Design of novel drug delivery system and optimal dosage regimens

Three representative drug delivery systems were analyzed to emphasize the roles of mathematical models and computer-aided simulations in pharmaceutical research. In the first project, a protocol was developed so that the optimal regimen, consisting of the intravenous boluses and subsequent infusion of theophylline, could be obtained once information on the pharmacokinetics became available. The method was based on a two-compartment model of the human body. A module was created and posted on a website for free access. The second project dealt with the transdermal heat-assisted delivery of corticosterone. Heat conduction and drug diffusion through the patch and the skin were expressed in the mathematical model. Four design parameters were estimated. This model was validated using clinical data from the administration of fentanyl. Cortisone concentrations through the patch and skin layers were predicted. The results were used to rank the relative impacts of the design parameters on the corticosterone delivery and to make proper suggestions for fabricating the products. Finally, the simultaneous application of an electric current and soluble microneedles were proposed for the first time. Preliminary experimental studies suggested that the electric field enhanced the flux by increasing drug diffusion and, thereby, the dissolution of the microneedles. One-, two- and three-dimensional simulations were conducted. In addition, protocols were proposed to help with the analysis of laboratory data

Optimising intravenous salbutamol in children: a phase 2 study

OBJECTIVE: The β2-agonists such as salbutamol are the mainstay of asthma management. Pharmacokinetic-pharmacodynamic (PKPD) models to guide paediatric dosing are lacking. We explored the relationship between salbutamol dose, serum concentration, effectiveness and adverse effects in children by developing a PKPD model. DESIGN: A prospective cohort study of children admitted to hospital with acute asthma, who received intravenous salbutamol. SETTING: Children were recruited in two cohorts: the emergency departments of two London hospitals or those retrieved by the Children's Acute Transport Service to three London paediatric intensive care units. PATIENTS: Patients were eligible if aged 1-15 years, admitted for acute asthma and about to receive or receiving intravenous salbutamol. INTERVENTIONS: Treatment was according to local policy. Serial salbutamol plasma levels were taken. Effectiveness measurements were recorded using the Paediatric Asthma Severity Score (PASS). Toxicity measurements included lactate, pH, glucose, heart rate, blood pressure and arrhythmias. PKPD modelling was performed with non-linear mixed-effect models. MAIN OUTCOMES: Fifty-eight children were recruited with 221 salbutamol concentration measurements from 54 children. Median (range) age was 2.9 (1.1-15.2) years, and weight was 13.6 (8-57.3) kg. Ninety-five PASS measurements and 2078 toxicity measurements were obtained. RESULTS: A two-compartment PK model adequately described the time course of salbutamol-plasma concentrations. An EMAX (maximum drug effect) concentration-effect relationship described PASS and toxicity measures. PKPD simulations showed an infusion of 0.5 µg/kg/min (maximum 20 µg/min) for 4 hours after bolus achieves >90% maximal bronchodilation for 12 hours. CONCLUSIONS: A paediatric PKPD model for salbutamol is described. An infusion of 0.5 µg/kg/min after bolus achieves effective bronchodilation. Higher rates are associated with greater tachycardia and hyperglycaemia

Mathematical Models for Optimisation of Drug Administration in Intensive Care Units

Clinical status of critically ill patients is often extreme and rapidly evolving. Hence, pharmacological therapies must be tailored to patients' characteristics and adapted according to the evolution of their clinical pictures. To identify optimal personalized treatments, possible scenarios produced by different therapeutic choices must be predicted and compared. This process requires complex analyses involving the development of appropriate mathematical models. In this Thesis, I focused on two important aspects of the pharmacological treatment of critically ill patients: the administration of antimicrobial drugs and the control of their glycaemic level. Although these problems are clinically very different, the modelling of their pathophysiological mechanisms can be addressed with similar tools. I performed analyses based on retrospective clinical data collected with MargheritaTre, an electronic health record developed by GiViTI. The software to synchronize databases from hospitals to our laboratory and to preprocess data for analyses was written for the purpose of this Thesis. Starting from the study of the physiological mechanisms at the basis of vancomycin pharmacokinetics I constructed a model to describe the evolution of the plasma concentration of this drug in critically ill patients. Compartment models were fitted on a sample of 141 patients, testing about 30 patient covariates and several functional dependencies for each variable. Glucose dynamics were described through a system of delay differential equations reproducing intake, uptake and endogenous production of glucose, and organ-organ interactions mediated by hormones. Existing models, describing only the dynamics of glucose and insulin, fail to reproduce the correct evolution when glucose concentrations vary too rapidly. I improved these models, by introducing an equation describing glucagon dynamics and taking into account its effect on glucose metabolism. I investigated the dynamical properties of my model with analytical analyses, numerical simulations and fitting it to observed data

