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Nonlinear ordinary differential equations (ODEs) are common in pharmacokinetic–pharmacodynamic systems. Although their exact solutions cannot generally be determined via algebraic methods, their rapid and accurate solutions are desirable. Thus, numerical methods have a critical role. Inductive Linearization was proposed as a method to solve systems of nonlinear ODEs. It is an iterative approach that converts a nonlinear ODE into a linear time-varying (LTV) ODE, for which a range of standard integration techniques can then be used to solve (e.g., eigenvalue decomposition [EVD]). This study explores the properties of Inductive Linearization when coupled with EVD for integration of the LTV ODE and illustrates how the efficiency of the method can be improved. Improvements were based on three approaches, (1) incorporation of a convergence criterion for the iterative linearization process (for simulation and estimation), (2) creating more efficient step sizes for EVD (for simulation and estimation), and (3) updating the initial conditions of the Inductive Linearization (for estimation). The performance of these improvements were evaluated using single subject stochastic simulation-estimation with an application to a simple pharmacokinetic model with Michaelis–Menten elimination. The reference comparison was a standard non-stiff Runge–Kutta method with variable step size (ode45, MATLAB). Each of the approaches improved the speed of the Inductive Linearization technique without diminishing accuracy which, in this simple case, was faster than ode45 with comparable accuracy in the parameter estimates. The methods described here can easily be implemented in standard software programme such as R or MATLAB. Further work is needed to explore this technique for estimation in a population approach setting.

Objectives To determine the therapeutic target of vancomycin in young infants with staphylococcal infections. Methods Retrospective data were collected for infants aged 0 to 90 days with CoNS or MRSA bacteraemia over a 4 year period at the Royal Children’s Hospital Melbourne, Australia. Vancomycin broth microdilution MICs were determined. A published pharmacokinetic model was externally validated using the study dataset and a time-to-event (TTE) pharmacodynamic model developed to link the AUC of vancomycin with the event being the first negative blood culture. Simulations were performed to determine the trough vancomycin concentration that correlates with a 90% PTA of the target AUC24. Results Thirty infants, 28 with CoNS and 2 with MRSA bacteraemia, who had 165 vancomycin concentrations determined were included. The vancomycin broth microdilution MIC was determined for 24 CoNS and 1 MRSA isolate, both with a median MIC of 1 mg/L (CoNS range = 0.5–4.0). An AUC0–24 target of ≥300 mg/L·h or AUC24–48 of ≥424 mg/L·h. increased the chance of bacteriological cure by 7.8- and 7.3-fold, respectively. However, AUC0–24 performed best in the pharmacokinetic-pharmacodynamic model. This correlates with 24 to 48 h trough concentrations of >15–18 mg/L and >10–15 mg/L for 6- and 12-hourly dosing, respectively, and can be used to guide vancomycin therapy in this population. Conclusions An AUC0–24 ≥300 mg/L·h or AUC24–48 ≥424 mg/L·h was associated with an increase in bacteriological cure in young infants with staphylococcal bloodstream infections.

Objective: To evaluate the use of cloud-based virtual patients as a tool for engagement in interprofessional distance education (IPDE). Methods: Five pairs of final-year pharmacy and final-year nursing students interacted with an autonomous, real-time, cloud-based virtual patient (VP). They were debriefed after completion of their case and completed a questionnaire on the relevance of the VP to core IPE competencies. Results: The virtual patient approach was considered to be able to cover 25 of the 39 core IPE competencies. From a thematic analysis, there was evidence of students learning from, with, and about each other. Conclusions: The use of cloud-based autonomous VPs could be a successful tool for IPE.

Overdose with paracetamol modified-release (MR) formulation, a bilayer tablet containing 69% slow-release component, has been increasing since its introduction to the market. However, little evidence exists for the management of MR paracetamol overdose. We aimed to develop a population pharmacokinetic (PK) model for immediate-release (IR) and MR paracetamol and its major metabolism, and quantitatively understand the formulation difference in toxicity assessment based on the nomogram line.Data from a cross-over study design in nine healthy volunteers administered a single supratherapeutic oral dose (80 mg/kg) of either IR and MR paracetamol were available from a published study. Plasma concentrations for paracetamol and its metabolites glucuronide (APAPG) and sulfate conjugate (APAPS) for both formulations were measured and analysed with population pharmacokinetic (PK) method using NONMEM. Toxicity in both formulations was assessed by comparing the simulated paracetamol concentrations under different paracetamol dose levels with the 150 mg/L nomograms. The difference in the assessment was compared between the two formulations.Paracetamol concentrations for the IR formulation were described with a two-compartment model with first-order input and a lag time. The delayed time-course of MR paracetamol concentrations was best captured by a parallel absorption model in which the slow-release component was a serial zero-order then the first-order process. The formation of APAPG was linear, while APAPS concentrations were best fitted by a Michaelis-Menten process. The relative bioavailability of MR paracetamol compared to IR (A joint parent-metabolite model to describe time-course profiles of both IR and MR paracetamol and its metabolites APAPG and APAPS concentrations was developed. Simulations from the model showed that toxicity assessment based on the 150 mg/L nomograms is not suitable in MR paracetamol overdoses.

