Can we Predict Drug Excretion into Saliva? A Systematic Review and Analysis of Physicochemical Properties.

BACKGROUND AND OBJECTIVES: Saliva is a patient-friendly matrix for therapeutic drug monitoring (TDM) but is infrequently used in routine care. This is due to the uncertainty of saliva-based TDM results to inform dosing. This study aimed to retrieve data on saliva-plasma concentration and subsequently determine the physicochemical properties that influence the excretion of drugs into saliva to increase the foundational knowledge underpinning saliva-based TDM. METHODS: Medline, Web of Science and Embase (1974-2023) were searched for human clinical studies, which determined drug pharmacokinetics in both saliva and plasma. Studies with at least ten subjects and five paired saliva-plasma concentrations per subject were included. For each study, the ratio of the area under the concentration-time curve between saliva and plasma was determined to assess excretion into saliva. Physicochemical properties of each drug (e.g. pKa, lipophilicity, molecular weight, polar surface area, rotatable bonds and fraction of drug unbound to plasma proteins) were obtained from PubChem and Drugbank. Drugs were categorised by their ionisability, after which saliva-to-plasma ratios were predicted with adjustment for protein binding and physiological pH via the Henderson-Hasselbalch equation. Spearman correlation analyses were performed for each drug category to identify factors predicting saliva excretion (α = 5%). Study quality was assessed by the risk of bias in non-randomised studies of interventions tool. RESULTS: Overall, 42 studies including 40 drugs (anti-psychotics, anti-microbials, immunosuppressants, anti-thrombotic, anti-cancer and cardiac drugs) were included. The median saliva-to-plasma ratios were similar for drugs in the amphoteric (0.59), basic (0.43) and acidic (0.41) groups and lowest for drugs in the neutral group (0.21). Higher excretion of acidic drugs (n = 5) into saliva was associated with lower ionisation and protein binding (correlation between predicted versus observed saliva-to-plasma ratios: R2 = 0.85, p = 0.02). For basic drugs (n = 21), pKa predicted saliva excretion (Spearman correlation coefficient: R = 0.53, p = 0.02). For amphoteric drugs (n = 10), hydrogen bond donor (R = - 0.76, p = 0.01) and polar surface area (R = - 0.69, p = 0.02) were predictors. For neutral drugs (n = 10), protein binding (R = 0.84, p = 0.004), lipophilicity (R = - 0.65, p = 0.04) and hydrogen bond donor count (R = - 0.68, p = 0.03) were predictors. Drugs considered potentially suitable for saliva-based TDM are phenytoin, tacrolimus, voriconazole and lamotrigine. The studies had a low-to-moderate risk of bias. CONCLUSIONS: Many commonly used drugs are excreted into saliva, which can be partly predicted by a drug's ionisation state, protein binding, lipophilicity, hydrogen bond donor count and polar surface area. The contribution of drug transporters and physiological factors to the excretion needs to be evaluated. Continued research on drugs potentially suitable for saliva-based TDM will aid in adopting this person-centred TDM approach to improve patient outcomes.

Economic evaluations of therapeutic drug monitoring interventions in acute hospital-based settings: A systematic review.

AIMS: Therapeutic drug monitoring (TDM) aims to optimize drug therapy. As demand on health resources increases, and the technology underpinning TDM becomes more sophisticated, the economic benefits of TDM in hospitals is unclear. The aim of this systematic review was to summarize the economic evidence that could be used to support investment in TDM in hospital settings. In so doing, we sought to provide guidance for future economic evaluations. METHODS: Medline, Embase, CENTRAL, Econlit and NHS Economic Evaluation databases were searched (inception to December 2022) for economic evaluations of hospital-based TDM. Two authors reviewed the studies and extracted data. Overall quality of economic analysis reporting was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. RESULTS: Ten prospective studies (including six randomized studies) and nine retrospective studies were eligible. Overall study reporting was poor, publications meeting a median (range) of 61% (46-82%) of CHEERS checklist criteria. An antimicrobial TDM intervention for adult patients was the focus of most studies (n = 18). Variable clinical outcomes were reported, and length of stay was the primary economic outcome for most studies (n = 13). The majority of studies determined that TDM was economically and clinically favourable (n = 14), four studies reporting a cost-reduction in patient sub-populations. CONCLUSIONS: Significant improvements in both economic and clinical outcomes may be realized with TDM interventions, particularly when targeted to complex patient populations. Attainment of therapeutic target could serve as a feasible surrogate measure of benefit for hospital-based TDM interventions. However, systematic reporting of economic outcomes is needed to inform investment decisions.

