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Background: There is a need to examine the impact of increasingly prevalent antibiotic shortages on patient outcomes and on the emergence and spread of antimicrobial resistance (AMR)., Objectives: To: 1) assess patterns and causes of shortages, 2) investigate the effect of shortages on health systems and patient outcomes, and 3) identify strategies for forecasting and managing shortages., Data Sources: PubMed/MEDLINE, EMBASE, Scopus, and Web of Science., Study Eligibility Criteria: Studies published in English during January 2000-July 2023., Participants: Healthcare, policy and strategic teams managing and responding to shortages. Patient populations (adult and children) affected by shortages., Interventions: Strategies, policies, and mitigation options for managing and responding to antibiotic drug shortages., Risk of Bias: Methodological quality of included studies was reviewed using the most appropriate tool from Joanna Briggs Institute critical appraisal tool for each study design., Methods: Data synthesis was qualitative and quantitative using descriptive statistics., Results: The final analysis included 74 studies (61/74, 82.4% high-income countries). Shortages were most reported for piperacillin-tazobactam (21/74, 28.4%) with most of the reported antibiotics being in the WHO Watch category (27/54, 51%). Frequent cause of shortages was disruption in manufacturing including supply of active pharmaceutical ingredient and raw materials. Clinical implications of shortages included increased length of hospital stay, treatment failure after using inferior alternative agents and negative impact on antimicrobial stewardship programmes (AMS). Robust economic impact analysis of shortages is unavailable. Successfully reported mitigation strategies were driven by AMS and infectious diseases teams in hospitals., Conclusions: Antibiotic shortages are directly or indirectly driven by economic viability and reliance on single source ingredients. The limited data on clinical outcomes indicates mixed effect with some infections becoming more difficult to treat, though there is no robust data on the impact of shortages on AMR. The mitigation strategies to manage shortages rely heavily on AMS teams., (Copyright © 2024 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

In the face of increasing antimicrobial tolerance and resistance there is a global obligation to optimise oral antimicrobial dosing strategies including narrow spectrum penicillins, such as penicillin-V. We conducted a randomised, crossover study in healthy volunteers to characterise the influence of probenecid on penicillin-V pharmacokinetics and estimate the pharmacodynamics against Streptococcus pneumoniae. Twenty participants took six doses of penicillin-V (250 mg, 500 mg or 750 mg four times daily) with and without probenecid. Total and free concentrations of penicillin-V and probenecid were measured at two timepoints. A pharmacokinetic model was developed, and the probability of target attainment (PTA) calculated. The mean difference (95% CI) between penicillin-V alone and in combination with probenecid for serum total and free penicillin-V concentrations was significantly different at both timepoints (total: 45 min 4.32 (3.20-5.32) mg/L p < 0.001, 180 min 2.2 (1.58-3.25) mg/L p < 0.001; free: 45 min 1.15 (0.88-1.42) mg/L p < 0.001, 180 min 0.5 (0.35-0.76) mg/L p < 0.001). There was no difference between the timepoints in probenecid concentrations. PTA analysis shows probenecid allows a fourfold increase in MIC cover. Addition of probenecid was safe and well tolerated. The data support further research into improved dosing structures for complex outpatient therapy and might also be used to address penicillin supply shortages., (© 2024. The Author(s).)

Health-care systems, food supply chains, and society in general are threatened by the inexorable rise of antimicrobial resistance. This threat is driven by many factors, one of which is inappropriate antimicrobial treatment. The ability of policy makers and leaders in health care, public health, regulatory agencies, and research and development to deliver frameworks for appropriate, sustainable antimicrobial treatment is hampered by a scarcity of tangible outcome-based measures of the damage it causes. In this Personal View, a mathematically grounded, outcome-based measure of antimicrobial treatment appropriateness, called imprecision, is proposed. We outline a framework for policy makers and health-care leaders to use this metric to deliver more effective antimicrobial stewardship interventions to future patient pathways. This will be achieved using learning antimicrobial systems built on public and practitioner engagement; solid implementation science; advances in artificial intelligence; and changes to regulation, research, and development. The outcomes of this framework would be more ecologically and organisationally sustainable patterns of antimicrobial development, regulation, and prescribing. We discuss practical, ethical, and regulatory considerations involved in the delivery of novel antimicrobial drug development, and policy and patient pathways built on artificial intelligence-augmented measures of antimicrobial treatment imprecision., Competing Interests: Declaration of interests AH declares consulting work for Pfizer outside of the submitted work. BW sits on the board of the York Health Economics Consortium. IB holds a senior investigator award with the National Institute for Health and Care Research and fees via University of Liverpool Consult service as Chief Data Scientist Advisor for AstraZeneca, outside of the submitted work. WH holds or has held research grants with United Kingdom Research and Innovation, EU, F2G, Spero Therapeutics, Antabio, Pfizer, Bugworks, Phico Therapeutics, BioVersys, Global Antibiotic Research & Development Partnership (GARDP), and NAEJA-RGM. WH is or has been a consultant for Appili Therapeutics, F2G, Spero Therapeutics, NAEJA-RGM, Centauri, Pfizer, Phico Therapeutics, Pulmocide, Amplyx, Mundipharma Research, and VenatoRx. WH is a member of the Specialist Advisory Committee for GARDP and the Specialty National co-lead for Infectious Diseases for the National Institute of Health Research. A-GM holds a ZonMW Rubicon Postdoctoral Fellowship Dutch Research Council. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Abstract: Therapeutic drug monitoring (TDM) results for ganciclovir in 12 different treatment episodes showed large intraindividual and interindividual variabilities in the trough concentration and area under the 24-hour concentration-time curve (AUC24). Despite adequate valganciclovir dosing, subtherapeutic concentrations were found in 30% of the treatment episodes. A decrease in viral load was observed regardless of subtherapeutic exposure. These findings show the need for target concentration evaluation and assessment of the applicability of ganciclovir TDM in children., Competing Interests: The authors declare no conflict of interest., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association of Therapeutic Drug Monitoring and Clinical Toxicology.)

