Recirculatory modeling in man using Indocyanine green

Titration to effect is the most important action anesthesiologists use to assure adequacy of anesthesia and safeguard their patients from serious side effects. For a proper titration to effect the anesthesiologist takes into consideration the historical response to a given dose to estimate the response to a future dose. During induction of anesthesia the anesthesiologist is still unaware of the dose-response relationship of the patient. Because for many agents the knowledge of the covariates of influence on the induction dose-response relationship is lacking, many patients experience serious side effects during induction of anesthesia, often in the form of hemodynamic depression. In this thesis light is shed on the pharmacology of induction of anesthesia. The front-end kinetics are complex and often flow dependent. The observations in this thesis teach us that the modeling of the dose-concentration-effect relation is insufficiently described by compartmental modeling and improves by applying recirculatory PK-PD modeling. The anesthetic propofol and neuromuscular blocking agent rocuronium are described, using recirculatory modeling. (Non)invasive ICG measurement is used extensively in recirculatory modeling but is less well suited for hemodynamic monitoring. Noninvasive measurement of the ICG plasma disappearance rate proved adequate.Department of Anesthesiology, Leiden University Medical Centre, Leiden, the NetherlandsUBL - phd migration 201

Preclinical pharmacokinetic evaluation of novel antimalarial and antituberculosis drug leads

Preclinical pharmacokinetics relies on efficient and accurate screening to select clinical candidates from early leads. Poor pharmacokinetic interpretation can disadvantage drug discovery by promoting inadequate compounds and expelling potential drug candidates. Objectives of this project included pharmacokinetic evaluation of antimalarial and anti-tuberculosis lead compounds with techniques aimed at improving preclinical pharmacokinetic outcomes. This included mechanistic pharmacokinetic approaches such as non-linear mixed effects (NLME) modelling in comparison with traditional non-compartmental analysis. Where appropriate, pharmacokinetic methods were expanded to include organ distribution and capsule dosing in mice to bridge our techniques from discovery to early development. Three benzoxazole amodiaquine analogues possessing equipotent in vitro antiplasmodial activity and showed diverse in vivo efficacy in a malaria mouse model. Evaluation of their respective pharmacokinetics in mice showed their in vivo exposures could translate to in vivo efficacy. Retrospective PK/PD simulations point to a time above IC50 drive in efficacy. Pharmacokinetic evaluation of an aminopyridine antimalarial compound in its cyclodextrin inclusion complex revealed a pH dependent increase in solubility that reduced variance, likely due to favoured intestinal absorption. Investigation of two novel fusidic acid C-3 ester prodrugs aimed at repositioning fusidic acid for tuberculosis, showed high concentrations of the rodent specific 3-epifusidic acid metabolite that greatly reduced exposure of fusidic acid in mice. Further organ distribution studies showed a prodrug strategy is still viable for repositioning fusidic acid for tuberculosis, but that rodent models are inappropriate for further evaluation. NLME modelling successfully provided unique mechanistic and mathematical insight of pharmacokinetic profiles of new leads. The level of interpretation on pharmacology parameters improved and aided in understanding why drug leads are likely to fail or succeed, assisting future compound optimisation

Towards the rational use of antibiotics: Utilising pharmacometric approaches to improve meropenem and piperacillin treatment in critically ill patients

In 1909 the discovery of the antibiotic arsphenamin marked the beginning of a new era in treating potentially deadly bacterial infections. In the following decades, the discovery of various new antibiotic drugs substantially contributed to a rise in life expectancy from 47.0 to 78.8 years in the United States of America. Despite this considerable progress in treating infectious diseases, bacterial infections remain a major threat to public health. Especially vulnerable patient populations, like critically ill patients, continued to suffer under mortality rates up to 60%. Worryingly, the described achievements are threatened by two alarming developments: While no truly novel antibiotic classes have been discovered and developed in the last three decades, the emergence and spread of antimicrobial resistance -accelerated by the inappropriate use of antibiotic drugs - steadily reduces the efficacy of currently available drugs. As a response to this new challenge, several national and international action plans call not only for a determined search for new antimicrobial drugs, but also for a more rational use of existing antibiotics. One vital component of rational antibiotic drug therapy is an adequate drug exposure at the site of infection, facilitated by