Incidence and risk factors of major bleeding following major orthopaedic surgery with fondaparinux thromboprophylaxis. A time-to-event analysis.

AIMS: Increased exposure to fondaparinux, as observed in patients with renal impairment, may increase bleeding risk. This study aims to determine the time course of major bleeding after major orthopaedic surgery, identify predictors of bleeding and simulate the effect of a reduced dose of fondaparinux on bleeding for patients with moderate renal impairment (creatinine clearance = 20-50 ml min-1 ). METHODS: Data including fondaparinux anti-Xa activities from two multicentre prospective cohorts were used. In the first cohort, patients (n = 957) received fondaparinux 2.5 mg once a day. In the second, patients with moderate renal impairment (n = 436) received 1.5 mg once per day. The time-to-major bleeding after the end of surgery was modelled using a parametric survival analysis in NONMEM. RESULTS: The observed rate of major bleeding up to day 11 was 5.2%. The time-to-event analysis indicated that the hazard of bleeding was highest in the first days following surgery and then remained low thereafter. Independent significant predictors of an increased hazard of major bleeding were male sex, lower body weight and increased drug exposure. Simulated rates of major bleeding up to day 11 in patients with moderate renal impairment were 6.5% with fondaparinux 2.5 mg once daily and 3.8% with fondaparinux 1.5 mg once daily. CONCLUSION: The hazard of major bleeding is highest in the first postoperative days and increases with fondaparinux exposure. To reduce the risk of bleeding in patients with moderate renal impairment, this study supports the use of a lower dose of fondaparinux 1.5 mg once daily.

A model-based meta-analysis of the influence of factors that impact adherence to medications.

WHAT IS KNOWN AND OBJECTIVE: Several studies have investigated factors that may influence adherence for a given disease. The influence of disease on adherence has received limited attention. Less work has been conducted to investigate the influence of other factors in conjunction with disease on adherence. The aim of this study was to determine the independent influence of disease and other factors on adherence. METHODS: A literature search was conducted to retrieve adherence studies using medication event monitoring system devices. Studies were categorized into different therapeutic areas. Only the two most commonly studied therapeutic areas were selected. Pseudopatient-level data were extracted from each study. The extracted data were analysed using a model-based meta-analysis technique. Univariate and multivariate models were developed. Model selection was based on a likelihood ratio test and visual plots. RESULTS: The most commonly studied therapeutic areas were HIV and hypertension. The most commonly recorded adherence criterion was percentage of prescribed doses taken per day. Based on this adherence criterion, ultimately, 24 HIV papers and 12 hypertension papers were included for data extraction. The statistically significant factors were disease, age and dosing regimen. The independent influences of each factor on adherence were as follows: an increase in adherence of approximately 8% per 10-year increase of age, a 15-19% reduction from once to thrice daily dosing and that patients with HIV were 5% more adherent than those with hypertension. WHAT IS NEW AND CONCLUSION: Although the influence of disease on adherence was significant, it was of limited clinical significance in the diseases studied here. Adherence appears to improve with age and decline with more frequent dosing. Additionally, the influence of dosing regimen wanes with increasing age. These results should be treated as exploratory and require prospective assessment.

A learning-based approach for performing an in-depth literature search using MEDLINE.

WHAT IS KNOWN AND OBJECTIVE: Exhaustive literature searching is a core requirement for developing guidelines for evidence-based practice. MEDLINE is typically used. Searching requires the user to identify appropriate search terms, called Medical Subject Headings (MeSH) and refine the search to retrieve relevant articles. The objective of this study was to develop and test a learning algorithm for conducting a thorough literature search. METHODS: A learning algorithm to effectively utilize MeSH terms is presented. This algorithm creates combinations of available MeSH terms from which a search is conducted. The algorithm was applied to search MEDLINE (January 1950 to Janaury 2008) focusing on the impact of pharmaceutical care in HIV-infected patients. The number of relevant articles retrieved from the learning algorithm search was then compared against a static search with a fixed set of keywords implemented by an independent user. RESULTS AND DISCUSSION: The learning algorithm retrieved 1670 articles with six relevant articles identified. The static search retrieved a total of 49 articles, with three being relevant. These three articles were also located from the learning algorithm-based search. WHAT IS KNOWN AND CONCLUSION: Performing a literature search for retrieving evidence-based studies can be a daunting and error-prone process. The introduction of automatic, learning tools for searching is desirable and we present a possible approach.

Optimal design criteria for discrimination and estimation in nonlinear models.