Background: Voriconazole is an antifungal drug used for the treatment of invasive fungal infections. Due to highly variable drug exposure, therapeutic drug monitoring (TDM) has been recommended. TDM may be helpful to predict exposure accurately, but covariates, such as severe inflammation, that influence the metabolism of voriconazole have not been included in the population pharmacokinetic (popPK) models suitable for routine TDM., Objectives: To investigate whether the effect of inflammation, reflected by C-reactive protein (CRP), could improve a popPK model that can be applied in clinical care., Patients and Methods: Data from two previous studies were included in the popPK modelling. PopPK modelling was performed using Edsim++. Different popPK models were compared using Akaike Information Criterion and goodness-of-fit plots., Results: In total, 1060 voriconazole serum concentrations from 54 patients were included in this study. The final model was a one-compartment model with non-linear elimination. Only CRP was a significant covariate, and was included in the final model and found to affect the maximum rate of enzyme activity (V max ). For the final popPK model, the mean volume of distribution was 145 L [coefficient of variation percentage (CV%)=61%], mean Michaelis-Menten constant was 5.7 mg/L (CV%=119%), mean V max was 86.4 mg/h (CV%=99%) and mean bioavailability was 0.83 (CV%=143%). Internal validation using bootstrapping resulted in median values close to the population parameter estimates., Conclusions: This one-compartment model with non-linear elimination and CRP as a covariate described the pharmacokinetics of voriconazole adequately., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Gastrointestinal mucositis could potentially compromise drug absorption due to functional loss of mucosa and other pathophysiological changes in the gastrointestinal microenvironment. Little is known about this effect on commonly used anti-infectives. This study aimed to explore the association between different stages of gastrointestinal mucositis, drug exposure, and gut microbiota. A prospective, observational pilot study was performed in HSCT patients aged ≥ 18 years receiving anti-infectives orally. Left-over blood samples and fecal swabs were collected from routine clinical care until 14 days after HSCT to analyze drug and citrulline concentrations and to determine the composition of the gut microbiota. 21 patients with a median age of 58 (interquartile range 54-64) years were included with 252 citrulline, 155 ciprofloxacin, 139 fluconazole, and 76 acyclovir concentrations and 48 fecal swabs obtained. Severe gastrointestinal mucositis was observed in all patients. Due to limited data correlation analysis was not done for valacyclovir and fluconazole, however we did observe a weak correlation between ciprofloxacin and citrulline concentrations. This could suggest that underexposure of ciprofloxacin can occur during severe mucositis. A follow-up study using frequent sampling rather than the use of left-over would be required to investigate the relationship between gastrointestinal mucositis, drug exposure, and gut microbiome., (© 2023. The Author(s).)

Background: Single, high-dose liposomal amphotericin B (LAmB; AmBisome, Gilead Sciences) has demonstrated non-inferiority to amphotericin B deoxycholate in combination with other antifungals for averting all-cause mortality from HIV-associated cryptococcal meningitis. There are limited data on the pharmacokinetics (PK) of AmBisome. The aim of this study was to describe population PK of AmBisome and conduct a meta-analysis of the available studies to suggest the optimal dosing for cryptococcal meningoencephalitis., Methods: Data from a Phase II and Phase III trial of high-dose, short-course AmBisome for cryptococcal meningoencephalitis were combined to develop a population PK model. A search was conducted for trials of AmBisome monotherapy and meta-analysis of clinical outcome data was performed., Results: A two-compartment model with first-order clearance of drug from the central compartment fitted the data best and enabled the extent of inter-individual variability in PK to be quantified. Mean (SD) population PK parameter estimates were: clearance 0.416 (0.363)  L/h; volume of distribution 4.566 (4.518) L; first-order transfer of drug from central to peripheral compartments 2.222 (3.351)  h-1, and from peripheral to central compartment 2.951 (4.070)  h-1. Data for the meta-analysis were insufficient to suggest optimal dosing of AmBisome for cryptococcal meningoencephalitis., Conclusions: This study provides novel insight into the PK of AmBisome at the population level and the variability therein. Our analysis also serves to highlight the paucity of data available on the pharmacodynamics (PD) of AmBisome and underscores the importance of thorough and detailed PK/PD analysis in the development of novel antifungals, by demonstrating the challenges associated with post hoc PK/PD analysis., (© The Author(s) 2022. Published by Oxford University Press on behalf of British Society for Antimicrobial Chemotherapy.)

Background: Acyclovir and valacyclovir are used for the treatment and prophylaxis of infections with herpes simplex virus (HSV) and varicella zoster virus (VZV). The aim of this study is to provide insight into the pharmacodynamics (PD) of (val)acyclovir., Methods: Patients were retrospectively selected, based on therapeutic drug monitoring for acyclovir, to create a population pharmacokinetic (PK) model in Pmetrics. This PK model was used to develop a PK/PD model to study the effect of acyclovir levels on VZV viral load in plasma in immunocompromised patients., Results: Immunocompromised patients with known VZV viral loads in plasma were included for PK/PD modelling ( N = 4, with 23 measure points); they were part of the population of 43 patients used for PK model building. The PK/PD model described the data well (r 2 = 0.83). This is a hopeful first step in clarifying the pharmacodynamics of acyclovir; however, the data in this study are limited., Conclusions: Our preliminary PK/PD model can be used in further research to determine the effect of acyclovir levels on VZV viral load.