the selection of suitable antibiotic drug(s) in combination with an appropriate dosing regimen. The antibiotic drug administered to the patient should be selected based on its efficacy against the pathogen causing the infection. Unfortunately, the pathogen causing the infection is often unknown at the start of antibiotic therapy. As a consequence, broad spectrum antibiotics – like meropenem and piperacillin/tazobactam - are frequently administered to increase the likelihood of an effective therapy. The selection of an appropriate dosing regimen can be complicated and is especially challenging in critically ill patients: The broad range of pathophysiological changes observed in this patient population leads to high pharmacokinetic (PK) variability, which results in substantial differences in drug exposures between patients receiving the same antibiotic drug and dosing regimen. Under the concept of model-informed precision dosing (MIPD), population pharmacokinetic/pharmacodynamic models and patient-specific data (e.g. patient characteristics, drug measurement(s)) can be leveraged to inform and improve dosing decisions in this vulnerable patient population. The objective of the presented thesis was the development, implementation and evaluation of MIPD tools for antibiotic drugs in critically ill patients. To enable the successful integration of MIPD into clinical practice an iterative, integrative and translational approach was followed. The initial and central question ’Is the current antibiotic dosing appropriate?’, was iteratively addressed integrating expertise from a diverse interprofessional team of healthcare professionals and can be segmented into four intermediate steps, all vital to the main objective. First, and as a prerequisite both for model development/evaluation and dosing adaptation, the establishment of a reliable and frequent antibiotic concentration measurement program was required. Second, the collected data was analysed employing pharmacometric and statistical methodology to characterise population PK/pharmacodynamics (PD) and local factors influencing antibiotic therapy (e.g. local pathogen susceptibility). Third, the gained scientific knowledge was translated into easy-to-use, model-informed dosing tools and comprehensive dosing strategies optimised for clinical practice. And fourth, the developed model-informed dosing tools were implemented into clinical routine and subsequently evaluated and optimised. This thesis focused on meropenem and the fixed drug combination piperacillin/tazobactam and addressed individual or multiple of these four steps in three different projects. In Project I, a possible adsorption of the antibiotic meropenem at the cytokine adsorber CytoSorb®, its effect on meropenem exposure and possible consequences for an adequate meropenem dosing were investigated. Despite the absence of clear evidence for a beneficial effect on patients outcomes, the CytoSorb® filter is increasingly used to reduce circulating cytokines in patients experiencing sepsis. Due to its unspecific binding and therefore elimination of molecules up to a molar mass of 55 kDa, concerns have been raised that the CytoSorb® filter unintentionally adsorbs various drugs including meropenem. To investigate if meropenem dosing needs to be increased during CytoSorb® treatment, a nonlinear mixed-effects (NLME) modelling and simulation approach was employed: A population pharmacokinetic model was developed and three distinct approaches to assess if meropenem clearance differed without or during CytoSorb® treatment were applied: (i) quantification of a possible proportional increase in clearance during CytoSorb® treatment (ii) investigation of (non)saturable adsorption at the CytoSorb® filter using different adsorption submodels and (iii) model parameter re-estimation excluding samples collected during CytoSorb® treatment and evaluating the predictive performance for meropenem concentrations during CytoSorb® treatment. In contrast to the expectation of meropenem being adsorped at the CytoSorb® filter, no significant (p<0.05) or relevant effect of CytoSorb® treatment on meropenem exposure was observed. Consequently, neither additional dosing nor a more frequent drug concentration monitoring of meropenem is necessary during the application of CytoSorb® therapy. Project II focused on improving meropenem and piperacillin/tazobactam treatment for critically ill patients at the Charité-Universitätsmedizin Berlin. For this purpose, a 3-staged clinical study was initiated as a coordinated intervention. In stage I, a frequent and reliable concentrations measurement program was implemented to evaluate the current antibiotic therapy. The assessment of the current antibiotic therapy provided insights about local pathogen susceptibility, while highlighting the need for dose individualisation based on patient characteristics: The majority (>90%) of observed pathogens were susceptible to the two administered antibiotic drugs, but target range attainment (minimum antibiotic drug concentrations between 1 and 5 times minimum inhibitory concentration (MIC) of the pathogen) was