EGb 761® Does Not Affect Blood Coagulation and Bleeding Time in Patients with Probable Alzheimer’s Dementia - Secondary Analysis of a Randomized, Double-Blind Placebo-Controlled Trial

Following reports of bleeding upon Ginkgo intake, we assessed whether Ginkgo extract EGb 761® affects coagulation or platelet function or increases the risk of bleeding. In a double-blind, placebo-controlled trial, prothrombin time, activated partial thromboplastin time, international normalized ratio and bleeding time were measured in patients with Alzheimer’s dementia at baseline, weeks 6 and 26. A total of 513 patients were randomized to 120 mg (n = 169) or 240 mg EGb 761® (n = 170) or placebo (n = 174). No relevant changes were found for coagulation parameters and bleeding time. Numbers of bleeding-related adverse events were similar in all groups. Concomitant intake of acetylsalicylic acid was documented for 68 patients in the placebo group and 105 in the EGb 761® groups. Within these groups, the means at baseline and week 26 differed by less than 1 unit for prothrombin time and bleeding time and less than 0.1 unit for international normalized ratio. Data on warfarin treatment in nine patients each taking placebo or EGb 761® did not indicate enhancement of warfarin effects by EGb 761®. No evidence was found that EGb 761® affects hemostasis or increases the bleeding risk. No pharmacodynamic interactions with warfarin or acetylsalicylic acid were found

Bayesian data assimilation to support informed decision-making in individualized chemotherapy

An essential component of therapeutic drug/biomarker monitoring (TDM) is to combine patient data with prior knowledge for model-based predictions of therapy outcomes. Current Bayesian forecasting tools typically rely only on the most probable model parameters (maximum a-posteriori (MAP) estimate). This MAP-based approach, however, does neither necessarily predict the most probable outcome nor does it quantify the risks of treatment inefficacy or toxicity. Bayesian data assimilation (DA) methods overcome these limitations by providing a comprehensive uncertainty quantification. We compare DA methods with MAP-based approaches and show how probabilistic statements about key markers related to chemotherapy-induced neutropenia can be leveraged for more informative decision support in individualized chemotherapy. Sequential Bayesian DA proved to be most computational efficient for handling interoccasion variability and integrating TDM data. For new digital monitoring devices enabling more frequent data collection, these features will be of critical importance to improve patient care decisions in various therapeutic areas

Cell‐level systems biology model to study inflammatory bowel diseases and their treatment options

To help understand the complex and therapeutically challenging inflammatory bowel diseases (IBDs), we developed a systems biology model of the intestinal immune system that is able to describe main aspects of IBD and different treatment modalities thereof. The model, including key cell types and processes of the mucosal immune response, compiles a large amount of isolated experimental findings from literature into a larger context and allows for simulations of different inflammation scenarios based on the underlying data and assumptions. In the context of a large and diverse virtual IBD population, we characterized the patients based on their phenotype (in contrast to healthy individuals, they developed persistent inflammation after a trigger event) rather than on a priori assumptions on parameter differences to a healthy individual. This allowed to reproduce the enormous diversity of predispositions known to lead to IBD. Analyzing different treatment effects, the model provides insight into characteristics of individual drug therapy. We illustrate for anti‐TNF‐α therapy, how the model can be used (i) to decide for alternative treatments with best prospects in the case of nonresponse, and (ii) to identify promising combination therapies with other available treatment options

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies Against Staphylococcus Aureus Exploiting In Vitro Information

Broad-spectrum antibiotic combination therapy is frequently applied due to increasing resistance development of infective pathogens. The objective of the present study was to evaluate two common empiric broad-spectrum combination therapies consisting of either linezolid (LZD) or vancomycin (VAN) combined with meropenem (MER) against Staphylococcus aureus (S. aureus) as the most frequent causative pathogen of severe infections. A semimechanistic pharmacokinetic-pharmacodynamic (PK-PD) model mimicking a simplified bacterial life-cycle of S. aureus was developed upon time-kill curve data to describe the effects of LZD, VAN, and MER alone and in dual combinations. The PK-PD model was successfully (i) evaluated with external data from two clinical S. aureus isolates and further drug combinations and (ii) challenged to predict common clinical PK-PD indices and breakpoints. Finally, clinical trial simulations were performed that revealed that the combination of VAN-MER might be favorable over LZD-MER due to an unfavorable antagonistic interaction between LZD and MER