Background: Cytomegalovirus (CMV) can cause severe disease, including rejection in transplant recipients. Ganciclovir and its oral prodrug valganciclovir have been used as first-line therapy for CMV disease in transplant recipients. The exposure targets of ganciclovir are not exactly known, and toxicity and resistance have interfered with ganciclovir therapy., Objectives: To evaluate the pharmacokinetics (PK) and pharmacodynamics (PD) of ganciclovir in transplant recipients., Methods: We used patient data from a previous observational study on ganciclovir therapeutic drug monitoring (TDM) in prophylaxis and therapy. The ganciclovir concentrations and CMV viral loads were determined during routine clinical care. The PK/PD population modelling and simulations were done with non-parametric methodology using the Pmetrics program., Results: Eighty-five patients were included in the PK modelling. The final PK model was a two-compartment model with first-order absorption and elimination. A subset of 17 patients on CMV therapy were included in the PD modelling. A median of 4 (range 2-8) viral loads were obtained per patient. A simulation of 10 000 patients showed that an approximately 1 log10 reduction of CMV viral load will be observed after 12.5 days at the current recommended dose., Conclusions: The developed linked PK/PD population model and subsequent PD simulations showed slow decline of CMV viral load and it appears that dosing of (val)ganciclovir in this study might have been inadequate to achieve fast reduction of viral load. It is clear that further studies are needed to specify the PD effects of ganciclovir by performing systematic measurements of both ganciclovir concentrations and CMV viral loads., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.)

Background: Therapeutic drug monitoring (TDM) supports personalized treatment. For successful implementation, TDM must have a turnaround time suited to the clinical needs of patients and their health care settings. Here, the authors share their views of how a TDM strategy can be tailored to specific settings and patient groups., Methods: The authors selected distinct scenarios for TDM: high-risk, complex, and/or critically ill patient population; outpatients; and settings with limited laboratory resources. In addition to the TDM scenario approach, they explored potential issues with the legal framework governing dose escalation., Results: The most important issues identified in the different scenarios are that critically ill patients require rapid turnaround time, outpatients require an easy sampling procedure for the sample matrix and sample collection times, settings with limited laboratory resources necessitate setting-specific analytic techniques, and all scenarios warrant a legal framework to capture the use of escalated dosages, ideally with the use of trackable dosing software., Conclusions: To benefit patients, TDM strategies need to be tailored to the intended population. Strategies can be adapted for rapid turnaround time for critically ill patients, convenient sampling for outpatients, and feasibility for those in settings with limited laboratory resources., Competing Interests: The authors declare no conflict of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Ganciclovir is the mainstay of therapy for the prophylaxis and treatment of Cytomegalovirus. However, therapy with this antiviral agent is hindered by side effects such as myelosuppression, which often leads to therapy cessation. Underdosing, as an attempt to prevent side effects, can lead to drug resistance and therapy failure. Therapeutic drug monitoring (TDM) has been used to overcome these problems. The purpose of this narrative review was to give an overview of ganciclovir TDM, available assays, population pharmacokinetic models, and discuss the current knowledge gaps., Methods: For this narrative review, a nonsystematic literature search was performed on the PubMed database in April 2021. The following search terms were used: ganciclovir, valganciclovir, pharmacokinetics, pharmacodynamics, population pharmacokinetics, therapeutic drug monitoring, bioassay, liquid chromatography coupled with tandem mass spectrometry, liquid chromatography, chromatography, spectrophotometry, and toxicity. In addition, the reference lists of the included articles were screened., Results: The most common bioanalysis method identified was liquid chromatography coupled with tandem mass spectrometry. There are different models presenting ganciclovir IC50; however, establishing a pharmacokinetic/pharmacodynamic target for ganciclovir based on preclinical data is difficult because there are no studies combining dynamic drug exposure in relation to inhibition of viral replication. The data on ganciclovir TDM show large interindividual variability, indicating that TDM may play a role in modifying the dose to reduce toxicity and prevent treatment failure related to low concentrations. The main hurdle for implementing TDM is the lack of robust data to define a therapeutic window., Conclusions: Although the pharmacokinetics (PK) involved is relatively well-described, both the pharmacodynamics (PD) and pharmacokinetic/pharmacodynamic relationship are not. This is because the studies conducted to date have mainly focused on estimating ganciclovir exposure, and owing to the limited therapeutic options for CMV infections, future studies on ganciclovir are warranted., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association of Therapeutic Drug Monitoring and Clinical Toxicology.)