low for the observed drug concentrations (meropenem: 35.7%, piperacillin: 50.5%) and highly variable between patients with different renal functions. To improve initial meropenem dosing (i.e. prior to the first concentration measurement) and to exploit the newly gained information about the local pathogen susceptibility, a tabular model-informed dosing tool was developed and implemented in stage II of the study. For the development of the tool, an appropriate meropenem PK model was selected from literature and successfully evaluated using the local clinical data. The PK model was then used to conduct stochastic simulations investigating clinically relevant dosing regimens, possible clinical scenarios and the probability of the dosing regimens to achieve adequate drug exposures. To inform dosing prior to pathogen identification, the local pathogen-independent mean fraction of response (LPIFR) was introduced: The LPIFR characterises the probability of a dosing regimen to reach a defined target, e.g. time above the MIC, if only the underlying MIC distribution at a hospital and not the individual MIC of the pathogen causing the infection is known. To inform dosing after MIC value determination, probability of target attainment analyses (PTA) were performed. Dosing recommendations achieving PTA>90% or LPIFR>90% for patients with different creatinine clearances (10.0-300 mL/min) were derived and summarised in one concise and clear table. To assess the potential of the newly developed model-informed dosing tool prior to implementation, the total daily dose of the dosing regimens recommended by the dosing tool for the local study population was compared to the total daily dose of the actually administered dosing regimens. For 77% of the patients with meropenem concentrations outside the target range, the dosing tool suggested a change in daily dose, highlighting the potential of the tool to optimise dosing regimens. To integrate patient individual antibiotic drug measurements and allow for more user flexibility, an interactive model-informed dosing software termed ‘DoseCalculator’ was developed for stage III of the study. In addition to the meropenem PK model already evaluated for stage II of the study, different piperacillin/tazobactam models were extracted from literature, evaluated using the local clinical data collected in stage I of the study and the best performing model implemented into the tool. Based on available knowledge about the infection, three possibilities to calculate the probability of a dosing regimen to reach adequate antibiotic exposures were integrated into the tool: (i) the LPIFR if neither the pathogen nor the MIC is available, (ii) the cumulative fraction of response (CFR) based on the MIC distribution of a specific pathogen if the pathogen is available and (iii) the PTA if the MIC is available. Furthermore, employing a maximum a-posterior (MAP) estimation approach the observed antibiotic drug measurement(s) of a patient can be used in the DoseCalculator to derive patient individual parameter estimates. If drug measurement(s) of a patient are supplied, all analyses and the resulting recommended dosing regimen are based on the individual parameter estimates of the patient. Compared to the observed dosing in stage I, the recommendations of the DoseCalculator led to a substantial relative increase in predicted target attainment (322% meropenem, 505% piperacillin) while reducing the daily dose (median reduction: 77.8% meropenem, 83.4% piperacillin). In Project III the MeroRisk Calculator, an easy-to-use Excel tool to determine the risk of meropenem target non-attainment after standard dosing previously developed at our department, was evaluated using clinical routine data. Since the direct evaluation of the MeroRisk Calculator was not feasible with the available retrospective clinical dataset, a two-step data- and model-based evaluation was conducted: In step one, a meropenem PK model was successfully evaluated using the clinical data. In step two, the evaluated PK model was used as a benchmark for the drug concentration and risk predictions of the MeroRisk Calculator. Compared to the successfully evaluated compartmental PK model, the MeroRisk Calculator provided an equally good and reliable risk assessment (Lin’s concordance correlation coefficient = 0.99) for patients with maintained renal function (creatinine clearance > 50 mL/min). However, for patients with creatinine clearances below 50 mL/min significant deviations were observed. As a consequence, the MeroRisk Calculator should not be used in patients with (severe) renal impairment. In addition to the successful evaluation, the functionality of the MeroRisk Calculator was extended. Based on CFR analysis and EUCAST reported MIC value distributions, risk of target non-attainment can now be assessed depending on the infecting pathogen informing dosing decisions prior to MIC value determination. To conclude, the presented thesis contributed to an individualised and more rational antibiotic drug therapy in critically ill patients. While PK modelling was employed in Project I to exclude a clinically relevant adsorption of meropenem at the CytoSorb® filter, Project II and Project III represent a successful example on development, implementation and evaluation of MIPD tools. As a next step, both the tabular model-informed dosing tool and the DoseCalculator should be prospectively evaluated at Charité-Universitätsmedizin Berlin. The results from this evaluation in particular and this thesis demonstrate the potential of MIPD using comprehensive examples on how to develop, implement and evaluate model-informed dosing tools and contribute to the accelerating implementation of MIPD into clinical practice