This research explored the intact nephron hypothesis (INH) as a model for metformin dosing in patients with chronic kidney disease (CKD). The INH assumes that glomerular filtration rate (GFR) will account for all kidney drug handling even for drugs eliminated by tubular secretion like metformin. We conducted two studies: (1) a regression analysis to explore the relationship between metformin clearance and eGFR metrics, and (2) a joint population pharmacokinetic analysis to test the relationship between metformin renal clearance and gentamicin clearance. The relationship between metformin renal clearance and eGFR metrics and gentamicin clearance was found to be linear, suggesting that a proportional dose reduction based on GFR in patients with CKD is reasonable.

Understanding the time course of venom exposure in snakebite patients is important for the optimisation of treatment including antivenom dose and timing. We aimed to investigate the pharmacokinetics of red-bellied black snake (RBBS; Pseudechis porphyriacus) venom in envenomed patients. Timed venom concentration data were obtained from patients with RBBS envenomation recruited to the Australian Snakebite Project (ASP), including demographics and antivenom treatment. Venom concentrations were measured using an enzyme immunoassay. Data were modelled using NONMEM version 7.3. Uncertainty in venom ���dose��� was accounted for by arbitrarily fixing the average amount to 1 mg and incorporating between-subject variability on relative bioavailability. A scale parameter for venom clearance was implemented to account for the rapid venom clearance following antivenom dosing. A sensitivity analysis was performed to determine the magnitude of venom clearance amplification. There were 457 venom concentrations in 114 patients (median age 41, 2���90 y; 80 male). Antivenom was administered to 54 patients a median of 4.2 h post-bite (0.67 to 32 h). A one-compartment model with first-order absorption and elimination provided the best description of the data. The estimated clearance and volume of distribution were 5.21 L/h and 39.9 L, respectively. The calculated elimination half-life of P. porphyriacus venom from the final pharmacokinetic model was 5.35 �� 0.36 h. The variability in the relative dose of injected venom was 140%. Antivenom administration increased venom clearance by 40-fold. Ten patients showed evidence of a double peak in the absorption profile. The information on the exposure time of venom in the body following envenomation will help improve treatment and the timing of antivenom.

Quantitative systems pharmacology models are often highly complex and not amenable to further simulation and/or estimation analyses. Model-order reduction can be used to derive a mechanistically sound yet simpler model of the desired input–output relationship. In this study, we explore the use of artificial neural networks for approximating an input–output relationship within highly dimensional systems models. We illustrate this approach using a model of blood coagulation. The model consists of two components linked together through a highly dimensional discontinuous interface, which creates a difficulty for model reduction techniques. The proposed approach enables the development of an efficient approximation to complex models with the desired level of accuracy. The technique is applicable to a wide variety of models and provides substantial speed boost for use of such models in simulation and control purposes.

Background Globally, pharmacists report to be providing free or partially subsidised patient-focused services in order to meet healthcare needs of their communities. Budget cuts to pharmacy contracts are reported to challenge the provision of such services. Limited information exists identifying the types of unfunded services provided in community pharmacies. Objectives To identify the types of services which pharmacists report to provide that are not reimbursed by the government, insurance companies or paid for by the patient. Methods Semi-structured focus group discussions with pharmacists were conducted stimulating narratives from community pharmacists across New Zealand about the types of unfunded pharmacy services they provide. Discussions were audio recorded and transcribed verbatim. Inductive coding of the data was carried out using QSR International Nvivo 11 for Windows. A semantic thematic analysis was carried out. Results Twenty-four pharmacists took part in the focus groups across five regions in both the North and South Islands of New Zealand. Key themes identified from focus groups were: ‘Standalone unfunded services’, ‘Services funded elsewhere’ and ‘Leakages from the current funding model’. Pharmacists reported that unfunded patient-focused services accounted for 15%–50% of their daily activities. Pharmacists stated that they believed these services often led to reduction of disease progression, hospitalisations and improved quality of life. Pharmacists also stated that given budget cuts, these services are not sustainable. Conclusions Pharmacists report to offer many professional services without remuneration. In some cases, these services make up a substantial part of the pharmacist's time. Further budgetary constraints and increased competition may put these services at risk of being lost. Findings from this study can be applied to unfunded pharmacy services elsewhere, as worldwide pharmacy faces many similar challenges, particularly where there are budget cuts and decreasing revenue in other jurisdictions.