Purpose: Reduced exposure to echinocandins has been reported in specific patient populations, such as critically ill patients; however, fixed dosing strategies are still used. The present review examines the accumulated evidence supporting echinocandin therapeutic drug monitoring (TDM) and summarizes available assays and sampling strategies., Methods: A literature search was conducted using PubMed in December 2020, with search terms such as echinocandins, anidulafungin, caspofungin, micafungin, or rezafungin with pharmacology, pharmacokinetics (PKs), pharmacodynamics (PDs), drug-drug interactions, TDM, resistance, drug susceptibility testing, toxicity, adverse drug reactions, bioanalysis, chromatography, and mass spectrometry. Data on PD/PD (PK/PD) outcome markers, drug resistance, PK variability, drug-drug interactions, assays, and TDM sampling strategies were summarized., Results: Echinocandins demonstrate drug exposure-efficacy relationships, and maximum concentration/minimal inhibitory concentration ratio (Cmax/MIC) and area under the concentration-time curve/MIC ratio (AUC/MIC) are proposed PK/PD markers for clinical response. The relationship between drug exposure and toxicity remains poorly clarified. TDM could be valuable in patients at risk of low drug exposure, such as those with critical illness and/or obesity. TDM of echinocandins may also be useful in patients with moderate liver impairment, drug-drug interactions, hypoalbuminemia, and those undergoing extracorporeal membrane oxygenation, as these conditions are associated with altered exposure to caspofungin and/or micafungin. Assays are available to measure anidulafungin, micafungin, and caspofungin concentrations. A limited-sampling strategy for anidulafungin has been reported., Conclusions: Echinocandin TDM should be considered in patients at known risk of suboptimal drug exposure. However, for implementing TDM, clinical validation of PK/PD targets is needed., Competing Interests: The authors declare no conflict of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Introduction: Osteophytes are a prominent feature of osteoarthritis (OA) joints and one of the clinical hallmarks of the disease progression. Research on osteophytes is fragmentary and modes of its contribution to OA pathology are obscure., Aim: To elucidate the role of osteophytes in OA pathology from a perspective of molecular and cellular events., Methods: RNA-seq of fully grown osteophytes, collected from tibial plateau of six OA patients revealed patterns corresponding to active extracellular matrix re-modulation and prominent participation of mast cells. Presence of mast cells was further confirmed by immunohistochemistry, performed on the sections of the osteophytes using anti-tryptase alpha/beta-1 and anti-FC epsilon RI antibodies and the related key up-regulated genes were validated by qRT-PCR. To test the role of OA synovial fluid (SF) in mast cell maturation as proposed by the authors, hematopoietic stem cells (HSCs) and ThP1 cells were cultured in a media supplemented with 10% SF samples, obtained from various grades of OA patients and were monitored using specific cell surface markers by flow cytometry. Proteomics analysis of SF samples was performed to detect additional markers specific to mast cells and inflammation that drive the cell differentiation and maturation., Results: Transcriptomics of osteophytes revealed a significant upregulation of mast cells specific genes such as chymase 1 (CMA1; 5-fold) carboxypeptidase A3 (CPA3; 4-fold), MS4A2/FCERI (FCERI; 4.2-fold) and interleukin 1 receptor-like 1 (IL1RL1; 2.5-fold) indicating their prominent involvement. (In IHC, anti-tryptase alpha/beta-1 and anti- FC epsilon RI-stained active mast cells were seen populated in cartilage, subchondral bone, and trabecular bone.) Based on these outcomes and previous learnings, the authors claim a possibility of mast cells invasion into osteophytes is mediated by SF and present in vitro cell differentiation assay results, wherein ThP1 and HSCs showed differentiation into HLA-DR+/CD206+ and FCERI+ phenotype, respectively, after exposing them to medium containing 10% SF for 9 days. Proteomics analysis of these SF samples showed an accumulation of mast cell-specific inflammatory proteins., Conclusions: RNA-seq analysis followed by IHC study on osteophyte samples showed a population of mast cells resident in them and may further accentuate inflammatory pathology of OA. Besides subchondral bone, the authors propose an alternative passage of mast cells invasion in osteophytes, wherein OA SF was found to be necessary and sufficient for maturation of mast cell precursor into effector cells.

Nitric oxide is a gas produced in the airways of asthmatic subjects and related to T2 inflammation. It can be measured as fractional nitric oxide (FeNO) in the exhaled air and used as a non-invasive, easy to evaluate, rapid marker. It is now widely used in many settings to determine airway inflammation. The aim of this narrative review is to report relationship between FeNO and the physiopathologic characteristics of asthmatic patients. Factors affecting FeNO levels have also been analysed as well as the impact of corticosteroid, target therapies and rehabilitation programs. Considering the availability of the test, spreading this methodology to low income countries has also been considered as a possibility for evaluating airway inflammation and monitoring adherence to inhaled corticosteroid therapy. PubMed data search has been performed restricted to English language papers. Research was limited to studies in adults unless studies in children were the only ones reported for a particular issue. This revision could be useful to summarize the role of FeNO in relation to asthma characteristics and help in the use of FeNO in different clinical settings particularly in low income countries., (Copyright © 2020 Sociedade Portuguesa de Pneumologia. Published by Elsevier España, S.L.U. All rights reserved.)

Invasive fungal infections (IFI) are a common infection-related cause of death in immunocompromised patients. Approximately 10 million people are at risk of developing invasive aspergillosis annually. Detailed study of the pharmacokinetics (PK) and pharmacodynamics (PD) of antifungal drugs has resulted in a better understanding of optimal regimens for populations, drug exposure targets for therapeutic drug monitoring, and establishing in vitro susceptibility breakpoints. Importantly, however, each is an example of a "one size fits all strategy", where complex systems are reduced to a singularity that ensures antifungal therapy is administered safely and effectively at the level of a population. Clearly, such a notion serves most patients adequately but is completely counter to the covenant at the centre of the clinician-patient relationship, where each patient should know whether they are well-positioned to maximally benefit from an antifungal drug. This review discusses the current therapy of fungal infections and areas of future research to maximise the effectiveness of antifungal therapy at an individual level.

Antimicrobial prophylaxis is increasingly being used in patients with hematological malignancies receiving high-dose chemotherapy and hematopoietic stem cell transplantation (HSCT). However, few studies have focused on the potential impact of gastrointestinal mucositis (GI-M), a frequently observed side effect of chemotherapy in patients with cancer that affects the gastrointestinal microenvironment, on drug absorption. In this review, we discuss how chemotherapy leads to an overall loss of mucosal surface area and consequently to uncontrolled transport across the barrier. The barrier function is depending on intestinal luminal pH, intestinal motility, and diet. Another factor contributing to drug absorption is the gut microbiota, as it modulates the bioavailability of orally administrated drugs by altering the gastrointestinal properties. To better understand the complex interplay of factors in GI-M and drug absorption we suggest: (i) the longitudinal characterization of the impact of GI-M severity on drug exposure in patients, (ii) the development of tools to predict drug absorption, and (iii) strategies that allow the support of the gut microbiota. These studies will provide relevant data to better design strategies to reduce the severity and impact of GI-M in patients with cancer.