Pichia kudriavzevii (Candida krusei): A systematic review to inform the World Health Organisation priority list of fungal pathogens.

In response to the growing global threat of fungal infections, in 2020 the World Health Organisation (WHO) established an Expert Group to identify priority fungi and develop the first WHO fungal priority pathogen list (FPPL). The aim of this systematic review was to evaluate the features and global impact of invasive infections caused by Pichia kudriavzevii (formerly known as Candida krusei). PubMed and Web of Science were used to identify studies published between 1 January 2011 and 18 February 2021 reporting on the criteria of mortality, morbidity (defined as hospitalisation and length of stay), drug resistance, preventability, yearly incidence, and distribution/emergence. Overall, 33 studies were evaluated. Mortality rates of up to 67% in adults were reported. Despite the intrinsic resistance of P. kudriavzevii to fluconazole with decreased susceptibility to amphotericin B, resistance (or non-wild-type rate) to other azoles and echinocandins was low, ranging between 0 and 5%. Risk factors for developing P. kudriavzevii infections included low birth weight, prior use of antibiotics/antifungals, and an underlying diagnosis of gastrointestinal disease or cancer. The incidence of infections caused by P. kudriavzevii is generally low (∼5% of all Candida-like blood isolates) and stable over the 10-year timeframe, although additional surveillance data are needed. Strategies targeting the identified risk factors for developing P. kudriavzevii infections should be developed and tested for effectiveness and feasibility of implementation. Studies presenting data on epidemiology and susceptibility of P. kudriavzevii were scarce, especially in low- and middle-income countries (LMICs). Thus, global surveillance systems are required to monitor the incidence, susceptibility, and morbidity of P. kudriavzevii invasive infections to inform diagnosis and treatment. Timely species-level identification and susceptibility testing should be conducted to reduce the high mortality and limit the spread of P. kudriavzevii in healthcare facilities.

Evaluation of Published Population Pharmacokinetic Models to Inform Tacrolimus Therapy in Adult Lung Transplant Recipients.

BACKGROUND: The applicability of currently available tacrolimus population pharmacokinetic models in guiding dosing for lung transplant recipients is unclear. In this study, the predictive performance of relevant tacrolimus population pharmacokinetic models was evaluated for adult lung transplant recipients. METHODS: Data from 43 lung transplant recipients (1021 tacrolimus concentrations) administered an immediate-release oral formulation of tacrolimus were used to evaluate the predictive performance of 17 published population pharmacokinetic models for tacrolimus. Data were collected from immediately after transplantation up to 90 days after transplantation. Model performance was evaluated using (1) prediction-based assessments (bias and imprecision) of individual predicted tacrolimus concentrations at the fourth dosing based on 1 to 3 previous dosings and (2) simulation-based assessment (prediction-corrected visual predictive check; pcVPC). Both assessments were stratified based on concomitant azole antifungal use. Model performance was clinically acceptable if the bias was within ±20%, imprecision was ≤20%, and the 95% confidence interval of bias crossed zero. RESULTS: In the presence of concomitant antifungal therapy, no model showed acceptable performance in predicting tacrolimus concentrations at the fourth dosing (n = 33), and pcVPC plots displayed poor model fit to the data set. However, this fit slightly improved in the absence of azole antifungal use, where 4 models showed acceptable performance in predicting tacrolimus concentrations at the fourth dosing (n = 33). CONCLUSIONS: Although none of the evaluated models were appropriate in guiding tacrolimus dosing in lung transplant recipients receiving concomitant azole antifungal therapy, 4 of these models displayed potential applicability in guiding dosing in recipients not receiving concomitant azole antifungal therapy. However, further model refinement is required before the widespread implementation of such models in clinical practice.

Therapeutic Drug Monitoring and Biomarkers; towards Better Dosing of Antimicrobial Therapy.

