaders and frontline pharmacy staff can implement these interventions to improve patient outcomes.

Major depression drives severity of American Urological Association Symptom Index.

OBJECTIVES: To evaluate the unclear relationship between depression and benign prostatic hyperplasia (BPH) by assessing depression's effect on the American Urological Association Symptom Index (AUA-SI) scores. Depression is a common illness associated with chronic inflammatory disease states. Data have suggested a significant role of inflammation in the progression of BPH. METHODS: The present prospective study involved 547 male patients who completed the Geriatric Depression Scale and the AUA-SI. We evaluated whether the mean AUA-SI score and the severity categories differed by the state of depression. We then conducted binary logistic regression analysis with forward stepwise regression to assess the relationship between depression and the severity symptoms as determined by the AUA-SI score. RESULTS: Of the cohort, 22% screened positive for depressive symptoms. The depressed patients (Geriatric Depression Scale score >5) reported significantly more severe symptoms (mean AUA-SI score 16.61 ± 9.89) compared with the nondepressed patients (Geriatric Depression Scale score of ≤5 and mean AUA-SI score 10.65 ± 7.29; F = 40.19, P <.001). After controlling for socioeconomic and demographic variables, depressed patients were 3 times more likely to present with severe symptoms (odds ratio 3.079, 95% confidence interval 1.129-8.402, P = .028). CONCLUSIONS: A significant association was found between depression and BPH. However, it remains unclear whether this relationship represents unidirectional or bidirectional causality. Additional research is imperative to assess the nature of this correlation, either to address comorbid depression in patients with BPH or to ensure that depressed patients do not report falsely elevated symptoms.