Nonlinear models are common in pharmacokinetics and pharmacodynamics. To date, most work in design in this area has concentrated on parameter estimation. Here, we introduce the idea of optimization of both estimation and model selection. However, experimental designs that provide powerful discrimination between a pair of competing model structures are rarely efficient in terms of estimating the parameters under each model. Conversely, designs which are efficient for parameter estimation may not provide suitable power to discriminate between the models. Several different methods of addressing both of these objectives simultaneously are introduced in this paper and are compared to an existing optimality criterion.

Simultaneous versus sequential optimal design for pharmacokinetic-pharmacodynamic models with FO and FOCE considerations.

We consider nested multiple response models which are used extensively in the area of pharmacometrics. Given the conditional nature of such models, differences in predicted responses are a consequence of different assumptions about how the models interact. As such, sequential versus simultaneous and First Order (FO) versus First Order Conditional Estimation (FOCE) techniques have been explored in the literature where it was found that the sequential and FO approaches can produce biased results. It is therefore of interest to determine any design consequences between the various methods and approximations. As optimal design for nonlinear mixed effects models is dependent upon initial parameter estimates and an approximation to the expected Fisher information matrix, it is necessary to incorporate any influence of nonlinearity (or parameter-effects curvature) into our exploration. Hence, sequential versus simultaneous design with FO and FOCE considerations are compared under low, typical and high degrees of nonlinearity. Additionally, predicted standard errors of parameters are also compared to empirical estimates formed via a simulation/estimation study in NONMEM. Initially, design theory for nested multiple response models is developed and approaches mentioned above are investigated by considering a pharmacokinetic-pharmacodynamic model found in the literature. We consider design for situations where all responses are continuous and extend this methodology to the case where a response may be a discrete random variable. In particular, for a binary response pharmacodynamic model, it is conjectured that such responses will offer little information about all parameters and hence a sequential optimization, in the form of product design optimality, may yield near optimal designs.

A model for venom-induced consumptive coagulopathy in snake bite.

Many snake venoms contain procoagulant toxins that activate the coagulation cascade and cause venom-induced consumptive coagulopathy (VICC). We developed a semi-mechanistic model of the clotting cascade in order to explore the effects of the procoagulant toxin from taipan venom on this system as well as the effects of antivenom. Simulations of the time course in the change of clotting factors were compared to data collected from taipan envenomed patients. The model accurately predicted the observed concentration of clotting factors over time following taipan envenomation. Investigations from the model indicated that the upper limit of the half-life of the procoagulant toxin was 1h. Simulations from the model also suggest that antivenom for Australasian elapids has negligible effect on reducing the recovery time of the coagulation profile unless administered almost immediately after envenomation. The model has generality to be expanded to describe the effects of other venoms and drugs on the clotting cascade.

Compound optimal design criteria for nonlinear models.

Three approaches for combining parameter estimation with opposing design criteria are proposed for nonlinear models. The first method discussed is the technique found in the literature and as such is the reference method for this paper. The compound crtierion is formed by maximizing a weighted product of efficiencies. The second criterion involves maximizing an opposing criterion while minimizing a defined loss function. The third method simultaneously maximizes both efficiencies with respect to parameter estimation and an opposing criterion with a multiple objective simulated annealing algorithm. The examples presented are based on a PK-model and a generalized linear model found in the literature.

Pharmacokinetics of quetiapine in overdose and the effect of activated charcoal.

The aim of the study was to investigate the pharmacokinetics of quetiapine overdose and the effect of charcoal. The data set included 204 concentration-time points from 54 quetiapine overdose events (median dose 2,700 mg (300-24,000 mg)). Charcoal was administered 0.5-6 h after 19 overdoses. A fully Bayesian methodology for population pharmacokinetic analysis was used and data were modelled using WinBUGS. Uncertainty in the dose history was considered in model building by estimating dose amount and dose time within a possible range. Inclusion of informative priors stabilized the model and population parameter values could be estimated well. A one-compartment model with first-order input and first-order elimination described the data. The final model included uncertainty in dose time. The median and interquartile range of the half-life for individual patients was 6.6 h (4.9-8.4 h). Charcoal was estimated to reduce fraction absorbed by 35%. Co-ingested CYP3A4 inhibitors appeared to decrease clearance and CYP3A4 inducers increase clearance. Charcoal administration may be beneficial after quetiapine overdose.

Optimal designs for studying bioimpedance.

D-optimal designs for nonlinear fixed and mixed effects models are explored, and the theory is applied to the measurement and analysis of bioelectrical impedance. Bioimpedance is known to vary more at extreme frequencies than others. D-optimal designs that account for this variation, and also possible mis-specification of initial parameter estimates, are considered in an attempt to find designs that will provide good parameter estimates in practice.