Background Therapeutic decision-making is a core element of pharmacy practice, however, little has been documented about how it is enacted in practice and how it can be theorised. Objective(s) This study aims to contribute to pharmacy education and practice theory by investigating the correspondence between explanations from primary care pharmacists in clinical practice roles about how they make decisions related to medicines therapy and a theoretical model of therapeutic decision-making. Methods In this qualitative study, interview data from 10 pharmacists in primary care settings were analysed using a general inductive approach. The emergent themes were compared to a theoretical model of therapeutic decision-making. Results Eight themes were identified from the explanations of how participants were making therapeutic decisions in practice. The themes were found to correspond to at least one of the four steps of therapeutic decision-making in the model. Themes corresponding to the information gathering step were described most vividly, whereas, the themes corresponding to the reasoning, judgement, and decision steps were less well-articulated. Conclusions These findings suggest that the theoretical model can be useful to interpret empirical data about therapeutic decision-making in practice. These findings might provide a means for pharmacists to adopt language to better describe the steps in their therapeutic decision-making process to others, and especially, their colleagues and patients. Findings can be used by pharmacy educators to design learning opportunities for students about therapeutic decision-making.

There is increasing evidence of pharmacists providing free or partially subsidised patient-focused services in order to meet healthcare needs. Limited information exists about the types of unfunded services and their value.(1) Identify the types of unfunded services provided nationally in New Zealand (NZ) and (2) Determine the costs associated with service provision.A continuous observation time-motion study was conducted across New Zealand to characterise the provision of unfunded pharmacy services and the labour costs associated with their provision. The time-motion study spanned one business day (between seven to eight hours) in each participating pharmacy. The primary investigator (YA) spent one business day in each participating pharmacy (n = 51) and recorded details about the patient-focused services that were provided. Details included the type of service provided, approximate duration of the service and out-of-pocket costs borne by the patient.A total of 660 observations of unfunded services were recorded across the 51 pharmacies where 360 observation hours were carried out. Twenty-three types of unfunded services were identified, where minor ailments accounted for over half of the total observations. Labour costs associated with service provision were variable.Pharmacies across New Zealand are providing patient-focused services for which no funding is being provided.

Background: In vitro-in vivo extrapolation (IVIVE) of hepatic drug clearance (CL) involves the scaling of hepatic intrinsic clearance (CLint,uH) by functional liver size, which is approximated by total liver volume (LV) as per the convention. However, in most overweight and obese patients, LV includes abnormal liver fat, which is not thought to contribute to drug elimination, thus overestimating drug CL. Therefore, lean liver volume (LLV) might be a more appropriate scaler of CLint,uH. Objective: The objective of this work was to assess the application of LLV in CL extrapolation in overweight and obese patients (BMI>25 kg/m2) using a model drug antipyrine. Methods: Recently, a model to predict LLV from patient sex, weight, and height was developed and evaluated. In order to assess the LLV model’s use in IVIVE, a correlation-based analysis was conducted using antipyrine as an example drug. Results: In the overweight group (BMI >25 kg/m2), LLV could describe 36% of the variation in antipyrine CL (R2 = 0.36), which was >2-fold higher than that was explained by LV (R2 = 0.17). In the normal-weight group (BMI ≤25 kg/m2), the coefficients of determination were 58% (R2 = 0.58) and 43% (R2= 0.43) for LLV and LV, respectively. Conclusion: The analysis indicates that LLV is potentially a more appropriate descriptor of functional liver size than LV, particularly in overweight individuals. Therefore, LLV has a potential application in IVIVE of CL in obesity.

Paracetamol-induced hepatotoxicity is the leading cause of acute liver failure in many countries, including North America and the United Kingdom. Among the three dominant paracetamol metabolism pathways (i.e. glucuronidation, sulfation and oxidation), the importance of sulfation is often underestimated because of the general thinking that the sulfation pathway is saturated at therapeutic doses and ultimately accounts for a limited proportion of the fate of a paracetamol dose. We illustrate that insufficient sulfation leads to a shift in biotransformation of paracetamol to toxic oxidation pathways and patients with low sulfate reserves are at higher risk of paracetamol toxicity. Here, we propose that sulfation is of critical importance in understanding the risk of liver toxicity secondary to paracetamol overdose. Serum inorganic sulfate, a measurable substrate on the causal path of paracetamol-induced liver toxicity, should be considered a biomarker for potential toxicity as well as a target for treatment.