Preclinical pharmacokinetic evaluation of novel antimalarial and antituberculosis drug leads

Preclinical pharmacokinetics relies on efficient and accurate screening to select clinical candidates from early leads. Poor pharmacokinetic interpretation can disadvantage drug discovery by promoting inadequate compounds and expelling potential drug candidates. Objectives of this project included pharmacokinetic evaluation of antimalarial and anti-tuberculosis lead compounds with techniques aimed at improving preclinical pharmacokinetic outcomes. This included mechanistic pharmacokinetic approaches such as non-linear mixed effects (NLME) modelling in comparison with traditional non-compartmental analysis. Where appropriate, pharmacokinetic methods were expanded to include organ distribution and capsule dosing in mice to bridge our techniques from discovery to early development. Three benzoxazole amodiaquine analogues possessing equipotent in vitro antiplasmodial activity and showed diverse in vivo efficacy in a malaria mouse model. Evaluation of their respective pharmacokinetics in mice showed their in vivo exposures could translate to in vivo efficacy. Retrospective PK/PD simulations point to a time above IC50 drive in efficacy. Pharmacokinetic evaluation of an aminopyridine antimalarial compound in its cyclodextrin inclusion complex revealed a pH dependent increase in solubility that reduced variance, likely due to favoured intestinal absorption. Investigation of two novel fusidic acid C-3 ester prodrugs aimed at repositioning fusidic acid for tuberculosis, showed high concentrations of the rodent specific 3-epifusidic acid metabolite that greatly reduced exposure of fusidic acid in mice. Further organ distribution studies showed a prodrug strategy is still viable for repositioning fusidic acid for tuberculosis, but that rodent models are inappropriate for further evaluation. NLME modelling successfully provided unique mechanistic and mathematical insight of pharmacokinetic profiles of new leads. The level of interpretation on pharmacology parameters improved and aided in understanding why drug leads are likely to fail or succeed, assisting future compound optimisation

Tramadol in the elderly : pharmacokinetic and pharmacodynamic modelling in healthy young and elderly subjects

Même si la douleur est très fréquente chez les personnes âgées et que ces dernières sont parmi les plus grands utilisateurs d'analgésiques, les preuves factuelles supportant les décisions médicales sont limitées. Récemment, une revue systématique des essais cliniques portant sur les douleurs aigues au bas du dos a permis de constater que les adultes de plus de 65 ans étaient systématiquement exclus des essais cliniques randomisés en dépit des incitations règlementaires à inclure de tels patients dans ces études. Les données en pharmacocinétique (PK) et pharmacodynamie (PD) concernant les analgésiques chez les patients du troisième âge, particulièrement les personnes âgées de plus de 75 ans, sont rares. Comprendre la relation pharmacocinétique-pharmacodynamique (PK/PD) des médicaments employés pour traiter les conditions qui affectent communément nos ainés est fondamentale pour un traitement optimal leur permettant de conserver une bonne qualité de vie et leur dignité et ce, tout en minimisant les effets secondaires délétères. Le tramadol est un opioïde faible communément employé chez les personnes âgées pour soulager la douleur. Pourtant, il y a peu de données sur sa relation PK/PD chez ces mêmes personnes. Plusieurs essais cliniques visant à établir l’efficacité d’un médicament, et en particulier les analgésiques, produisent des résultats non concluants ou négatifs; les modèles expérimentaux de douleur offrent l'opportunité de comprendre la PD des analgésiques au moyen d’études de plus petite échelle qui minimisent les circonstances environnementales pouvant introduire un biais. Les analyses PK/PD par approche de population permettent d'optimiser les régimes posologiques et de concevoir des essais cliniques qui prennent en considération les connaissances acquises. Le modèle expérimental de douleur employé dans ce programme de recherche nous donne une façon d'évaluer les différences de tolérance à la douleur entre sujets jeunes et âgés de façon quantitative. L'objectif de cette thèse est de contribuer au savoir en caractérisant la relation PK/PD du tramadol et de son métabolite actif, ODM, chez les patients de 75 ans et plus, afin de déterminer s'il existe des différences reliées