Due to variability in pharmacokinetics and pharmacodynamics, clinical outcomes of antimicrobial drug therapy vary between patients. As such, personalised medication management, considering both pharmacokinetics and pharmacodynamics, is a growing concept of interest in the field of infectious diseases. Therapeutic drug monitoring is used to adjust and individualise drug regimens until predefined pharmacokinetic exposure targets are achieved. Minimum inhibitory concentration (drug susceptibility) is the best available pharmacodynamic parameter but is associated with many limitations. Identification of other pharmacodynamic parameters is necessary. Repurposing diagnostic biomarkers as pharmacodynamic parameters to evaluate treatment response is attractive. When combined with therapeutic drug monitoring, it could facilitate making more informed dosing decisions. We believe the approach has potential and justifies further research.

The experiences and perspectives of people with gout on urate self-monitoring.

INTRODUCTION: Gout management remains suboptimal despite safe and effective urate-lowering therapy. Self-monitoring of urate may improve gout management, however, the acceptability of urate self-monitoring by people with gout is unknown. The aim of this study was to explore the experiences of urate self-monitoring in people with gout. METHODS: Semistructured interviews were conducted with people taking urate-lowering therapy (N = 30) in a 12-month trial of urate self-monitoring in rural and urban Australia. Interviews covered the experience of monitoring and its effect on gout self-management. Deidentified transcripts were analysed thematically. RESULTS: Participants valued the ability to self-monitor and gain more understanding of urate control compared with the annual monitoring ordered by their doctors. Participants indicated that self-monitoring at home was easy, convenient and informed gout self-management behaviours such as dietary modifications, hydration, exercise and medication routines. Many participants self-monitored to understand urate concentration changes in response to feeling a gout flare was imminent or whether their behaviours, for example, alcohol intake, increased the risk of a gout flare. Urate concentrations were shared with doctors mainly when they were above target to seek management support, and this led to allopurinol dose increases in some cases. CONCLUSION: Urate self-monitoring was viewed by people with gout as convenient and useful for independent management of gout. They believed self-monitoring achieved better gout control with a less restricted lifestyle. Urate data was shared with doctors at the patient's discretion and helped inform clinical decisions, such as allopurinol dose changes. Further research on implementing urate self-monitoring in routine care would enable an evaluation of its impact on medication adherence and clinical outcomes, as well as inform gout management guidelines. PATIENT OR PUBLIC CONTRIBUTION: One person with gout, who was not a participant, was involved in the study design by providing feedback and pilot testing the semistructured interview guide. In response to their feedback, subsequent modifications to the interview guide were made to improve the understandability of the questions from a patient perspective. No additional questions were suggested.

Patient-Led Urate Self-Monitoring to Improve Clinical Outcomes in People With Gout: A Feasibility Study.

OBJECTIVE: Self-monitored point-of-care urate-measuring devices are an underexplored strategy to improve adherence to urate-lowering therapy and clinical outcomes in gout. This study observed patient-led urate self-monitoring practice and assessed its influence on allopurinol adherence, urate control, and health-related quality of life. METHODS: People with gout (n = 31) and prescribed allopurinol self-monitored their urate concentrations (HumaSens2.0plus) at baseline and thereafter monthly for 12 months (3 months per quarter). Adherence to allopurinol was measured using medication event monitoring technology (Medication Event Monitoring System cap). Time spent below the target urate concentration (<0.36 mmol/L) was determined. Health-related quality of life was measured using a survey (EuroQoL EQ-5D-5L). Gout flares were recorded. Two-tailed Spearman correlation and the Wilcoxon matched-pairs signed-rank test (P < 0.05) were used for statistical comparisons. RESULTS: Most participants were male (94%) and had urate concentrations below the target (74%) at baseline. Overall, seven participants demonstrated repeated periods of "missed doses" (two or fewer allopurinol doses missed consecutively) and "drug holidays" (three or more missed doses). Most participants (94%) persisted with allopurinol. Time spent within the target urate concentration increased 1.3-fold (from 79% to 100%; P = 0.346), and the incidence of gout flares decreased 1.6-fold (from 8 to 5; P = 0.25) in the final quarter compared to that in the first quarter of the study. Health-related quality of life was reduced for participants reporting at least one gout flare (median utility values 0.9309 vs 0.9563, P = 0.04). CONCLUSION: Patient-led urate self-monitoring may support the maintenance of allopurinol adherence and improve urate control, thus reducing the incidence of gout flares. Further research on patient-led urate self-monitoring in a randomized controlled study is warranted.