Warfarin Dosing Algorithms Underpredict Dose Requirements in Patients Requiring ≥7 mg Daily: A Systematic Review and Meta-analysis.

There is preliminary evidence to suggest that some published warfarin dosing algorithms produce biased maintenance dose predictions in patients who require higher than average doses. We conducted a meta-analysis of warfarin dosing algorithms to determine if there exists a systematic under- or overprediction of dose requirements for patients requiring ≥7 mg/day across published algorithms. Medline and Embase databases were searched up to September 2015. We quantified the proportion of over- and underpredicted doses in patients whose observed maintenance dose was ≥7 mg/day. The meta-analysis included 47 evaluations of 22 different warfarin dosing algorithms from 16 studies. The meta-analysis included data from 1,492 patients who required warfarin doses of ≥7 mg/day. All 22 algorithms were found to underpredict warfarin dosing requirements in patients who required ≥7 mg/day by an average of 2.3 mg/day with a pooled estimate of underpredicted doses of 92.3% (95% confidence interval 90.3-94.1, I2 = 24%).

A Philosophical Framework for Integrating Systems Pharmacology Models Into Pharmacometrics.

The framework for systems pharmacology style models does not naturally sit with the usual scientific dogma of parsimony and falsifiability based on deductive reasoning. This does not invalidate the importance or need for overarching models based on pharmacology to describe and understand complicated biological systems. However, it does require some consideration on how systems pharmacology fits into the overall scientific approach.

A framework for quantifying the influence of adherence and dose individualization.

A failure to accommodate for a patient's imperfect adherence may result in therapeutic failure. Similarly, failure to accommodate a patient's individual needs via dose individualization may also result in poor patient outcomes. The property of a drug that signifies the likelihood of therapeutic success to imperfect adherence is termed "forgiveness." We introduce an extension to this concept as: (1) a priori forgiveness (forgiveness when dose individualization is not considered) and (2) a posteriori forgiveness (forgiveness when considering dose individualization). We illustrate cases when adherence is of primary importance and in which dose individualization is of primary importance. The concept of a priori forgiveness and a posteriori forgiveness provides a quantitative measure that allows the influence of adherence to be disentangled from dose individualization and could be used to provide clear guidelines about the relative importance of each in clinical practice.

Quantification of the Forgiveness of Drugs to Imperfect Adherence.

The circumstance of how sensitive therapeutic success is under imperfect adherence is driven by the property known as forgiveness. To date, no studies have considered variability in the pharmacokinetic-pharmacodynamic process in conjunction with imperfect adherence patterns in order to develop a comparative criterion to determine the forgiveness of a drug. In this study, we have proposed a criterion to quantify forgiveness; illustrated the criterion for a theoretical example and evaluated the forgiveness of a motivating example, namely warfarin. A forgiveness criterion, relative forgiveness, is defined as the number of times more likely that a target is successfully attained under perfect adherence compared to imperfect adherence; or when comparing two drugs under a standard setting of imperfect adherence. The relative forgiveness criterion may have important implications for both drug development and clinical practice since the choice of drug can account for the likely influence of its forgiveness.

Clinical pharmacokinetics and dose optimisation of carboplatin.