Background and purpose Therapeutic decision-making is a critical part of the skill set required by practicing pharmacists. A potentially straightforward way to teach and evaluate decision-making skills is use of real-time simulations. This study aimed to evaluate pharmacy students' perceptions of using a real-time simulation game to treat their own virtual patient. Educational activity and setting Second professional year (Y2) and fourth professional year (Y4) pharmacy students were provided an opportunity to use a virtual patient simulation in their courses. Student perceptions of the game and use of the game for decision-making were evaluated by a questionnaire. The qualitative findings were analysed using an inductive thematic analysis. Findings The questionnaire was completed by 120 Y2 and 115 Y4 students. Four themes arose from the analysis that reflected the students' perceptions of autonomy in their learning and practice, the difficulty in committing to a decision, and having fun while learning. Summary This work provides an initial exploration of the perceptions of pharmacy students about playing a real-time, autonomous, simulation-based game for treating a patient. Future research should focus on more detailed evaluation of this game for learning therapeutic decision-making.

Unfractionated heparin (UFH) dosing and monitoring guidelines for children are often extrapolated from adult data. This practice is suboptimal given the inherent differences in haemostatic maturation and drug handling in children compared with adults. The aim of this work was to investigate the impact of haemostatic system maturation on the dose–response relationship of UFH in children. A quantitative model for haemostasis in adults was adapted to account for maturation in UFH pharmacokinetic (PK) parameters with and without age-related changes in coagulation factor concentrations. The adult and adapted models were used to predict the time courses of anti-factor Xa activity (aXa) and activated partial thromboplastin time (aPTT) in patients receiving UFH infusion. Predictions from both models were compared with observed aXa and aPTT measurements from 31 paediatric patients receiving UFH during extracorporeal membrane oxygenation (ECMO). The model with maturation for both UFH PK and the haemostatic system had an improved aXa and aPTT predictive performance compared with maturation in UFH PK only and the original adult model. Despite the minor effect of haemostatic system maturation on baseline aPTT, it led to substantial changes in the time course of aPTT sensitivity to UFH. This finding suggests that between-subject variability in clotting factors concentrations is potentially a major contributor to the overall variability of aPTT response to UFH. In addition, time-varying clotting factors concentrations may explain within-subject changes in aPTT sensitivity to UFH. We developed the first quantitative systems pharmacology (QSP) model that provides a mechanistic and quantitative basis for linking physiological and pharmacological maturation to UFH effect and response biomarkers. After appropriate clinical validation, the model could be useful for the development of paediatric-specific individualised UFH dosing recommendations.

Cellular response to insults may result in the initiation of different cell death processes. For many cases the cell death process will result in an acute release of cellular material that in some circumstances provides valuable information about the process (i.e. may represent a biomarker). The characteristics of the biomarker release is often informative and plays critical roles in clinical practice and toxicology research. The aim of this study is to develop a general, semi-mechanistic model to describe cell turnover and biomarker release by injured tissue that can be used for estimation in pharmacokinetic and (toxicokinetic)-pharmacodynamic studies. The model included three components: (1) natural tissue turnover, (2) biomarker release from cell death and its movement from the cell through the tissue into the blood, (3) different target insult mechanisms of cell death. We applied the general model to biomarker release profiles for four different cell insult causes. Our model simulations showed good agreements with reported data under both delayed release and rapid release cases. Additionally, we illustrate the use of the model to provide different biomarker profiles. We also provided details on interpreting parameters and their values for other researchers to customize its use. In conclusion, our general model provides a basic structure to study the kinetic behaviour of biomarker release and disposition after cellular insult.

Aims Current pharmacokinetic-pharmacodynamic models describing the haemodynamic changes often do not include necessary feedback mechanisms. These models provide adequate description of current data but may fail to adequately extrapolate to additional scenarios. This study aims to develop a minimal model to describe the short-term changes of haemodynamics that can be used as the basis for model development by future researchers. Methods A minimal haemodynamic model was developed to describe the influence of drugs on blood pressure components. The model structure was defined based on known mechanisms and previously published models. The model was evaluated under 2 different simulation settings. The model parameters were calibrated to describe (without estimation) the haemodynamics of 2 antihypertensive drugs with data extracted from the literature. Structural identifiability analysis was done using various combinations of the observed variable. Results The proposed model structure includes mean arterial pressure, heart rate and stroke volume and is composed of 4 states described by differential equations. Model evaluation showed flexibility in describing the haemodynamics at different target perturbations. Overlay plots of model predictions and literature data showed a good description without data fitting. The structural identifiability analysis revealed all model parameters and initial conditions were identifiable only when heart rate, mean arterial pressure and cardiac output were measured together. Conclusions A minimal model of the haemodynamic system was developed and evaluated. The model accounted for short-term haemodynamic feedback processes. We propose that this model can be used as the basis for future pharmacometric analyses of drugs acting on the haemodynamic system.