Background: The use of (val)ganciclovir is complicated by toxicity, slow response to treatment and acquired resistance., Objectives: To evaluate a routine therapeutic drug monitoring (TDM) programme for ganciclovir in a transplant patient population., Methods: An observational study was performed in transplant recipients from June 2018 to February 2020. Dose adjustments were advised by the TDM pharmacist as part of clinical care. For prophylaxis, a trough concentration (Cmin) of 1-2 mg/L and an AUC24h of >50 mg·h/L were aimed for. For treatment, a Cmin of 2-4 mg/L and an AUC24h of 80-120 mg·h/L were aimed for., Results: Ninety-five solid organ and stem cell transplant patients were enrolled. Overall, 450 serum concentrations were measured; with a median of 3 (IQR = 2-6) per patient. The median Cmin and AUC24h in the treatment and prophylaxis groups were 2.0 mg/L and 90 mg·h/L and 0.9 mg/L and 67 mg·h/L, respectively. Significant intra- and inter-patient patient variability was observed. The majority of patients with an estimated glomerular filtration rate of more than 120 mL/min/1.73 m2 and patients on continuous veno-venous haemofiltration showed underexposure. The highest Cmin and AUC24h values were associated with the increase in liver function markers and decline in WBC count as compared with baseline., Conclusions: This study revealed that a standard weight and kidney function-based dosing regimen resulted in highly variable ganciclovir Cmin and under- and over-exposure were observed in patients on dialysis and in patients with increased renal function. Clearly there is a need to explore the impact of concentration-guided dose adjustments in a prospective study., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.)

Nontuberculous mycobacteria can cause minimally symptomatic self-limiting infections to progressive and life-threatening disease of multiple organs. Several factors such as increased testing and prevalence have made this an emerging infectious disease. Multiple guidelines have been published to guide therapy, which remains difficult owing to the complexity of therapy, the potential for acquired resistance, the toxicity of treatment, and a high treatment failure rate. Given the long duration of therapy, complex multi-drug treatment regimens, and the risk of drug toxicity, therapeutic drug monitoring is an excellent method to optimize treatment. However, currently, there is little available guidance on therapeutic drug monitoring for this condition. The aim of this review is to provide information on the pharmacokinetic/pharmacodynamic targets for individual drugs used in the treatment of nontuberculous mycobacteria disease. Lacking data from randomized controlled trials, in vitro, in vivo, and clinical data were aggregated to facilitate recommendations for therapeutic drug monitoring to improve efficacy and reduce toxicity.

Tuberculosis (TB) is still the number one cause of death due to an infectious disease. Pharmacokinetics and pharmacodynamics of anti-TB drugs are key in the optimization of TB treatment and help to prevent slow response to treatment, acquired drug resistance, and adverse drug effects. The aim of this review was to provide an update on the pharmacokinetics and pharmacodynamics of anti-TB drugs and to show how population pharmacokinetics and Bayesian dose adjustment can be used to optimize treatment. We cover aspects on preclinical, clinical, and population pharmacokinetics of different drugs used for drug-susceptible TB and multidrug-resistant TB. Moreover, we include available data to support therapeutic drug monitoring of these drugs and known pharmacokinetic and pharmacodynamic targets that can be used for optimization of therapy. We have identified a wide range of population pharmacokinetic models for first- and second-line drugs used for TB, which included models built on NONMEM, Pmetrics, ADAPT, MWPharm, Monolix, Phoenix, and NPEM2 software. The first population models were built for isoniazid and rifampicin; however, in recent years, more data have emerged for both new anti-TB drugs, but also for defining targets of older anti-TB drugs. Since the introduction of therapeutic drug monitoring for TB over 3 decades ago, further development of therapeutic drug monitoring in TB next steps will again depend on academic and clinical initiatives. We recommend close collaboration between researchers and the World Health Organization to provide important guideline updates regarding therapeutic drug monitoring and pharmacokinetics/pharmacodynamics.

Therapeutic drug monitoring (TDM) and model-informed precision dosing (MIPD) have evolved as important tools to inform rational dosing of antibiotics in individual patients with infections. In particular, critically ill patients display altered, highly variable pharmacokinetics and often suffer from infections caused by less susceptible bacteria. Consequently, TDM has been used to individualize dosing in this patient group for many years. More recently, there has been increasing research on the use of MIPD software to streamline the TDM process, which can increase the flexibility and precision of dose individualization but also requires adequate model validation and re-evaluation of existing workflows. In parallel, new minimally invasive and noninvasive technologies such as microneedle-based sensors are being developed, which-together with MIPD software-have the potential to revolutionize how patients are dosed with antibiotics. Nonetheless, carefully designed clinical trials to evaluate the benefit of TDM and MIPD approaches are still sparse, but are critically needed to justify the implementation of TDM and MIPD in clinical practice. The present review summarizes the clinical pharmacology of antibiotics, conventional TDM and MIPD approaches, and evidence of the value of TDM/MIPD for aminoglycosides, beta-lactams, glycopeptides, and linezolid, for which precision dosing approaches have been recommended., (© 2021 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Introduction: Therapeutic drug monitoring (TDM) has been recommended for treatment optimization in tuberculosis (TB) but is only is used in certain countries e.g. USA, Germany, the Netherlands, Sweden and Tanzania. Recently, new drugs have emerged and PK studies in TB are continuing, which contributes further evidence for TDM in TB. The aim of this review is to provide an update on drugs used in TB, treatment strategies for these drugs, and TDM to support broader implementation., Areas Covered: This review describes the different drug classes used for TB, multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB), along with their pharmacokinetics, dosing strategies, TDM and sampling strategies. Moreover, the review discusses TDM for patient TB and renal or liver impairment, patients co-infected with HIV or hepatitis, and special patient populations - children and pregnant women., Expert Opinion: TB treatment has a long history of using 'one size fits all.' This has contributed to treatment failures, treatment relapses, and the selection of drug-resistant isolates. While challenging in resource-limited circumstances, TDM offers the clinician the opportunity to individualize and optimize treatment early in treatment. This approach may help to refine treatment and thereby reduce adverse effects and poor treatment outcomes. Funding, training, and randomized controlled trials are needed to advance the use of TDM for patients with TB.