Geographic variation in sodium-glucose cotransporter 2 inhibitor and glucagon-like peptide-1 receptor agonist use in people with type 2 diabetes in New South Wales, Australia.

AIM: Sodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1RAs) improve glycaemic control and cardio-renal outcomes for people with type 2 diabetes (T2D). However, geographic and socio-economic variation in use is not well understood. METHODS: We identified 367 829 New South Wales residents aged ≥40 years who dispensed metformin in 2020 as a proxy for T2D. We estimated the prevalence of use of other glucose-lowering medicines among people with T2D and the prevalence of SGLT2i and GLP-1RA use among people using concomitant T2D therapy (i.e. metformin + another glucose-lowering medicine). We measured the prevalence by small-level geography, stratified by age group, and characterized by remoteness and socio-economic status. RESULTS: The prevalence of SGLT2i (29.7%) and GLP-1RA (8.3%) use in people with T2D aged 40-64 increased with geographic remoteness and in areas of greater socio-economic disadvantage, similar to other glucose-lowering medicines. The prevalence of SGLT2i (55.4%) and GLP-1RA (15.4%) among people using concomitant T2D therapy varied across geographic areas, with lower SGLT2i use in more disadvantaged areas and localized areas of high GLP-1RA use (2.5 times the median). Compared with people aged 40-64 years, the prevalence of SGLT2i and GLP-1RA use was lower in older age groups, but with similar patterns of variation across geographic areas. CONCLUSIONS: The prevalence of SGLT2i and GLP-1RA use varied by geography, probably reflecting a combination of system- and prescriber-level factors. Socio-economic variation in GLP-1RA use was overshadowed by localized patterns of prescribing. Continued monitoring of variation can help shape interventions to optimize use among people who would benefit the most.

The impact of peritoneal dialysis on oxypurinol and urate elimination in people with gout.

Gout affects 15%-30% of individuals with advanced kidney disease. Allopurinol which is rapidly and extensively metabolised to an active metabolite, oxypurinol, is the most commonly prescribed urate-lowering therapy. Oxypurinol is almost entirely eliminated by the kidneys (>95%) and has an elimination half-life of 18-30 h in those with normal kidney function. However, oxypurinol pharmacokinetics are poorly understood in individuals with kidney failure on peritoneal dialysis. This study characterised the elimination of oxypurinol and urate in people with gout receiving peritoneal dialysis. Oxypurinol steady-state oral clearance (CL/F), elimination half-life as well as kidney (CLk) and peritoneal (CLpd) clearances for oxypurinol and urate were calculated from the plasma, urine and dialysate concentration data for each individual. Our results demonstrate that oxypurinol and urate are removed by peritoneal dialysis, accounting for more than 50% of oxypurinol and urate clearances. An allopurinol dose about 50%-60% lower than the usual dose used for a patient with normal kidney function will provide adequate urate-lowering therapy.

The development and evaluation of dose-prediction tools for allopurinol therapy (Easy-Allo tools).

AIMS: Dose escalation at the initiation of allopurinol therapy can be protracted and resource intensive. Tools to predict the allopurinol doses required to achieve target serum urate concentrations would facilitate the implementation of more efficient dose-escalation strategies. The aim of this research was to develop and externally evaluate allopurinol dosing tools, one for use when the pre-urate-lowering therapy serum urate is known (Easy-Allo1) and one for when it is not known (Easy-Allo2). METHODS: A revised population pharmacokinetic-pharmacodynamic model was developed using data from 653 people with gout. Maintenance doses to achieve the serum urate target of <0.36 mmol L-1 in >80% of individuals were simulated and evaluated against external data. The predicted and observed allopurinol doses were compared using the mean prediction error (MPE) and root mean square error (RMSE). The proportion of Easy-Allo predicted doses within 100 mg of the observed was quantified. RESULTS: Allopurinol doses were predicted by total body weight, baseline urate, ethnicity and creatinine clearance. Easy-Allo1 produced unbiased and suitably precise dose predictions (MPE 2 mg day-1 95% confidence interval [CI] -13-17, RMSE 91%, 90% within 100 mg of the observed dose). Easy-Allo2 was positively biased by about 70 mg day-1 and slightly less precise (MPE 70 mg day-1 95% CI 52-88, RMSE 131%, 71% within 100 mg of the observed dose). CONCLUSIONS: The Easy-Allo tools provide a guide to the allopurinol maintenance dose requirement to achieve the serum urate target of <0.36 mmol L-1 and will aid in the development of novel dose-escalation strategies for allopurinol therapy.