AIMS Dose adjustment for drugs eliminated by the kidneys generally assume a linear relationship between renal drug clearance (CLR ) and glomerular filtration rate (GFR). This assumption may not hold for drugs that undergo extensive tubular secretion where nonlinearity in drug handling is expected. The aim of this study is to determine if renal drug study designs recommended by the European Medicines Agency (EMA) and Food and Drug Administration (FDA) could distinguish linear from nonlinear renal drug handling. METHODS In this simulation and estimation study, the study designs based on the EMA and FDA guidelines for Phase I renal drug studies were evaluated for their ability to discriminate a linear from a nonlinear relationship between CLR and GFR. The number of subjects for each simulated study ranged from 4 to 960. Power, relative standard error and bias were calculated. RESULTS Study designs under the EMA and FDA guidelines required ≥8 and ≥48 subjects, respectively, to achieve ≥80% power to discriminate a linear from nonlinear relationship between CLR and GFR. The relative standard error of estimated parameters were 13-37 and 17-44% for the designs with 24 subjects under the EMA and FDA guidelines, respectively. The bias in parameter estimates under the EMA designs were not evident, however, they were biased (13-21%) under the FDA designs. CONCLUSION The EMA design was found to require fewer subjects (n = 8) compared to the FDA (n = 48) to discriminate linear from nonlinear drug renal handling at ≥80% study power while both the designs perform poorly for the parameter precision.

Background Cephalexin is used for the treatment of methicillin-susceptible Staphylococcus aureus (MSSA) infections in children. Although 4 times daily dosing is recommended, less frequent dosing regimens are often prescribed to improve treatment acceptability and adherence. We developed a population pharmacokinetic model of cephalexin in children to determine a twice-daily (BID) and thrice-daily (TID) cephalexin dosing regimen for MSSA infections. Methods A population pharmacokinetic model was developed using a nonlinear mixed effects modeling approach. The dataset used was from a prospective open-label pharmacokinetic study of orally administered cephalexin in 12 children 1-16 years of age with bone and joint infections. Simulations were performed to determine a BID and TID dosing regimen so that ≥90% of children in this age group would achieve the pharmacodynamic target for MSSA (ie, time that the free drug concentration exceeds the minimum inhibitory concentration of the bacteria for at least 40% of the dosing interval). Results The final model was 1 compartment with a transit compartment model to account for delay in oral absorption. For BID dosing, doses of 22-45 and 80 mg/kg were required for MSSA with minimum inhibitory concentrations of 1-2 and 4 mg/L, respectively. For TID dosing, the respective required doses were 15-25 and 45 mg/kg. Conclusions Our study proposes a BID and TID cephalexin dosing regimen that can be prospectively evaluated. Through reducing the dose frequency of this widely prescribed antibiotic, we can reduce the medication burden for children and improve treatment compliance for MSSA infections.

BACKGROUND AND PURPOSE: Biased agonism describes the ability of ligands to differentially regulate multiple signalling pathways when coupled to a single receptor. Signalling is affected by rapid agonist‐induced receptor internalisation. Hence, the conventional use of equilibrium models may not be optimal, because (i) receptor numbers vary with time and, in addition, (ii) some pathways may show non‐monotonic profiles over time. EXPERIMENTAL APPROACH: Data were available from internalisation, cAMP inhibition and phosphorylation of ERK (pERK) of the cannabinoid‐1 (CB(1)) receptor using a concentration series of six CB(1) ligands (CP55,940, WIN55,212‐2, anandamide, 2‐arachidonylglycerol, Δ(9)‐tetrahydrocannabinol and BAY59,3074). The joint kinetic model of CB(1) signalling was developed to simultaneously describe the time‐dependent activities in three signalling pathways. Based on the insights from the kinetic model, fingerprint profiles of CB(1) ligand bias were constructed and visualised. KEY RESULTS: A joint kinetic model was able to capture the signalling profiles across all pathways for the CB(1) receptor simultaneously for a system that was not at equilibrium. WIN55,212‐2 had a similar pattern as 2‐arachidonylglycerol (reference). The other agonists displayed bias towards internalisation compared to cAMP inhibition. However, only Δ(9)‐tetrahydrocannabinol and BAY59,3074 demonstrated bias in the pERK–cAMP pathway comparison. Furthermore, all the agonists exhibited little preference between internalisation and pERK. CONCLUSION AND IMPLICATIONS: This is the first joint kinetic assessment of biased agonism at a GPCR (e.g. CB(1) receptor) under non‐equilibrium conditions. Kinetic modelling is a natural method to handle time‐varying data when traditional equilibria are not present and enables quantification of ligand bias.