Pharmacokinetic-pharmacodynamic cutoff values for benzylpenicillin in horses to support the establishment of clinical breakpoints for benzylpenicillin antimicrobial susceptibility testing in horses

Introduction: The aim of this international project was to establish a species-specific Clinical Breakpoint for interpretation of Antimicrobial Susceptibility Testing of benzylpenicillin (BP) in horses.Methods: A population pharmacokinetic model of BP disposition was developed to compute PK/PD cutoff values of BP for different formulations that are commonly used in equine medicine around the world (France, Sweden, USA and Japan). Investigated substances were potassium BP, sodium BP, procaine BP, a combination of procaine BP and benzathine BP and penethamate, a prodrug of BP. Data were collected from 40 horses that provided 63 rich profiles of BP corresponding to a total of 1022 individual BP plasma concentrations.Results: A 3-compartment disposition model was selected. For each of these formulations, the PK/PD cutoff was estimated for different dosage regimens using Monte Carlo simulations. The fAUC/MIC or fT>MIC were calculated with a free BP fraction set at 0.4. For fAUC/MIC, a target value of 72 h (for a 72h treatment) was considered. For fT>MIC, efficacy was assumed when free plasma concentrations were above the explored MIC (0.0625-2 mg/L) for 30 or 40 % of the dosing interval. For continuous infusion, a fT>MIC of 90 % was considered. It was shown that a PK/PD cutoff of 0.25 mg/L can be achieved in 90 % of horses with routine regimen (typically 22,000 IU/kg or 12.4 mg/kg per day) with IM procaine BP once a day (France, Japan, Sweden but not USA1) and with IM sodium BP at 14.07 mg/kg, twice a day or IV sodium BP infusion of 12.4 mg/kg per day. In contrast, penethamate and the combination of procaine BP and benzathine BP were unable to achieve this PK/PD cutoff not even an MIC of 0.125 mg/L.Discussion: The PK/PD cutoff of 0.25 mg/L is one dilution lower than the clinical breakpoint released by the CLSI (0.5 mg/ L). From our simulations, the CLSI clinical breakpoint can be achieved with IM procaine BP twice a day at 22,000 IU i.e. 12.4 mg/kg

Optimising clonidine dosage for sedation in mechanically ventilated children: a pharmacokinetic simulation study

BACKGROUND: Clonidine is in widespread off-label use as a sedative in mechanically ventilated children, despite limited evidence of efficacy. A variety of dosage regimens have been utilised in clinical practice and in research studies. Within these studies, clonidine has inconsistently shown useful sedation properties. One of the reasons attributed to the inconsistent signs of efficacy is suboptimal clonidine dosing. AIM: This study aims to propose a target plasma concentration and simulate clonidine pharmacokinetics (PK) in a cohort of mechanically ventilated children to evaluate the adequacy of clonidine dosage regimens used in clinical practice and research studies. METHOD: A literature search was undertaken to identify a clonidine PKPD model, from which a target concentration for sedation was defined. Using a previously published PK model the projected plasma concentrations of 692 mechanically ventilated children (demographics taken from a recent study) were generated. Doses from recently published clinical studies were investigated. Adequacy of each regimen to attain therapeutic clonidine plasma concentrations was assessed. RESULTS: A target plasma concentration of above 2 μg/L was proposed. Nine dosage regimens (four intravenous boluses, four intravenous infusions and one nasogastric route boluses) were evaluated ranging from 1μg/kg 8 hourly intravenous boluses to a regimen up to 3μg/kg/hr continuous intravenous infusion. Regimens with a loading dose of 2μg/kg followed by variable continuous infusion of up to 2μg/kg/hr titrated according to sedation score appear most suitable. CONCLUSIONS: The variety of dosage regimens in previous studies of clonidine along with difficulties in the conduct of interventional studies may have contributed to the lack of efficacy data to support its use. Simulations of clonidine plasma concentrations based on known population pharmacokinetic parameters suggest a loading dose followed by higher than current practice maintenance dose infusion is required to achieve adequate steady-state concentrations early in treatment. Further PKPD studies will aid in the determination of the optimal clonidine dosage regimen. This article is protected by copyright. All rights reserved