Bayesian Vancomycin Model Selection for Therapeutic Drug Monitoring in Neonates.

BACKGROUND AND OBJECTIVE: Pharmacokinetic models can inform drug dosing of vancomycin in neonates to optimize therapy. However, the model selected needs to describe the intended population to provide appropriate dose recommendations. Our study aims to identify the population pharmacokinetic (PopPK) model(s) with the best performance to predict vancomycin exposure in neonates in our hospital. METHODS: Relevant published PopPK models for vancomycin in neonates were selected based on demographics and vancomycin dosing strategy. The predictive performance of the models was evaluated in Tucuxi using a local cohort of 69 neonates. Mean absolute error (MAE), relative bias (rBias) and relative root mean square error (rRMSE) were used to quantify the accuracy and precision of the predictive performance of each model for three different approaches: a priori, a posteriori, and Bayesian forecasting for the next course of therapy based on the previous course predictions. A PopPK model was considered clinically acceptable if rBias was between ± 20 and 95% confidence intervals included zero. RESULTS: A total of 25 PopPK models were identified and nine were considered suitable for further evaluation. The model of De Cock et al. 2014 was the only clinically acceptable model based on a priori [MAE 0.35 mg/L, rBias 0.8 % (95% confidence interval (CI) - 7.5, 9.1%), and rRMSE 8.9%], a posteriori [MAE 0.037 mg/L, rBias - 0.23% (95% CI - 1.3, 0.88%), and rRMSE 6.02%] and Bayesian forecasting for the next courses [MAE 0.89 mg/L, rBias 5.45% (95% CI - 8.2, 19.1%), and rRMSE 38.3%) approaches. CONCLUSIONS: The De Cock model was selected based on a comprehensive approach of model selection to individualize vancomycin dosing in our neonates.

A Scoping Review of Pharmacogenomic Educational Interventions to Improve Knowledge and Confidence.

OBJECTIVES: Poor knowledge and confidence in pharmacogenomics are key barriers to implementation. Education of future health care professionals is required to enhance appropriate use of pharmacogenomics; however, the optimal education approach is unclear. This systematic scoping review evaluates pharmacogenomic educational interventions to improve knowledge and confidence. FINDINGS: A total of 24 studies were included. Most (90%) studies delivered pharmacogenomic education to pharmacy students and consisted of didactic lectures and workshops with case studies. To supplement case studies, self or class aggregated (52%, 12 of 23), mock (43%, 10 of 23) or faculty member provided (4%, 1 of 23) pharmacogenomic data were used in the case scenarios. All studies used quantitative methods, including student assessments and scaled surveys to assess the impact of the educational intervention on knowledge and/or confidence in pharmacogenomics. On average, the educational interventions improved knowledge acquisition by 21%, confidence in pharmacogenomic data interpretation by 37%, confidence in communication of pharmacogenomic information to patients by 41% and to health care professionals by 44%. Improvement in communication with other health care professionals was greater in students involved in interprofessional learning compared to self-pharmacogenomic testing. SUMMARY: The measures used to determine the effect of educational interventions on student knowledge and confidence varied. Innovative pedagogy, specifically interactive case-based learning and simulation such as interprofessional learning, enhances the knowledge and confidence of students in pharmacogenomics. Course-embedded self-pharmacogenomic testing may offer a supplementary, interactive component to case-based learning by using real-life reports as the foundation of knowledge and confidence acquisition.