The Complex Interplay of Pulmonary Kinetic Processes

The inhalation route is frequently used to administer drugs for the management of respiratory diseases such as asthma or chronic obstructive pulmonary disease. Compared with other routes of administration, inhalation offers a number of advantages in the treatment of these diseases. For example, via inhalation, a drug is directly delivered to the target organ, conferring high pulmonary drug concentrations and low systemic drug concentrations. Therefore, drug inhalation is typically associated with high pulmonary efficacy and minimal systemic side effects. The lung, as a target, represents an organ with a complex structure and multiple pulmonary-specific pharmacokinetic processes, including (1) drug particle/droplet deposition; (2) pulmonary drug dissolution; (3) mucociliary and macrophage clearance; (4) absorption to lung tissue; (5) pulmonary tissue retention and tissue metabolism; and (6) absorptive drug clearance to the systemic perfusion. In this review, we describe these pharmacokinetic processes and explain how they may be influenced by drug-, formulation- and device-, and patient-related factors. Furthermore, we highlight the complex interplay between these processes and describe, using the examples of inhaled albuterol, fluticasone propionate, budesonide, and olodaterol, how various sequential or parallel pulmonary processes should be considered in order to comprehend the pulmonary fate of inhaled drugs

Deriving mechanism-based pharmacodynamic models by reducing quantitative systems pharmacology models: An application to warfarin

Quantitative systems pharmacology (QSP) models integrate comprehensive qualitative and quantitative knowledge about pharmacologically relevant processes. We previously proposed a first approach to leverage the knowledge in QSP models to derive simpler, mechanism-based pharmacodynamic (PD) models. Their complexity, however, is typically still too large to be used in the population analysis of clinical data. Here, we extend the approach beyond state reduction to also include the simplification of reaction rates, elimination of reactions, and analytic solutions. We additionally ensure that the reduced model maintains a prespecified approximation quality not only for a reference individual but also for a diverse virtual population. We illustrate the extended approach for the warfarin effect on blood coagulation. Using the model-reduction approach, we derive a novel small-scale warfarin/international normalized ratio model and demonstrate its suitability for biomarker identification. Due to the systematic nature of the approach in comparison with empirical model building, the proposed model-reduction algorithm provides an improved rationale to build PD models also from QSP models in other applications

Patients’ handling of a standardized medication plan: a pilot study and method development

Purpose: The Action Plan for Medication Safety by the German Federal Ministry of Health introduced a standardized medication plan (MP), a printable document for the patient. The practical handling needs to be tested before the nationwide implementation in Germany. Therefore, the aims of our study were 1) to develop an instrument to evaluate the usage of the standardized MP, 2) to assess if patients can locate, and 3) understand important information. Moreover, we explored patients’ opinion and suggestions regarding the standardized MP template. Patients and methods: We conducted a cross-sectional study to evaluate the practical handling of the standardized MP. We interviewed 40 adult patients in seven community pharmacies in Germany, who took at least five medicines regularly and gave their written informed consent. The interview consisted of questions regarding finding and understanding information provided on a mock-up MP, patients’ opinion and the execution of the information on the MP by filling pill boxes. We eventually developed a new evaluation method to quantify the practical handling of the MP by rating the pill boxes filled by the patients. Results: Overall, the participants rated the MP positively. Thirty-nine (98%) participants found important information on a mock-up standardized MP. Patients were questioned to identify if they understood information on medical intake as it relates to meals. In particular, they were questioned about medicine intake “1 hour before a meal”, which 98% (n=39) interpreted correctly, and “during a meal”, which 100% (n=40) interpreted correctly. The less precise advice of “before a meal” was interpreted correctly by 73% (n=29), and only 15% (n=6) correctly interpreted the term “after the meal”. The evaluation of the filled pill boxes resulted in the “Evaluation Tool to test the handling of the Medication Plan” (ET-MP) – a weighted scoring system. Conclusion: The standardized MP is clearly arranged, and patients are able to find important information. The findings of this study resulted in minor but important revisions of the standardized MP template. The developed evaluation tool ET-MP may serve as an objective instrument to assess patients’ ability to transfer written information on the MP into practical handling of medicines

A continued learning approach for model-informed precision dosing: Updating models in clinical practice