n-vitro time-kill assays and semi-mechanistic pharmacokinetic-pharmacodynamic modeling of a beta-lactam antibiotic combination against enterococcus faecalis: Optimizing dosing regimens for the geriatric population

Pharmacokinetic-pharmacodynamic (PKPD) modeling and simulation have emerged as pivotal tools in drug development and usage. Such models characterize typical trends in data and quantify the variability in relationships among dose, concentration, and desired effects. For antibacterial applications, models characterizing bacterial growth and antibiotic-induced bacterial killing offer insight into interactions between antibiotics, bacteria, and the host. Simulations from these models predict outcomes for untested scenarios, refine study designs, and optimize dosing regimens. Enterococcus faecalis, a significant opportunistic bacterial pathogen with increasing clinical relevance, is commonly found in the gastrointestinal tract but can lead to severe infection, such as endocarditis. Treatments for E. faecalis endocarditis involves combination antibiotic therapy, such as beta-lactam antibiotics and aminoglycosides. However, due to the toxicity of aminoglycosides, the primary treatment is typically double beta-lactam therapy—ampicillin and ceftriaxone. Eradicating an E. faecalis infection typically requires a lengthy six-week course of antibiotic treatment. However, keeping patients in hospitals for such an extended duration is impractical. Therefore, the objective of this thesis project is to explore the extension of double beta-lactam therapy to outpatient antibiotic treatment (OPAT). This approach is gaining importance due to the rising risks of hospital-acquired infections and escalating healthcare expenses. Leveraging the stability of penicillin G, which can be stored at room temperature for extended periods, makes it a promising candidate for OPAT, offering potential benefits in terms of both efficacy and cost-effectiveness. Despite limited evidence for penicillin G plus ceftriaxone, this research successfully bridges the gap through in-vitro time-kill assays and the subsequent development of a semi-mechanistic model for this antibiotic combination against E. faecalis isolates. This dissertation research evaluated 21 clinical strains of E. faecalis isolated from infected patients\u27 blood, sourced from Mount Sinai Health System and a hospital in Detroit as part of Dr. Jaclyn Cusumano’s American Association of Pharmacists (AACP) new investigator award research project. The first aim was to conduct susceptibility testing on these isolates. This testing played a pivotal role in guiding antibiotic therapy by determining a drug\u27s minimum inhibitory concentration (MIC) for a specific bacterial strain, offering insight into its effectiveness. The project highlights the importance of knowing a patient\u27s strain susceptibility since it influences the dosing regimen or treatment strategy. After susceptibility testing using broth microdilution techniques, strains were categorized as highly susceptible (MIC ≤ 2 μg/ml) or less susceptible (MIC = 4 μg/ml) to penicillin G. The next phase of the project involved in-vitro time-kill assays—a gold standard method for testing antibiotic concentrations and synergy in combination therapies. All 21 patient isolates were tested with penicillin G monotherapy and in combination with ceftriaxone, along with testing ampicillin and ceftriaxone combination therapies for comparison. It was noted that both combinations showed efficacy for strains highly susceptible to penicillin G (MIC ≤ 2 μg/ml), exhibiting bactericidal and synergistic activity. However, both treatments demonstrated poor performance for the less susceptible strains (MIC = 4 μg/ml). This observation focuses on the importance of in-vitro pharmacodynamic studies in understanding antibiotic action dynamics, forming the basis for the semi-mechanistic model. These 24-hour time-kill assays strongly suggested further investigation into the penicillin G and ceftriaxone combination, while considering the differential effects of the combination on more and less susceptible strains. Semi-mechanistic models were created for two out of the twenty-one tested strains, one with high susceptibility and another with lower susceptibility, with the goal of understanding the bacterial growth and drug kill effect in greater detail along with testing different dosing regimens. Following the typical progression of constructing a semi-mechanistic PK-PD model, a bacterial sub-model was created by employing intensive sampling during time-kill assays. This approach enabled the comprehension of the complete bacterial growth dynamics for both strains. By employing non-linear least squares regression within RStudio, the predictive model was effectively fitted to the observed data, providing estimates of essential bacterial growth parameters. The utilization of the Gompertz growth model yielded a remarkably close match between predicted and observed data, giving confidence in the accuracy of the estimated growth parameters. Subsequently, the focus shifted to obtaining the most suitable pharmacodynamic (PD) parameters to accurately encapsulate the drug\u27s antibacterial effects. This