à l'âge. Nous avons conduit une étude PK et PD à répartition aléatoire, contrôlée par placébo, comportant deux périodes en chassé-croisé. Treize sujets âgés de plus de 75 ans ayant une insuffisance rénale légère et 16 sujets âgés entre 18 et 40 ans ont été recrutés. Des échantillons de sang et d'urine ont été recueillis sur une durée de 48 heures post-dose. Un modèle expérimental de douleur à base de stimulation électrique a été employé pour évaluer le seuil de tolérance à la douleur (PTT), soit l'intensité maximale qu'un sujet est en mesure de tolérer et ce, employant un stimulus douloureux mais non blessant appliqué au doigt non dominant. Le PTT a été testé à des fréquences de 250 et 5 Hertz et ce, à 17 moments sur une période de 30 heures post-dose. Une analyse PK noncompartimentale (NCA) approfondie des concentrations plasmatiques et urinaires du (+) et (-) tramadol et du (+)- et (-)-ODM de même qu'une analyse PK par approche de population du tramadol ont d’abord été exécutées. Ces analyses ont démontré que l'exposition générale au tramadol chez les patients âgés est comparable à celle des plus jeunes. Aucunes différences dans les processus d'absorption n'ont été observées. Cependant, une différence significative a été observée au niveau de la demi-vie d’élimination du tramadol chez les personnes âgées, probablement à cause d’une augmentation de sa distribution corporelle. Les différences les plus notables se situent au niveau de la PK de l'(+)-ODM, le métabolite ayant une activité opioïde. Ses concentrations plasmatiques maximales ont été observées plus tard et ont décru plus lentement chez les personnes âgées que chez les jeunes. L'exposition à l' (+)-ODM était significativement plus grande chez les sujets âgés, et tant la clairance rénale que la clairance corporelle totale étaient plus lentes. L’analyse PK populationnelle a confirmé ces observations et identifié qu'une distribution supérieure de même qu'une élimination moyenne de 50% plus longue pour le tramadol chez les sujets âgés. Il est important de souligner que, dans notre groupe de personnes âgées, l'insuffisance rénale était plus fréquente que l'insuffisance hépatique. Par la suite, avant de procéder à l’analyse populationnelle pour établir une relation entre les concentrations de l’ODM et les seuils de tolérance à la douleur, nous avons analysé les données pharmacodynamiques sous les périodes placébo et tramadol afin de valider le nouveau modèle expérimental de douleur proposé. Nous souhaitions sélectionner le stimulus électrique (5 Hz ou 250 Hz) qui soit le plus sensible pour détecter un changement au niveau de hla tolérance à la douleur. Tant les jeunes sujets que les plus âgés ont démontré des valeurs de base similaires pour le seuil de tolérance à la douleur et ce, aux deux fréquences sous administration active et placébo. Chez les personnes âgées, la valeur maximale du PTT était de 30% supérieure sous tramadol comparativement au placébo et ce, tant à 5 Hz que 250 Hz; toutefois, la réponse était plus variable pour la dernière fréquence. La tolérance à la douleur, telle que mesurée par la surface sous la courbe de l’effet en fonction du temps (AUEC) sur une période de 24 heures, était significativement plus élevée (au-delà de 160%) chez les personnes âgées pendant le traitement actif comparativement au placebo pour les deux fréquences de stimulation; toutefois, aucune différence significative au niveau de la tolérance n'a été observée chez les plus jeunes. Nous avons émis l’hypothèse que cette différence pouvait résulter de la plus grande exposition des sujets âgés à l' (+)-ODM. Par conséquent, une analyse PK/PD devenait nécessaire pour déterminer si ces changements au niveau du seuil de tolérance à la douleur chez les personnes âgées étaient reliés à une plus grande exposition à l'(+)-ODM. Finalement, en utilisant des concentrations plasmatiques de (+)-ODM et les données PTT obtenues avec le stimulus de 5 Hz, nous avons conduit une analyse populationnelle exploratoire pour déterminer tout effet de l'âge sur la relation entre les concentrations plasmatiques de (+)-ODM et la tolérance à la douleur. En dépit de valeurs de base semblables pour la tolérance à la douleur, l'effet maximal possible relié au traitement était de 15% supérieur chez les sujets âgés, ce qui pourrait s’expliquer par une exposition plus élevée au métabolite actif, confirmant son mécanisme d'action opioïde. La concentration plasmatique associée à 50% de l’effet maximal n’était pas différente chez le sujet jeune et âgé, indiquant que l’âge n’est pas associé avec une plus grande sensibilité à l’ (+)-ODM. En conclusion, ceci est le premier programme de recherche ayant étudié extensivement la PK et PD du tramadol chez les patients de 75 ans et plus. La valeur de ce programme de recherche va au-delà d'une meilleure compréhension de la PK du tramadol, en améliorant notre compréhension des contributions relatives des clairances rénale et totale au niveau des changements survenant avec l'âge pour la PK du tramadol et de son métabolite actif chez les personnes âgées en relativement bonne santé. Ce programme contribue également