'We are somehow fixated on this being a diabetes drug': a qualitative study exploring the views of cardiologists and nephrologists about sodium-glucose cotransporter 2 inhibitor initiation.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are now indicated for heart failure and chronic kidney disease (CKD), irrespective of the presence of diabetes. Hence, cardiologists and nephrologists have an important role in initiating these drugs. AIMS: To explore cardiologists' and nephrologists' perspectives regarding initiating SGLT2i and their safety monitoring practices when initiating SGLT2i. METHODS: Purposive and snowball approaches were used to recruit participants working in diverse areas in New South Wales, Australia. Semi-structured interviews were conducted with 12 cardiologists and 12 nephrologists. Interviews were conducted until thematic saturation was reached. Emergent themes were identified from transcripts. An iterative general inductive approach was used for data analysis. RESULTS: There was a reluctance amongst most non-heart-failure subspecialist cardiologists to initiate SGLT2i. Reasons included the perception of SGLT2i as diabetes drugs, concern about side effects, lack of experience and issues with follow-up. In contrast, nephrologists reported feeling confident to initiate SGLT2i. Nephrologists varied in their opinions about the severity of CKD at which SGLT2i initiation was reasonable and monitoring of renal function following initiation. Government subsidisation was an important factor in the decision to prescribe SGLT2i to people without diabetes. CONCLUSIONS: Our findings highlight the complex transition from the perception of SGLT2i as diabetes drugs to cardiometabolic and reno-protective agents. Interdisciplinary collaboration may enable greater confidence amongst specialists to initiate SGLT2i, including in patients with CKD. Additionally, there is a need for clear and detailed guidance about SGLT2i prescription in patients with renal dysfunction and renal function monitoring following SGLT2i initiation.

The Influence of a Therapeutic Drug Monitoring Service on Vancomycin-Associated Nephrotoxicity.

Vancomycin's widespread use as the mainstay antibiotic against methicillin-resistant Staphylococcus aureus infections is complicated by its narrow therapeutic index. Therapeutic drug monitoring using area under the concentration-time curve (AUC)-guided dosing is recommended to optimize therapy and prevent vancomycin-associated nephrotoxicity (VAN). In 2018, a consultative therapeutic drug monitoring Advisory Service (the Service) was piloted at an Australian hospital to enable AUC-guided vancomycin dosing. This study sought to compare the incidence of VAN pre- and post-Service implementation. A 4-year retrospective observational study of intravenous vancomycin therapy (greater than 48 hours) in adults (aged 18 years or older), spanning 3 years before and 1-year after implementation of the Service was undertaken. Nephrotoxicity was defined as an increase in serum creatinine concentrations of 26.5 µmol/L or greater or 50% or more from baseline, on 2 or more consecutive days. Univariate analysis was performed to compare patients before and after implementation, and with and without VAN. Independent factors associated with VAN were identified using a multivariate model. In total, 971 courses of vancomycin therapy, administered to 781 patients, were included: 764 courses (603 patients) before implementation and 207 courses (163 patients) after implementation. The incidence of VAN decreased by 5% after Service implementation (15% before implementation vs 10% after implementation; P = .075). Independent factors associated with VAN were sepsis, heart failure, solid-organ transplant, concomitant piperacillin-tazobactam, and average vancomycin AUC during therapy. In conclusion, there was a nonsignificant trend toward a reduced incidence of VAN after the Service. Larger prospective studies are needed to confirm the efficacy of the Service.

Real-Time Monitoring of Antibiotics in the Critically Ill Using Biosensors.

By ensuring optimal dosing, therapeutic drug monitoring (TDM) improves outcomes in critically ill patients by maximizing effectiveness while minimizing toxicity. Current methods for measuring plasma drug concentrations, however, can be challenging, time-consuming, and slow to return an answer, limiting the extent to which TDM is used to optimize drug exposure. A potentially promising solution to this dilemma is provided by biosensors, molecular sensing devices that employ biorecognition elements to recognize and quantify their target molecules rapidly and in a single step. This paper reviews the current state of the art for biosensors regarding their application to TDM of antibiotics in the critically ill, both as ex vivo point-of-care devices supporting single timepoint measurements and in vivo devices supporting continuous real-time monitoring in situ in the body. This paper also discusses the clinical development of biosensors for TDM, including regulatory challenges and the need for standardized performance evaluation. We conclude by arguing that, through precise and real-time monitoring of antibiotics, the application of biosensors in TDM holds great promise for enhancing the optimization of drug exposure in critically ill patients, offering the potential for improved outcomes.