necessitated the use of a mathematical model. A widely employed model for this purpose is the Sigmoidal Emax model—an empirical model that is widely published. This model emerged as a valuable tool for formalizing the interpretation of experimental data and understanding the influence of altering penicillin G concentrations, both individually and in conjunction with ceftriaxone. Leveraging the data analysis capacity of RStudio, nonlinear least squares regression analysis was used to intricately fit the sigmoidal Emax equation to the observed data. This led to obtaining vital parameters, including Emax (maximum effect), EC50 (half-maximal effective concentration), and the sigmoidicity factor. Subsequent evaluation of goodness of fit based visual predictive checks and low standard errors in estimated parameters confirmed the favorable alignment between the predicted model and observed data. Physiologically based pharmacokinetic (PBPK) modeling and simulation stands as a well-established approach that bridges insights from preclinical studies to clinical outcomes. By combining drug-specific information with a comprehensive understanding of physiological and biological processes at the organism level, PBPK models mechanistically depict the behavior of drugs within biological systems. This enables the a priori simulation of drug concentration-time profiles. What distinguishes PBPK modeling is its unique capability to account for physiological variations within specific populations, offering predictive insights into pharmacokinetics tailored to those groups. This thesis project ventured into two vital applications of PBPK models: extrapolating novel clinical scenarios and exploring pharmacokinetics in special populations, particularly the geriatric demographic. With the aim of comprehending the pharmacokinetics of penicillin G and ceftriaxone, the project leveraged the Simcyp® Simulator, a modeling and simulation tool that is widely used in drug development. This platform pools the anatomical, physiological, drug-related, and trial design parameters to generate plasma drug concentration profiles. The simulated concentrations were compared against published data, with the fold error—a ratio of simulated to observed values—serving as a benchmark for model accuracy. Typically, predictions within a fold error range of 0.5 to 2 are deemed acceptable. Upon verification within the healthy population, the models were extended to geriatric subjects utilizing the Simcyp® population library. The same fold error criteria were applied, and the models adeptly predicted concentrations across both young and elderly populations. Remarkable differences in pharmacokinetics were seen in the geriatric cohort compared to a young adult population. Notably, for penicillin G, the AUC increased by 46% in the elderly due to an almost 47% decline in total clearance, stemming from a 49% reduction in glomerular filtration rate (GFR). Further expanding the PBPK model for penicillin G, the inclusion of a pharmacodynamic (PD) component led to the final goal of this project. Lua scripting in Simcyp® was utilized to build the PD model. This model used an equation that combined the bacterial growth model with the drug\u27s inhibitory effect via the Emax model. The impacts of monotherapy and combination were explored through the modulation of PD parameters. Consequently, when co-administered with ceftriaxone, kill rates for penicillin G increased, and IC50 values decreased, indicative of ceftriaxone\u27s augmentative effect. The free (unbound) plasma concentration-time profile from the developed PBPK model was linked as input to the PD model, facilitating testing and simulation of diverse penicillin G dosing regimens. Notably, penicillin G, a time-dependent beta-lactam antibiotic, exhibited a strong correlation with the PK/PD index %fT\u3eMIC (% of the dosing interval with a free concentration above MIC). This was especially pertinent for high-susceptibility strains, wherein continuous infusion of penicillin G led to the most significant reduction in bacterial density, irrespective of combination therapy or monotherapy. However, for low-susceptibility strains, the scenario differed, revealing that reliance on a single PK/PD index is not all-encompassing. For the geriatric population, the PBPK-PD model aligned with literature-backed dosing modifications for penicillin G. For highly susceptible strains, increasing the dosing interval or reducing the dose resulted in comparable reductions in bacterial density. Conversely, in low7 susceptibility strains, even an increase in AUC within the geriatric demographic failed to eradicate the bacteria. In summary, this comprehensive thesis journey navigates through the in-vitro bacterial studies and pharmacokinetic-pharmacodynamic (PKPD) modeling and simulation. This project sheds light on the ability to integrate in-vitro data with PBPK models which not only predict untested scenarios but also help dosing strategies. Overall, by addressing the clinical challenge of E. faecalis infections, the project showcased the extension of double beta-lactam therapy to penicillin G and ceftriaxone combination through a stepwise development of semi-mechanistic PK/PD model