Coronavirus disease 2019 (COVID-19) is a rapidly evolving, highly transmissible, and potentially lethal pandemic caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of June 11 2020, more than 7,000,000 COVID-19 cases have been reported worldwide, and more than 400,000 patients have died, affecting at least 188 countries. While literature on the disease is rapidly accumulating, an integrated, multinational perspective on clinical manifestations, immunological effects, diagnosis, prevention, and treatment of COVID-19 can be of global benefit. We aimed to synthesize the most relevant literature and experiences in different parts of the world through our global consortium of experts to provide a consensus-based document at this early stage of the pandemic., (Copyright © 2020 Abu-Raya, Migliori, O'Ryan, Edwards, Torres, Alffenaar, Märtson, Centis, D'Ambrosio, Flanagan, Hung, Lauretani, Leung, Leuridan, Maertens, Maggio, Nadel, Hens, Niesters, Osterhaus, Pontali, Principi, Rossato Silva, Omer, Spanevello, Sverzellati, Tan, Torres-Torreti, Visca and Esposito.)

Major epidemics, including some that qualify as pandemics, such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), HIV, influenza A (H1N1)pdm/09 and most recently COVID-19, affect the lung. Tuberculosis (TB) remains the top infectious disease killer, but apart from syndemic TB/HIV little is known regarding the interaction of viral epidemics and pandemics with TB. The aim of this consensus-based document is to describe the effects of viral infections resulting in epidemics and pandemics that affect the lung (MERS, SARS, HIV, influenza A (H1N1)pdm/09 and COVID-19) and their interactions with TB. A search of the scientific literature was performed. A writing committee of international experts including the European Centre for Disease Prevention and Control Public Health Emergency (ECDC PHE) team, the World Association for Infectious Diseases and Immunological Disorders (WAidid), the Global Tuberculosis Network (GTN), and members of the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group for Mycobacterial Infections (ESGMYC) was established. Consensus was achieved after multiple rounds of revisions between the writing committee and a larger expert group. A Delphi process involving the core group of authors (excluding the ECDC PHE team) identified the areas requiring review/consensus, followed by a second round to refine the definitive consensus elements. The epidemiology and immunology of these viral infections and their interactions with TB are discussed with implications for diagnosis, treatment and prevention of airborne infections (infection control, viral containment and workplace safety). This consensus document represents a rapid and comprehensive summary on what is known on the topic., Competing Interests: Conflict of interest: G.B. Migliori has nothing to disclose. Conflict of interest: M. Raviglione has nothing to disclose. Conflict of interest: G. MacGregor-Skinner has nothing to disclose. Conflict of interest: G. Sotgiu has nothing to disclose. Conflict of interest: J-W. Alffenaar has nothing to disclose. Conflict of interest: S. Tiberi has nothing to disclose. Conflict of interest: C. Adlhoch has nothing to disclose. Conflict of interest: T. Alonzi has nothing to disclose. Conflict of interest: S. Archuleta has nothing to disclose. Conflict of interest: S. Brusin has nothing to disclose. Conflict of interest: E. Cambau has nothing to disclose. Conflict of interest: M.R. Capobianchi has nothing to disclose. Conflict of interest: C. Castilletti has nothing to disclose. Conflict of interest: R. Centis has nothing to disclose. Conflict of interest: D.M. Cirillo has nothing to disclose. Conflict of interest: L. D'Ambrosio has nothing to disclose. Conflict of interest: G. Delogu has nothing to disclose. Conflict of interest: S.M.R. Esposito has nothing to disclose. Conflict of interest: J. Figueroa has nothing to disclose. Conflict of interest: J.S. Friedland has nothing to disclose. Conflict of interest: B.C.H. Ho has nothing to disclose. Conflict of interest: G. Ippolito has nothing to disclose. Conflict of interest: M. Jankovic has nothing to disclose. Conflict of interest: H.Y. Kim has nothing to disclose. Conflict of interest: S. Rosales Klintz has nothing to disclose. Conflict of interest: C. Ködmön has nothing to disclose. Conflict of interest: E. Lalle has nothing to disclose. Conflict of interest: Y.S. Leo has nothing to disclose. Conflict of interest: C-C. Leung has nothing to disclose. Conflict of interest: A-G. Märtson has nothing to disclose. Conflict of interest: M.G. Melazzini has nothing to disclose. Conflict of interest: S. Najafi Fard has nothing to disclose. Conflict of interest: P. Penttinen has nothing to disclose. Conflict of interest: L. Petrone has nothing to disclose. Conflict of interest: E. Petruccioli has nothing to disclose. Conflict of interest: E. Pontali has nothing to disclose. Conflict of interest: L. Saderi has nothing to disclose. Conflict of interest: M. Santin has nothing to disclose. Conflict of interest: A. Spanevello has nothing to disclose. Conflict of interest: R. van Crevel has nothing to disclose. Conflict of interest: M.J. van der Werf has nothing to disclose. Conflict of interest: D. Visca has nothing to disclose. Conflict of interest: M. Viveiros has nothing to disclose. Conflict of interest: J-P. Zellweger has nothing to disclose. Conflict of interest: A. Zumla has nothing to disclose. Conflict of interest: D. Goletti has nothing to disclose. Conflict of interest: C.W.M. Ong has nothing to disclose., (Copyright ©ERS 2020.)