au développement de modèle permettant d’effectuer davantage de recherches chez les personnes âgées puisqu’il est le premier modèle PK/PD populationnel de (+)-ODM chez les sujets de 75 ans et plus. Nos analyses démontrent que les changements reliés à l'âge dans la clairance rénale peuvent résulter en un accroissement proportionnel de l'exposition à l'ODM, et pourraient expliquer les observations faites par certains cliniciens dans la littérature qui rapportent une augmentation des effets (secondaires) à des doses équivalentes chez les personnes âgées. Ceci est d’autant plus de pertinence clinique que l'efficacité et les effets secondaires du tramadol découlant de sa nature opiacée, notamment la sédation, sont principalement reliés à l’(+)-ODM et le seraient davantage chez des patients âgés fragilisés souffrant d’une insuffisance rénale plus prononcée que celle des sujets étudiés au cours de notre recherche.Although pain is highly prevalent among the elderly and they are amongst the highest users of analgesics, research to support evidence based treatment decisions is limited. Recently a systematic review of clinical trials in low back pain found that elderly adults older than 65 were systematically excluded from randomised clinical trials despite calls to include elderly subjects in such studies. Pharmacokinetic (PK) and Pharmacodynamic (PD) data on analgesics in elderly patients, especially those older than 75 years, is sparse. Understanding the pharmacokinetic/pharmacodynamic relationship (PK/PD) of medicines used to treat conditions that commonly affect elderly people is key to treating them effectively, allowing them to live with quality of life and dignity and minimising the side effects that can interfere with this. Tramadol is a weak opioid commonly used in elderly patients for pain relief. Yet there is little data on its PK/PD in the elderly. Many later phase clinical trials, especially in analgesics produce inconclusive or negative results; experimental pain models offer the opportunity to understand the PD of analgesics on a smaller scale and minimise confounding environmental circumstances. Population PK/PD analyses of early research data permit the optimisation of dosing regimens and of the design of phase III clinical trials by taking into account what is learned. The pain model utilised in this research program gives us a way to look at the differences in pain tolerance between young and elderly in a quantitative fashion. The objective of this thesis is to contribute to the knowledge about age-related differences in the PK/PD of tramadol and its active metabolite O-desmethyltramadol (ODM) in subjects 75 years and older in order to examine whether there are age-related differences. We conducted a double-blind randomised, placebo-controlled, two-period crossover study including 13 elderly subjects (≥75 years) with mild renal insufficiency and 16 young (18-40 years) subjects. Blood samples and urine were collected for 48 hours post-dose. An electrically stimulated pain model (ESPM) was used to test pain tolerance threshold (PTT), the maximum intensity a subject is willing to tolerate, using a painful but non-injuring electrical stimulus applied to the non-dominant middle finger. PTT was tested at both 250 and 5 Hz at each of 17 time-points over 30 hours after a 200 mg dose of extended release tramadol . An in depth noncompartmental analysis of the PK of (+)- and (-)-tramadol and (+)- and (-)-ODM plasma and urine concentrations as well as a population PK analysis of tramadol were performed. Maximum plasma concentrations of (+)-ODM, the active metabolite, occurred later and plasma concentrations declined more slowly in the elderly than in young subjects. These analyses showed that overall exposure to tramadol in elderly subjects is comparable to that in young subjects. No differences in absorption processes were observed. However, there was a significant difference in tramadol elimination half-life, most probably due to increased distribution in elderly subjects. The most remarkable differences were in the PK of (+)-ODM, the metabolite with opioid activity. Exposure to ODM was significantly greater in elderly subjects and both renal and overall clearance from the body were slower. The population PK analysis supported our findings and identified that a higher distribution and a 50% longer mean elimination half-life was associated with age of 75 or older. A key observation was that in our study population renal insufficiency was more prevalent in the elderly subjects than hepatic insufficiency. Subsequently, in preparation for a population analysis of the PK and pain tolerance effect of tramadol’s active metabolite, (+)-ODM, we analysed pain tolerance data under placebo and tramadol administration to validate the exploratory experimental pain model that we used. We wanted to select the electrical stimulus (5 Hz or 250 Hz) that was most sensitive to detect changes in pain tolerance. Young and elderly subjects showed similar baseline pain tolerance at both 5 Hz and 250 Hz before administration of active and placebo, suggesting that pain tolerance is