Fat-free mass (FFM)-based dose scaling is increasingly being adopted in clinical pharmacology. Given the complexities with the measurement of FFM in clinical practice, choosing an appropriate equation for FFM is critical for accurate dose scaling. Janmahasatian’s FFM model (FFMJan) has largely remained the preferred choice because of its mechanistic basis and good predictive properties. This model was, however, developed from a largely European cohort and has been shown to give biased predictions of FFM in Indian people. The objective of this work was to derive an extended version of the FFMJan model (FFMExt) that accounts for the variation in body composition due to ethnicity, and to demonstrate its application by developing an extended FFM model in an Indian population (FFMExt,Ind). The fundamental assumption of FFMJan model development was a linear relationship between bioimpedance and body mass index. In this extension to Janmahasatian’s work, this assumption was extended to allow for potential non-linear relationships. While the original ZJan model parameters were kept fixed, a set of body composition-related parameters $$\varPsi \{ \psi_{1} , \;\psi_{2} , \;\psi_{3} \}$$ were incorporated, where $$\psi_{1}$$ and $$\psi_{2}$$ were the ethnicity factors to the intercept and the linear coefficient, respectively, and $$\psi_{3}$$ a non-linear exponent. The model was then applied to data arising from a south Indian population and the $$\varPsi$$ parameters were estimated by standard non-linear regression. The data were generated from a reference model for FFM for the Indian population, which was known to provide unbiased estimates for this population. The parameter estimates (%RSE) of the final FFMExt,Ind model were $$\psi_{1} = 0$$ (fixed), $$\psi_{2} = 0.77$$ (3.2%) for male patients, 0.70 (3.3%) for female patients, and $$\psi_{3} = 0.72$$ (12.4%). The final model predictions were in good agreement with the reference model predictions. An FFMExt model has been achieved by extending the original FFMJan model assumptions to account for inter-ethnic differences in body composition. The extended model can be applied to any ethnic population by estimating a set of body composition-related parameters $$\varPsi$$ . This can be performed using bioimpedance data without the need for formal FFM measurements.

We aimed to investigate the frequency of serotonin toxicity following overdose of antidepressants that inhibit serotonin reuptake and the factors that influence the probability of serotonin toxicity occurring. This was a retrospective cohort study of overdoses that included selective serotonin reuptake inhibitors (SSRIs) (70%) and serotonin norepinephrine reuptake inhibitors (SNRIs) (30%) admitted to a tertiary toxicology unit over 23 years. A multivariate mixed effects logistic regression model using NONMEM (7.2.0) was used to determine factors that influenced the probability of serotonin toxicity occurring. There were 1978 overdoses in 1520 patients; median age 33 y (range: 13–86 years) and 64% female. Median defined daily dose equivalent (DDD) was 15 (1–420). Co-ingestants were taken in 1678/1978 (85%) overdoses: 11 co-ingested the monoamine oxidase-A inhibitor (MAOI) moclobemide, 99 (5%) co-ingested olanzapine, 58 (3%) co-ingested risperidone and 417 co-ingested a benzodiazepine (21%). Serotonin toxicity occurred in 269 overdoses (13.6%). The probability of serotonin toxicity increased slightly per 10 DDD units dose [OR, 1.01; 95% confidence intervals (CIs): 0.93–1.10], increased for an SNRI vs. an SSRI [OR, 1.07; 95% CI: 0.99–1.15], and markedly increased with co-ingestion of moclobemide [OR, 33.12; 95% CI: 7.5–147]. The probability decreased per 10 y age [OR, 0.84; 95% CI: 0.74–0.95], and with co-ingestion of the serotonin 2 A receptor (5-HT2A) antagonists olanzapine [OR, 0.40; 95% CI: 0.17–0.94] or risperidone [OR, 0.13; 95% CI: 0.02–0.99]. The probability of serotonin toxicity was 12.5% at 1 DDD (therapeutic), 12.7% at 15 DDDs and 19% at 420 DDDs. In overdoses of the median dose of 15 DDDs, co-ingestion of moclobemide increased the probability to 83%, and co-ingestion of olanzapine or risperidone decreased it to 5.5% and 1.8%, respectively. Serotonin toxicity is common following SSRI/SNRI overdose. Although dose increases probability, this was only a small effect. Co-ingestion with olanzapine or risperidone reduced the risk 2–6-fold, and moclobemide increased the risk 5-fold.

Objectives Cherry concentrate has been suggested to reduce serum urate (SU) and gout flares. The aims of this study were to determine the magnitude of the effect of tart cherry concentrate on SU in people with gout, the most effective dose of tart cherry concentrate for lowering SU, and adverse effects. Methods Fifty people with gout and SU > 0.36 mmol/l were recruited. Half were on allopurinol and half were on no urate-lowering therapy. Participants were randomized to receive tart cherry juice concentrate: placebo, 7.5 ml, 15 ml, 22.5 ml or 30 ml twice daily for 28 days. Blood samples were taken at baseline, then at 1, 3 and 5 h post cherry and then on days 1, 3, 7, 14, 21 and 28. The area under the curve for SU was calculated over the 28-day study period. Results Cherry concentrate dose had no significant effect on reduction in SU area under the curve, urine urate excretion, change in urinary anthocyanin between day 0 and day 28, or frequency of gout flares over the 28-day study period (P = 0.76). There were 24 reported adverse events, with only one (hyperglycaemia) considered possibly to be related to cherry concentrate. Allopurinol use did not modify the effect of cherry on SU or urine urate excretion. Conclusion Tart cherry concentrate had no effect on SU or urine urate excretion. If there is an effect of cherry concentrate on gout flares over a longer time period, it is not likely to be mediated by reduction in SU. Trial registration Australian New Zealand Clinical Trials Registry (ANZCTR), https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=368887, ANZCTR 12615000741583).