Ethionamide (ETA), an isonicotinic acid derivative, is part of the multidrug-resistant tuberculosis (MDR-TB) regimen. The current guidelines have deprioritized ETA because it is potentially less effective than other agents. Our aim was to develop a population pharmacokinetic (PK) model and simulate ETA dosing regimens in order to assess target attainment. This study included subjects from four different sites, including healthy volunteers and patients with MDR-TB. The TB centers included were two in the United States and one in Bangladesh. Patients who received ETA and had at least one drug concentration reported were included. The population PK model was developed, regimens with a total of 1,000 to 2,250 mg daily were simulated, and target attainment using published MICs and targets of 1.0-log kill and resistance suppression was assessed with the Pmetrics R package. We included 1,167 ethionamide concentrations from 94 subjects. The final population model was a one-compartment model with first-order elimination and absorption with a lag time. The mean (standard deviation [SD]) final population parameter estimates were as follows: absorption rate constant, 1.02 (1.11) h -1 ; elimination rate constant, 0.69 (0.46) h -1 ; volume of distribution, 104.16 (59.87) liters; lag time, 0.43 (0.32) h. A total daily dose of 1,500 mg or more was needed for ≥90% attainment of the 1.0-log kill target at a MIC of 1 mg/liter, and 2,250 mg/day led to 80% attainment of the resistance suppression target at a MIC of 0.5 mg/liter. In conclusion, we developed a population PK model and assessed target attainment for different ETA regimens. Patients may not be able to tolerate the doses needed to achieve the predefined targets supporting the current recommendations for ETA deprioritization., (Copyright © 2020 American Society for Microbiology.)

The objective of this study was to develop a population pharmacokinetic model and to determine a dosing regimen for caspofungin in critically ill patients. Nine blood samples were drawn per dosing occasion. Fifteen patients with (suspected) invasive candidiasis had one dosing occasion and five had two dosing occasions, measured on day 3 (±1) of treatment. Pmetrics was used for population pharmacokinetic modeling and probability of target attainment (PTA). A target 24-h area under the concentration-time curve (AUC) value of 98 mg·h/liter was used as an efficacy parameter. Secondarily, the AUC/MIC targets of 450, 865, and 1,185 were used to calculate PTAs for Candida glabrata , C. albicans , and C. parapsilosis , respectively. The final 2-compartment model included weight as a covariate on volume of distribution ( V ). The mean V of the central compartment was 7.71 (standard deviation [SD], 2.70) liters/kg of body weight, the mean elimination constant ( K e ) was 0.09 (SD, 0.04) h -1 , the rate constant for the caspofungin distribution from the central to the peripheral compartment was 0.44 (SD, 0.39) h -1 , and the rate constant for the caspofungin distribution from the peripheral to the central compartment was 0.46 (SD, 0.35) h -1 A loading dose of 2 mg/kg on the first day, followed by 1.25 mg/kg as a maintenance dose, was chosen. With this dose, 98% of the patients were expected to reach the AUC target on the first day and 100% of the patients on the third day. The registered caspofungin dose might not be suitable for critically ill patients who were all overweight (≥120 kg), over 80% of median weight (78 kg), and around 25% of lower weight (≤50 kg). A weight-based dose regimen might be appropriate for achieving adequate exposure of caspofungin in intensive care unit patients., (Copyright © 2020 Märtson et al.)

Precision dosing for many antifungal drugs is now recommended. Saliva sampling is considered as a non-invasive alternative to plasma sampling for therapeutic drug monitoring (TDM). However, there are currently no clinically validated saliva models available. The aim of this study is firstly, to conduct a systematic review to evaluate the evidence supporting saliva-based TDM for azoles, echinocandins, amphotericin B, and flucytosine. The second aim is to develop a saliva population pharmacokinetic (PK) model for eligible drugs, based on the evidence. Databases were searched up to July 2019 on PubMed ® and Embase ® , and 14 studies were included in the systematic review for fluconazole, voriconazole, itraconazole, and ketoconazole. No studies were identified for isavuconazole, posaconazole, flucytosine, amphotericin B, caspofungin, micafungin, or anidulafungin. Fluconazole and voriconazole demonstrated a good saliva penetration with an average S/P ratio of 1.21 (± 0.31) for fluconazole and 0.56 (± 0.18) for voriconazole, both with strong correlation (r = 0.89-0.98). Based on the evidence for TDM and available data, population PK analysis was performed on voriconazole using Nonlinear Mixed Effects Modeling (NONMEM 7.4). 137 voriconazole plasma and saliva concentrations from 11 patients (10 adults, 1 child) were obtained from the authors of the included study. Voriconazole pharmacokinetics was best described by one-compartment PK model with first-order absorption, parameterized by clearance of 4.56 L/h (36.9% CV), volume of distribution of 60.7 L, absorption rate constant of 0.858 (fixed), and bioavailability of 0.849. Kinetics of the voriconazole distribution from plasma to saliva was identical to the plasma kinetics, but the extent of distribution was lower, modeled by a scale factor of 0.5 (4% CV). A proportional error model best accounted for the residual variability. The visual and simulation-based model diagnostics confirmed a good predictive performance of the saliva model. The developed saliva model provides a promising framework to facilitate saliva-based precision dosing of voriconazole., (Copyright © 2020 Kim, Märtson, Dreesen, Spriet, Wicha, McLachlan and Alffenaar.)