similar in either frequency. In the elderly, the peak pain tolerance was 30% greater for both 5 and 250 Hz after administration of tramadol as compared to placebo, but the response was noisier for the last frequency. The net pain tolerance over the 24 hours, as measured by area under the effect-time curve (AUEC) during active treatment was significantly higher (over 160%) compared to placebo for both 5 and 250 Hz stimulations in the elderly but no significant difference was observed in the young. We hypothesised that this difference might be due to the higher exposure of elderly subjects to ODM. And therefore, a PK/PD analysis was required to determine whether these age-related changes were due to altered sensitivity in elderly subjects to PTT or to a greater exposure to the active (+)-ODM metabolite. Finally utilising plasma concentrations of (+)-ODM and the PTT data from the 5 Hz stimulus, we conducted an exploratory population analysis to determine any age-related effects on the relationship between (+)-ODM concentrations and pain tolerance threshold. Although pain tolerance was similar between young and elderly subjects at baseline, there was a 15% higher maximum possible treatment-related effect that may be associated with the higher systemic exposure to ODM., the active metabolite, thereby confirming its opioid mechanism of action. The concentration at which 50% of effect was achieved was not reduced between the young and elderly, indicating that age was not associated with greater sensitivity to (+)-ODM. In conclusion, this is the first research program to extensively report the PK and PD of tramadol in subjects 75 and older. The value of this research program goes beyond that of a better understanding of the PK of tramadol, by delineating the relative contribution of renal clearance versus overall clearance to age-related alterations in the PK of tramadol and ODM in generally healthy elderly people. This research program also contributes to the development of population models to support further research in the elderly being the first population PK/PD model developed for (+)-ODM in subjects 75 and older. Our findings show that age-related changes in renal clearance versus overall clearance can result in a proportional increase in ODM exposure, and may explain the observation of some clinicians and literature that there is increased side effects at equivalent doses in the elderly. This is potentially of clinical significance since opioid-related efficacy and side effects of tramadol, among them sedation, are primarily linked to (+)-ODM and the risk of side effects would likely be greater in frail elderly subjects with greater renal impairment than those studied in our research

Statistical analysis of bioequivalence studies

A Research Report submitted to the Faculty of Science in partial fulfilment of the requirements for the degree of Master of Science. 26 October 2016.The cost of healthcare has become generally expensive the world over, of which the greater part of the money is spent buying drugs. In order to reduce the cost of drugs, drug manufacturers came up with the idea of manufacturing generic drugs, which cost less as compared to brand name drugs. The challenge which arose was how safe, effective and efficient the generic drugs are compared to the brand name drugs, if people were to buy them. As a consequence of this challenge, bioequivalence studies evolved, being statistical procedures for comparing whether the generic and brand name drugs are similar in treating patients for various diseases. This study was undertaken to show the existence of bioequivalence in drugs. Bioavailability is considered in generic drugs to ensure that it is more or less the same as that of the original drugs by using statistical tests. The United States of America’s Food and Agricultural Department took a lead in the research on coming up with statistical methods for certifying generic drugs as bioequivalent to brand name drugs. Pharmacokinetic parameters are obtained from blood samples after dosing study subjects with generic and brand name drugs. The design for analysis in this research report will be a 2 2 crossover design. Average, population and individual bioequivalence is checked from pharmacokinetic parameters to ascertain as to whether drugs are bioequivalent or not. Statistical procedures used include confidence intervals, interval hypothesis tests using parametric as well as nonparametric statistical methods. On presenting results to conclude that drugs are bioequivalent or not, in addition to hypothesis tests and confidence intervals, which indicates whether there is a difference or not, effect sizes will also be reported. If ever there is a difference between generic and brand name drugs, effect sizes then quantify the magnitude of the difference. KEY WORDS: bioequivalence, bioavailability, generic (test) drugs, brand name (reference) drugs, average bioequivalence, population bioequivalence, individual bioequivalence, pharmacokinetic parameters, therapeutic window, pharmaceutical equivalence, confidence intervals, hypothesis tests, effect sizes.TG201