Fat-free mass has gained wide acceptance as a scaler of the maintenance dose rate in obese patients. The choice of fat-free mass as a size scaler for the maintenance dose rate is based on its relationship with drug clearance, on the basis that only lean tissue is sufficiently metabolically active to provide capacity for elimination. For xenobiotics, the majority of biotransformation occurs in the liver and hence fat-free mass is implied to scale linearly with the component of liver that is metabolically active. The liver, like the body, can be assumed to comprise two components, lean mass and fat mass. We expect the lean liver mass (or volume) to be the component that most closely relates to drug clearance. The objective of this study was to investigate the relationship of lean liver volume and fat-free mass. Total liver volume and liver fat volume were measured in 100 Indian adults by computed tomography. Lean liver volume was derived as the difference between the two measurements (as liver volume − liver fat volume). Covariate modelling to describe lean liver volume, using NONMEM version 7.3, involved testing the influence of body weight, sex, body surface area and fat-free mass with or without allometric scaling (by estimating the exponent) and the influence of clinical chemistry variables. The final model did not exclude a linear relationship between lean liver volume and fat-free mass, while allometric scaling by body weight0.75 was also supported by the data. While scaling by fat-free mass, the coefficient of proportionality (i.e. lean liver volume per kg fat-free mass) was higher in female (31.25 mL) than male (25.81 mL) subjects. A model to predict lean liver volume from readily available patient data was developed and evaluated. Fat-free mass plus sex was found to be the best body descriptor to scale lean liver volume. The utility of this model in scaling drug clearance and dose requirements of hepatically cleared drugs needs further exploration.

Physiologically based pharmacokinetic (PBPK) models are an important type of systems model used commonly in drug development before commencement of first-in-human studies. Due to structural complexity, these models are not easily utilised for future data-driven population pharmacokinetic (PK) analyses that require simpler models. In the current study we aimed to explore and automate methods of simplifying PBPK models using a proper lumping technique. A linear 17-state PBPK model for fentanyl was identified from the literature. Four methods were developed to search the optimal lumped model, including full enumeration (the reference method), non-adaptive random search (NARS), scree plot plus NARS, and simulated annealing (SA). For exploratory purposes, it was required that the total area under the fentanyl arterial concentration–time curve (AUC) between the lumped and original models differ by 0.002% at maximum. In full enumeration, a 4-state lumped model satisfying the exploratory criterion was found. In NARS, a lumped model with the same number of lumped states was found, requiring a large number of random samples. The scree plot provided a starting lumped model to NARS and the search completed within a short time. In SA, a 4-state lumped model was consistently delivered. In simplify an existing linear fentanyl PBPK model, SA was found to be robust and the most efficient and may be suitable for general application to other larger-scale linear systems. Ultimately, simplified PBPK systems with fundamental mechanisms may be readily used for data-driven PK analyses. Electronic supplementary material The online version of this article (10.1007/s10928-019-09644-5) contains supplementary material, which is available to authorized users.

Clinical decision-making is arguably the most important and underappreciated skill in pharmacy. It can be described as four discrete steps: information gathering, clinical reasoning and judgement and, the decision process. The information gathering and decision negotiation steps and to some extent clinical reasoning are addressed either implicitly or explicitly by practitioners and educators. Clinical judgement, however, remains a largely unexplored concept for clinical decision-making in healthcare therapeutics. It defines how practitioners arrive at a favourable treatment strategy and, due to the often complicated benefit:risk evaluations, is often linked with concepts relating to ambiguity. In this article, we use game theory to explore the judgement stage of clinical decision-making. Game theory allows us to provide a quantitative evaluation of clinical judgement and explore concepts such as ambiguity and its sources in healthcare. Clarifying the elements involved in the judgement stage of clinical decision-making will enable a better understanding of how pharmacists contribute patient care in healthcare teams.