Carboplatin shares some of the therapeutic advantages of cisplatin, but without a significant incidence of the dose-limiting neurotoxicity and nephrotoxicity which is experienced with cisplatin. However, its use is associated with dose-limiting bone marrow suppression. Carboplatin is present in the blood as 3 distinct species. These are total platinum and 2 unbound species, carboplatin itself and a decarboxylated platinum-containing degradation product. The 2 main methods used to assay the unbound species are flameless atomic absorption spectrophotometry and high performance liquid chromatography. The first of these methods assays both unbound platinum species, the second is specific for carboplatin. Both unbound species have similar pharmacokinetic profiles for the first 12 hours post-dose. Carboplatin appears to have a linear pharmacokinetic profile over the doses used clinically and does not interact significantly with drugs that are used commonly in combination chemotherapy. The pharmacokinetics of carboplatin are adequately described by an open 2-compartment model with elimination from the central compartment. Its clearance is proportional to the glomerular filtration rate and the volume of distribution of the central compartment appears to correlate with extracellular fluid volume. The elimination half-life varies with renal function and is typically between 2 and 6 hours in patients with a normal glomerular filtration rate and may be as long as 18 hours in patients with impaired renal function. Relationships between systemic exposure to carboplatin, described as the area under the concentration-time curve (AUC), and both toxicity and response have been described. For toxicity the strongest evidence exists for a relationship between AUC and thrombocytopenia. To a lesser extent the relationship between AUC and neutropenia has also been described. Patients already treated with platinum analogues have been shown to develop a greater degree of myelosuppression from any given AUC. In addition, some evidence suggests a relationship between the shape of the concentration-time curve and myelotoxicity, where constant infusions appear less likely to cause myelosuppression on a mg/m2 dose administration basis. The relationship between AUC and response rate is not as clear, this may be related to the lack of studies describing both the dose and AUC of carboplatin. There appears to be a more clearly defined AUC-response relationship for ovarian cancer than for other malignancies, with an AUC of between 5 and 7 mg/ml.min being associated with the maximal response rate [located at the plateau on an AUC-response curve]. However, new data suggest that higher AUCs may lead to greater response rates. Data from testicular cancer also strongly supports an AUC-response relationship with an increased number of treatment failures with carboplatin AUCs < 5 to 6 mg/ml.min. Given the AUC-effect relationships described above a number of studies have been performed to develop models to describe the relationship between both dose and AUC and dose and platelet nadir. In adults, perhaps the most common method is that of Calvert which describes the relationship between dose and AUC. Paediatric formulas have also been described. More recently a number of limited sampling strategies have been proposed as well as Bayesian dose individualisation techniques.

Pharmacokinetic software for the health sciences: choosing the right package for teaching purposes.

Computer assisted learning has an important role in the teaching of pharmacokinetics to health sciences students because it transfers the emphasis from the purely mathematical domain to an 'experiential' domain in which graphical and symbolic representations of actions and their consequences form the major focus for learning. Basic pharmacokinetic concepts can be taught by experimenting with the interplay between dose and dosage interval with drug absorption (e.g. absorption rate, bioavailability), drug distribution (e.g. volume of distribution, protein binding) and drug elimination (e.g. clearance) on drug concentrations using library ('canned') pharmacokinetic models. Such 'what if' approaches are found in calculator-simulators such as PharmaCalc, Practical Pharmacokinetics and PK Solutions. Others such as SAAM II, ModelMaker, and Stella represent the 'systems dynamics' genre, which requires the user to conceptualise a problem and formulate the model on-screen using symbols, icons, and directional arrows. The choice of software should be determined by the aims of the subject/course, the experience and background of the students in pharmacokinetics, and institutional factors including price and networking capabilities of the package(s). Enhanced learning may result if the computer teaching of pharmacokinetics is supported by tutorials, especially where the techniques are applied to solving problems in which the link with healthcare practices is clearly established.

Idiosyncratic drug-induced haematological abnormalities. Incidence, pathogenesis, management and avoidance.

Haematological dyscrasias remain important because they are potentially fatal. Their accurate reporting is required to confirm the cause-effect relationship of suspected adverse drug reactions (ADRs); to estimate their incidence; and, by risk-benefit analysis of such events, to introduce preventive measures to reduce their impact. Limitations within the available data on haematological ADRs are reviewed and some suggestions made for improvement. The drugs most commonly associated with haematological dyscrasias are listed. An understanding of the pathogenesis of haematological dyscrasias is essential for their effective management and these are briefly reviewed. Features common to the management of the different types of haematological dyscrasia include the early involvement of a haematologist and drug information pharmacist and the accurate identification and early withdrawal of any likely offending agent. Guidelines for the management of drug-induced aplastic anaemia, agranulocytosis, thrombocytopenia and haemolytic anaemia are presented and the potential value of granulocyte and granulocyte-macrophage colony-stimulating factors (G-CSF; GM-CSF) in the management of agranulocytosis is specifically mentioned. Finally, general principles are discussed whereby serious haematological ADRs might be prevented. These include: the importance of continuing education for drug prescribers; policies on the restricted prescribing of likely offending agents; the use of written instructions for patients; and, the use of haematological monitoring. The guidelines presented in this article should be adapted to meet local circumstances and would prove suitable subjects for audit of their effectiveness.

A sequential Bayesian algorithm for dose individualisation of carboplatin.