Design of drug delivery strategies based on well-stirred experiments

Drugs are generally administered to the human body via injections (IV) or through other paths such as the buccal, nasal routes. The main consideration when designing a medication schedule is to maintain a therapeutic level of the drug in the body during the course of treatment. To achieve this goal, when IV drug therapy is selected, particular importance has to given to the dose to be injected and how to maintain the concentration of the pharmaceutical active ingredient (API) in the body between a Minimum Toxic Concentration (MTC) and a Minimum Effective Concentration (MEC). This therapeutic range varies with the drug and is designed so that the patient takes full benefit of the treatment while keeping potential risks or side effects to a minimum. The aim of this thesis is to design drug administration protocols based on well- stirred vessel experiments that mimic one- and two-compartment pharmacokinetic models. A one-compartment model assumes that drug is evenly distributed in the body, which is represented by a beaker with an inlet and an outlet stream. In a two- compartment model, drug is distributed between the central and peripheral vessels. Only bolus and constant-rate infusion are considered in this study. Mathematical models are used to estimate the pharmacokinetic parameters and to derive administration strategies to be tested experimentally. Results show that the well-stirred vessel captures the behavior of one- and two-compartment models very well. The time-concentration profiles of a tracer in the compartments are functions of the kinetic parameters

Predictive Factors of Piperacillin Exposure and the Impact on Target Attainment after Continuous Infusion Administration to Critically Ill Patients

Critically ill patients undergo significant pathophysiological changes that affect antibiotic pharmacokinetics. Piperacillin/tazobactam administered by continuous infusion (CI) improves pharmacokinetic/pharmacodynamic (PK/PD) target attainment. This study aimed to characterize piperacillin PK after CI administration of piperacillin/tazobactam in critically ill adult patients with preserved renal function and to determine the empirical optimal dosing regimen. A total of 218 piperacillin concentrations from 106 patients were simultaneously analyzed through the population PK approach. A two-compartment linear model best described the data. Creatinine clearance (CLCR) estimated by CKD-EPI was the covariate, the most predictive factor of piperacillin clearance (CL) interindividual variability. The mean (relative standard error) parameter estimates for the final model were: CL: 12.0 L/h (6.03%); central and peripheral compartment distribution volumes: 20.7 L (8.94%) and 62.4 L (50.80%), respectively; intercompartmental clearance: 4.8 L/h (26.4%). For the PK/PD target of 100% fT(>1xMIC), 12 g of piperacillin provide a probability of target attainment > 90% for MIC 100 mL/min. For 100% fT(>4xMIC), the highest dose (24 g/24 h) was not sufficient to ensure adequate exposure, except for MICs of 1 and 4 mg/L. Our model can be used as a support tool for initial dose guidance and during therapeutic drug monitoring