A framework for understanding sources of bias in medication adherence research.

The sources of bias in medication adherence research have not been comprehensively explored. We aimed to identify biases expected to affect adherence research and to develop a framework for mapping these onto the phases of adherence (initiation, implementation and discontinuation). A literature search was conducted, key papers were reviewed and a Catalogue of Bias was consulted. The specific biases related to adherence measurement and metrics were mapped onto the phases of adherence using a tabular matrix. Twenty-three biases were identified, of which 11 were specifically relevant to adherence measures and metrics. The mapping framework showed differences in the numbers and types of biases associated with each measure and metric while highlighting those common to many adherence study designs (e.g., unacceptability bias and apprehension bias). The framework will inform the design of adherence studies and the development of risk of bias tools for adherence research.

Is there a need to optimise pyrazinamide doses in patients with tuberculosis? A systematic review.

Pyrazinamide (PZA) is a first-line antituberculosis drug with potent sterilising activity. Variability in drug exposure may translate into suboptimal treatment responses. This systematic review, conducted according to PRISMA guidelines, aimed to evaluate the concentration-effect relationship. In vitro/in vivo studies had to contain information on the infection model, PZA dose and concentration, and microbiological outcome. Human studies had to present information on PZA dose, measures of drug exposure and maximum concentration, and microbiological response parameter or overall treatment outcome. A total of 34 studies were assessed, including in vitro (n = 2), in vivo (n = 3) and clinical studies (n = 29). Intracellular and extracellular models demonstrated a direct correlation between PZA dose of 15-50 mg/kg/day and reduction in bacterial count between 0.50-27.7 log10 CFU/mL. Consistent with this, higher PZA doses (>150 mg/kg) were associated with a greater reduction in bacterial burden in BALB/c mice models. Human pharmacokinetic studies displayed a linear positive correlation between PZA dose (i.e. 21.4-35.7 mg/kg/day) and drug exposure (AUC range 220.6-514.5 mg·h/L). Additionally, human studies confirmed a dose-effect relationship, with an increased 2-month sputum culture conversion rate at AUC/MIC targets of 8.4-11.3 with higher exposure/susceptibility ratios leading to greater efficacy. A 5-fold variability in AUC was observed at PZA dose of 25 mg/kg. A direct concentration-effect relationship and increased treatment efficacy with higher PZA exposure to susceptibility ratios was observed. Taking into account variability in drug exposure and treatment response, further studies on dose optimisation are justified.

Using seconds-resolved pharmacokinetic datasets to assess pharmacokinetic models encompassing time-varying physiology.

AIM: Pharmacokinetics have historically been assessed using drug concentration data obtained via blood draws and bench-top analysis. The cumbersome nature of these typically constrains studies to at most a dozen concentration measurements per dosing event. This, in turn, limits our statistical power in the detection of hours-scale, time-varying physiological processes. Given the recent advent of in vivo electrochemical aptamer-based (EAB) sensors, however, we can now obtain hundreds of concentration measurements per administration. Our aim in this paper was to assess the ability of these time-dense datasets to describe time-varying pharmacokinetic models with good statistical significance. METHODS: We used seconds-resolved measurements of plasma tobramycin concentrations in rats to statistically compare traditional one- and two-compartmental pharmacokinetic models to new models in which the proportional relationship between a drug's plasma concentration and its elimination rate varies in response to changing kidney function. RESULTS: We found that a modified one-compartment model in which the proportionality between the plasma concentration of tobramycin and its elimination rate falls reciprocally with time either meets or is preferred over the standard two-compartment pharmacokinetic model for half of the datasets characterized. When we reduced the impact of the drug's rapid distribution phase on the model, this one-compartment, time-varying model was statistically preferred over the standard one-compartment model for 80% of our datasets. CONCLUSIONS: Our results highlight both the impact that simple physiological changes (such as varying kidney function) can have on drug pharmacokinetics and the ability of high-time resolution EAB sensor measurements to identify such impacts.