Understanding the time course of venom exposure in snakebite patients is important for the optimisation of treatment including antivenom dose and timing. We aimed to investigate the pharmacokinetics of red-bellied black snake (RBBS;Timed venom concentration data were obtained from patients with RBBS envenomation recruited to the Australian Snakebite Project (ASP), including demographics and antivenom treatment. Venom concentrations were measured using an enzyme immunoassay. Data were modelled using NONMEM version 7.3. Uncertainty in venom "dose" was accounted for by arbitrarily fixing the average amount to 1 mg and incorporating between-subject variability on relative bioavailability. A scale parameter for venom clearance was implemented to account for the rapid venom clearance following antivenom dosing. A sensitivity analysis was performed to determine the magnitude of venom clearance amplification.There were 457 venom concentrations in 114 patients (median age 41, 2-90 y; 80 male). Antivenom was administered to 54 patients a median of 4.2 h post-bite (0.67 to 32 h). A one-compartment model with first-order absorption and elimination provided the best description of the data. The estimated clearance and volume of distribution were 5.21 L/h and 39.9 L, respectively. The calculated elimination half-life ofThe information on the exposure time of venom in the body following envenomation will help improve treatment and the timing of antivenom.

Background Myotoxicity is one of the common clinical manifestations of red-bellied black snake (Pseudechis porphyriacus) envenomation characterised by elevated creatine kinase (CK) concentrations of greater than 1000 U/L. This study aimed to investigate the occurrence of myotoxicity in patients following envenomation. Methods/Principal findings Patient characteristics and serial blood samples (timed venom concentrations and CK concentrations, pre- and post- antivenom) from 114 patients (median age 41, 2-90y; 80 male) were extracted from the Australian Snakebite Project database. Patients were categorised into three groups based on peak CK concentrations [no myotoxicity (10,000 U/L)]. The odds of (mild or severe) myotoxicity was lower in patients that received early antivenom (within 6 hours post-bite) compared to those that received late or no antivenom (odd ratio was 0.186; 95% confidence interval, 0.052–0.664). A population pharmacokinetic-pharmacodynamic (PKPD) model was developed to describe the relationship between the time course of venom (a mixture of toxins) and effect (elevated CK). In addition, a kinetic-pharmacodynamic (KPD) model was developed to describe the relationship between time course of a theoretical toxin and effect. Model development and parameter estimation was performed using NONMEM v7.3. No single set of parameter values from either the PKPD or KPD models were found that could accurately describe the time course of different levels of severity of myotoxicity. The predicted theoretical toxin half-life from the KPD model was 11 ± 3.9 hours compared to the half-life of venom of 5.3 ± 0.36 hours. This indicates that the putative causative toxin’s concentration-time profile does not parallel that of venom. Conclusion Early antivenom administration reduces the incidence of myotoxicity. The venom concentration profile does not appear to be the driver for myotoxicity following envenomation. Additional factors that affect the sensitivity of the patient to snake venom/toxins must be explored to understand the relationship with myotoxicity.

Ivermectin is a broad-spectrum antiparasitic agent used for the treatment and control of neglected tropical diseases. In Australia, ivermectin is primarily used for scabies and is licensed in children aged ≥5 years weighing >15 kg. However, young children, aged 15 kg. Doses of 200 μg/kg rounded to the nearest whole or half 3 mg tablet were given to children with scabies and ivermectin concentrations determined at two time points after dosing. A population pharmacokinetic model was developed using non-linear mixed effects modelling. A separate covariate database of children aged 2 to 4 years and weighing 5 years. The median simulated area under the concentration-time curve was 976 μg∙h/L. Using modelling, we have identified a dosing strategy for ivermectin in children aged 2 to 4 years and weighing less than 15 kg that can be prospectively evaluated for safety and efficacy., Author summary Ivermectin is an important drug for the control and treatment of neglected tropical diseases. However, despite numerous studies showing that ivermectin is safe and well tolerated in young children, it is not currently recommended in young children

Quantitative systems pharmacology (QSP) is a relatively new discipline within modelling and simulation that has gained wide attention over the past few years. The application of QSP models spans drug-target identification and validation, through all drug development phases as well as clinical applications. Due to their detailed mechanistic nature, QSP models are capable of extrapolating knowledge to predict outcomes in scenarios that have not been tested experimentally, making them an important resource in experimental and clinical pharmacology. However, these models are complicated to work with due to their size and inherent complexity. This makes many applications of QSP models for simulation, parameter estimation and trial design computationally intractable. A number of techniques have been developed to simplify QSP models into smaller models that are more amenable to further analyses while retaining their accurate predictive capabilities. Different simplification techniques have different strengths and weaknesses and hence different utilities. Understanding the utilities of different methods is essential for selection of the best method for a particular situation. In this paper, we have created an overall framework for model simplification techniques that allows a natural categorisation of methods based on their utility. We provide a brief description of the concept underpinning the different methods and example applications. A summary of the utilities of methods is intended to provide a guide to modellers in their model endeavours to simplify these complicated models.