Objectives: Infections remain a threat for solid organ and stem cell transplant recipients. Antimicrobial prophylaxis and pre-emptive therapy have improved survival of these patients; however, the failure rates of prophylaxis are not negligible. The aim of this systematic review is to explore the reasons behind failure of antimicrobial prophylaxis and pre-emptive therapy., Setting: This systematic review included prospective randomised controlled trials and prospective single-arm studies., Participants: The studies included were on prophylaxis and pre-emptive therapy of opportunistic infections in transplant recipients. Studies were included from databases MEDLINE, CENTRAL and Embase published until October first 2018., Primary and Secondary Outcome Measures: Primary outcome measures were breakthrough infections, adverse events leading to stopping of treatment, switching medication or dose reduction. Secondary outcome measures were acquired resistance to antimicrobials, antifungals or antivirals and death., Results: From 3317 identified records, 30 records from 24 studies with 2851 patients were included in the systematic review. Seventeen focused on prophylactic and pre-emptive treatment of cytomegalovirus and seven studies on invasive fungal infection. The main reasons for failure of prophylaxis and pre-emptive therapy were adverse events and breakthrough infections, which were described in 54% (13 studies) and 38% (9 studies) of the included studies, respectively. In 25%, six of the studies, a detailed description of patients who experienced failure of prophylaxis or pre-emptive therapy was unclear or lacking., Conclusions: Our results show that although failure is reported in the studies, the level of detail prohibits a detailed analysis of failure of prophylaxis and pre-emptive therapy. Clearly reporting on patients with a negative outcome should be improved. We have provided guidance on how to detect failure early in a clinical setting in accordance to the results from this systematic review., Prospero Registration Number: CRD42017077606., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Posaconazole is indicated for prophylaxis and treatment of invasive aspergillosis. Therapeutic drug monitoring (TDM) of posaconazole is used to optimise drug exposure. The aim of this study was to analyse and describe the TDM practices and exposure of posaconazole tablets. Patients who received posaconazole for treatment or prophylaxis of fungal infections were included in the study. The following therapeutic window was defined: if concentration was low (<0.7 mg/L for prophylaxis or < 1.5 mg/L for treatment) or high (>3.75 mg/L), the hospital pharmacist provided the physician with dosage advice, which implementation to patient care was analysed. A longitudinal analysis was performed to analyse if different confounding variables had an effect on posaconazole concentrations. Forty-seven patients were enrolled resulting in 217 posaconazole trough concentrations. A median of 3 (IQR 1-7) samples was measured per patient. The median concentration was 1.7 mg/L (IQR 0.8-2.7) for prophylaxis and 1.76 mg/L (IQR 1.3-2.3) for treatment. Overall, 78 posaconazole concentrations were out of the therapeutic window. For 45 (54%) of these concentrations, a dosage change was recommended. In the longitudinal analysis, the laboratory markers and patient baseline variables did not have an effect on posaconazole concentrations. Adequate posaconazole exposure was shown in 64% (affected 28 patients) of the measured concentrations. TDM practice of posaconazole can be improved by increasing the implementation rate of dose recommendation by a multidisciplinary antifungal stewardship team., (© 2019 The Authors. Mycoses published by Blackwell Verlag GmbH.)

This article presents 3 cases of immunocompromised patients for whom therapeutic drug monitoring of ganciclovir in combination with cytomegalovirus viral load measurement was used to guide treatment. The first patient is diagnosed with thymoma A, the second is a heart transplant recipient, and the third is an HIV-positive patient. These patients were all diagnosed with cytomegalovirus and treated with ganciclovir. Our case studies illustrate how therapeutic drug monitoring-guided dosing can be helpful in the management of these complex cases.

During inflammation, several cytochrome P450 enzymes are downregulated. Recently it was shown that voriconazole metabolism is reduced during inflammation. Posaconazole, another triazole with broad-spectrum antifungal activity, is metabolised only to a limited extent by cytochrome P450 enzymes and to a wider extent by phase 2 enzyme systems. The aim of this study was to investigate posaconazole concentrations during inflammation. Patients aged ≥18 years receiving posaconazole prophylaxis or treatment for fungal infections were enrolled in a prospective observational study. Samples for posaconazole and C-reactive protein (CRP) concentrations were collected routinely for each patient. Longitudinal data analysis was performed to analyse the correlation between posaconazole serum trough concentrations and CRP values, corrected for potential factors that could influence the posaconazole concentration. Between August 2015 and June 2017, 64 patients were recruited to this study. Data for 55 patients (511 posaconazole samples) were included in the final analysis. The overall median posaconazole concentration was 1.8 mg/L [interquartile range (IQR) 1-2.9 mg/L, range 0.1-7.94 mg/L] and the overall median CRP concentration was 23.5 mg/L (IQR 5-75 mg/L, range 0-457 mg/L). Longitudinal data analysis showed that only the posaconazole daily dose (in mg/kg body weight) had a significant influence on posaconazole concentration after correction for other factors (P < 0.0001). Posaconazole concentrations were not influenced by CRP concentrations (P = 0.77). Posaconazole concentrations are not influenced by inflammation, reflected by CRP concentration. Therefore, more frequent therapeutic drug monitoring of posaconazole during inflammation or after an infection subsides is not necessary., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)