Carboplatin is associated with significantly less nephrotoxicity and neurotoxicity than is cisplatin. The dose-limiting toxicity of carboplatin is myelotoxicity. A number of dosing methods have been described that allow a value for the area under the concentration-time curve to be targeted on the basis of the patient's renal function. Recently a formalised analysis of the pharmacodynamic response to carboplatin revealed a therapeutic window in which the response rate was maximal and toxicity, tolerable. Optimal therapy would result from targeting this window in the individual patient. The aim of this study was to develop a Bayesian dose-individualisation method for carboplatin. The method involved (1) development of a high-performance liquid chromatography (HPLC) method to measure serum concentrations of carboplatin; (2) a pharmacokinetic study in 12 women receiving carboplatin for ovarian cancer to estimate the population pharmacokinetic values for this group of patients; (3) development of population models to describe the concentration-time course of carboplatin in serum along with associated errors; and (4) development of an algorithm that uses a sequential Bayesian design, which enables estimation of future doses of carboplatin on the basis of feedback from serum concentrations. The results of each of the stages were (1) the coefficient of variation of the assay was 6.3% within day and 8.4% between days (r2 = 0.9993), and the limit of detection was 0.25 mg/l; (2) Patients' ages ranged from 49 to 68 years, their weights varied from 46 to 85 kg, and their glomerular filtration rate ranged from 3.2 to 7.4 l/h. A geometric mean clearance (Cl) of 6.8 L/h and a steady-state volume of distribution (Vss) of 221 were estimated, which are similar to previously published data; (3) and a two-compartment model best described the data. Two error models were developed, the first describing the error associated with the assay and the second, the error of the two-compartment model, i.e. error due to individual variation in pharmacokinetics and error due to model mis-specification. Finally, (4) the development of a sequential Bayesian dose-individualisation method for carboplatin is described. To our knowledge, this is the first sequential design that has been used for dose individualisation of chemotherapy. The program is specific for carboplatin and operates independently of commercially available Bayesian software. Doses predicted by this program are being tested prospectively against conventional dosing methods.

Pharmacokinetics and efficacy of rectal versus oral sustained-release morphine in cancer patients.

Sustained-release morphine (MST) given by the rectal route was compared with oral MST in an open randomised cross-over trial in ten patients with cancer who received stable doses of MST. No significant difference was found in the areas under the curve of the concentration-time profiles (AUC) following oral or rectal administration for parent morphine. The AUCs determined for morphine-6-glucuronide (M6G) and morphine-3-glucuronide (M3G) after oral administration were approximately twice those obtained following rectal administration. The maximal concentration achieved was lower and the time to maximal concentration was longer following rectal administration for morphine, M6G and M3G. The relative mean arrival times following rectal administration were significantly longer for morphine and M3G but not for M6G. These findings suggest slower absorption but less first-pass metabolism of MST after rectal administration. No significant difference was noted between the oral and the rectal route in measurements on visual-analogue scales for pain or side effects. We recommend the rectal route as being suitable for MST administration when the oral route is no longer available. In changing from oral to rectal administration, the same dose and dose interval may be used, but dose adjustment may be needed.

Development of a sequential linked pharmacokinetic and pharmacodynamic simulation model for ivabradine in healthy volunteers.

Ivabradine is a novel bradycardic agent that has been developed for the prevention of angina. Ivabradine has an active metabolite S-18982. The aim of the study was to develop a linked pharmacokinetic-pharmacodynamic simulation model for the description of exercise-induced heart rate. The pharmacodynamic data (heart rate) were pooled from two studies and included a total of 78 healthy subjects. The data consisted of multiple dose oral administration of ivabradine. The multiple dose regimens were administered every 12 h. There were eight active dosing levels and placebo, and a no-dose run in the period before each study. The modelling was performed using the NONMEM software. Both ivabradine and S-18982 possess bradycardic activity, although the extent of the activity of both could not be determined from the data available. A multiple ligand pharmacodynamic model provided the best fit to the data. The model was assessed in terms of its posterior predictive performance and was able to describe the original data adequately when used for simulation purposes.

A pharmacokinetic simulation model for ivabradine in healthy volunteers.

Ivabradine is a novel bradycardic agent that has been developed for the prevention of angina. Ivabradine has an active metabolite S-18982. The aim of this study is to develop a pharmacokinetic simulation model. Pharmacokinetic data from two studies were pooled and included data from a total of 66 healthy male volunteers. The data were collected following single dose intravenous and multiple dose oral administration of ivabradine. The multiple dose regimens were administered every 12 h and there were seven active dosing levels. The modelling was performed using the NONMEM software. The model was assessed in terms of its ability to describe the original data set used in its construction and also data arising from a different clinical pharmacology study involving 12 additional subjects. The pharmacokinetics of ivabradine and S-18982 were best described by two linked two compartment intravenous bolus and first-order input, with first-pass loss, and first-order output model. When the model was used for simulation it produced an adequate description of both the original data and data arising from a different clinical pharmacology study.