Model-informed precision dosing (MIPD) is a quantitative dosing framework that combines prior knowledge on the drug-disease-patient system with patient data from therapeutic drug/ biomarker monitoring (TDM) to support individualized dosing in ongoing treatment. Structural models and prior parameter distributions used in MIPD approaches typically build on prior clinical trials that involve only a limited number of patients selected according to some exclusion/inclusion criteria. Compared to the prior clinical trial population, the patient population in clinical practice can be expected to also include altered behavior and/or increased interindividual variability, the extent of which, however, is typically unknown. Here, we address the question of how to adapt and refine models on the level of the model parameters to better reflect this real-world diversity. We propose an approach for continued learning across patients during MIPD using a sequential hierarchical Bayesian framework. The approach builds on two stages to separate the update of the individual patient parameters from updating the population parameters. Consequently, it enables continued learning across hospitals or study centers, because only summary patient data (on the level of model parameters) need to be shared, but no individual TDM data. We illustrate this continued learning approach with neutrophil-guided dosing of paclitaxel. The present study constitutes an important step toward building confidence in MIPD and eventually establishing MIPD increasingly in everyday therapeutic use

Microdialysis of Drug and Drug Metabolite: a Comprehensive In Vitro Analysis for Voriconazole and Voriconazole N-oxide

Purpose Voriconazole is a therapeutically challenging antifungal drug associated with high interindividual pharmacokinetic variability. As a prerequisite to performing clinical trials using the minimally-invasive sampling technique microdialysis, a comprehensive in vitro microdialysis characterization of voriconazole (VRC) and its potentially toxic N-oxide metabolite (NO) was performed. Methods The feasibility of simultaneous microdialysis of VRC and NO was explored in vitro by investigating the relative recovery (RR) of both compounds in the absence and presence of the other. The dependency of RR on compound combination, concentration, microdialysis catheter and study day was evaluated and quantified by linear mixed-effects modeling. Results Median RR of VRC and NO during individual microdialysis were high (87.6% and 91.1%). During simultaneous microdialysis of VRC and NO, median RR did not change (87.9% and 91.1%). The linear mixed-effects model confirmed the absence of significant differences between RR of VRC and NO during individual and simultaneous microdialysis as well as between the two compounds (p > 0.05). No concentration dependency of RR was found (p = 0.284). The study day was the main source of variability (46.3%) while the microdialysis catheter only had a minor effect (4.33%). VRC retrodialysis proved feasible as catheter calibration for both compounds. Conclusion These in vitro microdialysis results encourage the application of microdialysis in clinical trials to assess target-site concentrations of VRC and NO. This can support the generation of a coherent understanding of VRC pharmacokinetics and its sources of variability. Ultimately, a better understanding of human VRC pharmacokinetics might contribute to the development of personalized dosing strategies

What opportunities do the New EU international investment agreements offer for developing countries?

Purpose: Cancer chemotherapy, although based on body surface area, often causes unpredictable myelosuppression, especially severe neutropenia. The aim of this study was to evaluate qualitatively and quantitatively the influence of patient-specific characteristics on the neutrophil concentration-time course, to identify patient subgroups, and to compare covariates on system-related pharmacodynamic variable between drugs. Experimental Design: Drug and neutrophil concentration, demographic, and clinical chemistry data of several trials with docetaxel (637 patients), paclitaxel (45 patients), etoposide (71 patients), or topotecan (191 patients) were included in the covariate analysis of a physiology-based pharmacokinetic-pharmacodynamic neutropenia model. Comparisons of covariate relations across drugs were made. Results: A population model incorporating four to five relevant patient factors for each drug to explain variability in the degree and duration of neutropenia has been developed. Sex, previous anticancer therapy, performance status, height, binding partners, or liver enzymes influenced system-related variables and alpha(1)-acid glycoprotein, albumin, bilirubin, concomitant cytotoxic agents, or administration route changed drug-specific variables. Overall, female and pretreated patients had a lower baseline neutrophil concentration. Across-drug comparison revealed that several covariates (e.g., age) had minor (clinically irrelevant) influences but consistently shifted the pharmacodynamic variable in the same direction. Conclusions: These mechanistic models, including patient characteristics that influence drug-specific parameters, form the rationale basis for more tailored dosing of individual patients or subgroups to minimize the risk of infection and thus might contribute to a more successful therapy. In addition, nonsignificant or clinically irrelevant relations on system-related parameters suggest that these covariates could be negligible in clinical trails and daily use