Therapeutic Drug Monitoring of Antibiotics in Critically Ill Patients: Current Practice and Future Perspectives With a Focus on Clinical Outcome

A new perspective on antimicrobial therapeutic drug monitoring: Surface-enhanced Raman spectroscopy

Therapeutic drug monitoring (TDM) enables the personalization of treatment regimens, enhancing efficacy in combating infectious diseases while minimizing toxicity risks and reducing the potential for pathogenic resistance. However, existing TDM techniques still present certain limitations. Chromatographic analysis involves a prolonged detection period, which hampers its capacity for rapid multi-sample analysis. Immunoassay is constrained by poor specificity and stability, as well as a restricted range of detectable drugs. Surface-enhanced Raman spectroscopy (SERS) amplifies the Raman signals of target molecules via the local electromagnetic field and charge transfer effects on the surface of plasmonic materials, offering many significant advantages including high sensitivity, rapid detection, minimal sample requirements, and the ability to provide molecular fingerprints. SERS biosensing has demonstrated considerable potential in the field of blood drug concentration monitoring. This paper comprehensively reviews the research on the application of SERS in the TDM of antimicrobial agents. Beginning with the clinical practice of antimicrobial TDM, this review systematically introduces the principles of SERS techniques, the enhancement substrates, and the commonly used data processing methods including machine learning. It then provides a detailed discussion of the application of SERS in the TDM of various types of antimicrobials. Finally, it summarizes four major challenges currently faced by SERS techniques in antimicrobial TDM-namely protein corona effects, matrix interferences, substrate heterogeneity, and quantification reproducibility-and proposes potential future directions. This paper aims to offer new strategies and perspectives for the TDM and personalized dosage of antimicrobial agents.

Teicoplanin pharmacokinetics in critically ill patients on extracorporeal organ support: a retrospective analysis

BACKGROUND

Extracorporeal membrane oxygenation (ECMO) can alter the pharmacokinetics of diverse antimicrobials, posing challenges in achieving therapeutic drug levels. Some literature suggests that teicoplanin may require higher dosing in ECMO patients, however the respective evidence is scarce. The aim of this study was to assess teicoplanin trough levels in critically patients on ECMO support and to compare patients with and without additional continuous renal replacement therapy (CRRT). We conducted a retrospective study at the Intensive Care Unit (ICU) of the University Hospital Zurich, Switzerland. Teicoplanin trough levels and doses were analyzed in critically ill patients during ECMO support by means of a non-parametric local estimated polynomial regression. Outcomes included the proportion of patients with insufficient or toxic teicoplanin trough levels, dosage adjustments, and differences in teicoplanin trough levels between patients with and without additional CRRT during ECMO support.

RESULTS

After screening 172 patients receiving teicoplanin therapy during their ICU stay from 1.1.2020 to 19.07.2023, a total of 23 adult patients were included. The proportion of patients with insufficient teicoplanin levels was notably higher during ECMO support compared to patients with toxic levels (78.3% vs. 13% of patients, respectively). Teicoplanin dosages mostly were increased during the first few days of ECMO treatment. Concomitant CRRT led to a further increase in the proportion of patients with insufficient levels.

CONCLUSIONS

Teicoplanin trough levels using standard dosing tend to be low in patients on ECMO support, especially in the early days of therapy. Higher doses than the standard regimen are often necessary to achieve therapeutic levels, particularly in patients receiving additional CRRT.

Therapeutic drug monitoring of antibiotics for methicillin-resistant Staphylococcus aureus infections: an updated narrative review for clinicians

BACKGROUND

Infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are associated with high mortality rates. Optimal antibiotic dosage plays a crucial role in reducing MRSA burden; thus, the use of therapeutic drug monitoring (TDM) in the clinical practice, especially of new drugs such as ceftobiprole, ceftaroline, dalbavancin, and oritavancin, should be implemented.

OBJECTIVES

We aim to examine and summarize the available evidence about TDM of anti-MRSA molecules, with a focus on pneumonia, endocarditis and vascular infections, and bone and joint infections.

SOURCES

We applied 'therapeutic drug monitoring' and 'Staphylococcus aureus' as search terms in PubMed, considering a time frame of 24 years (2001-2024). Articles in English language, non-duplicated, evaluating antibiotic therapeutic target, and role of TDM were included in the study.

CONTENT

In this review, available data for therapeutic target and TDM were critically analysed and summarized and suggestions about the use of old and new anti-MRSA antibiotics were provided, focusing on optimal dosages, tissue penetration according to infection types, and toxicity. Limitations to the widespread use of TDM in clinical practice were discussed.

IMPLICATIONS

The use of TDM may play an important role for the optimal management of patients with MRSA infections and may impact on patient outcomes by increasing efficacy and reducing the risk of adverse events. TDM may be implemented in clinical practice; however, several limitations such as the wide variability in the methodology and the need for skilled personnel need to be considered.

PK/PD Analysis of High-Dose Daptomycin Use in the Treatment of Bone and Joint Infections: Data from a Real-World Setting

BACKGROUND

Daptomycin is widely used in bone and joint infections (BJIs) caused by Gram-positive cocci. The pharmacokinetics of daptomycin are characterized by relevant variability in terms of drug exposure. Due to these pharmacological properties, the dosing suggested by the Summary of medical Product Characteristics could result in sub-therapeutic or toxic concentrations, especially considering the high doses recommended for BJIs. Therapeutic Drug Monitoring (TDM) of daptomycin helps clinicians in verifying the patient's exposure, due to the lack of pharmacokinetic/pharmacodynamic (PK/PD) data in this clinical setting.

METHODS

We retrospectively analyzed 170 daptomycin plasma concentrations of 77 patients with BJIs from July 2022 to December 2023. We focused on the pharmacokinetics of daptomycin to investigate when drug plasma concentrations achieved adequate PK/PD targets.

RESULTS

In the first TDM, 7.8% of patients were underexposed according to the estimated area under the curve (eAUC0-24h < 666 mg·h/L), whereas 35.1% were on target according to both the eAUC and trough plasma concentration (eAUC0-24h 666 - 939 mg·h/L; Cmin < 24.3 mg/L). The patients who were overexposed had trough plasma concentrations > 24.3 mg/L (27.3%) or eAUC0-24h > 1174 mg·h/L (33.8%). Differences in drug exposure were observed according to weight and sex.

CONCLUSIONS

Due to the difficult management of this drug's dosing, analyzing daptomycin plasma concentrations through TDM represents a powerful tool in BJIs.

Dose Evaluation and Optimization of Amoxicillin in Children Treated for Lyme Disease

Amoxicillin is commonly used to treat erythema migrans in the first stage of Lyme disease in children, with a recommended dose of 50 mg/kg/day, administered three times a day (q8h). This model-based simulation study aimed to determine whether splitting the same daily dose into two administrations (q12h) would provide comparable drug exposure. A pharmacokinetic model suitable for a pediatric population (age: 1 month to 18 years, weight: 4-80 kg) was selected through a literature review. Simulations were performed with 15,000 virtual patients receiving 16.67 mg/kg/dose q8h, 25 mg/kg/dose q12h, or other q12h dosing variations. The target therapeutic level was defined by the percentage of time that the unbound drug concentration remained above the minimum inhibitory concentration (% fT > MIC) specific to Borrelia burgdorferi, with MICs of 0.06, 0.25, 1, 2, and 4 mg/L, requiring at least 40% and 50% of time for effective treatment. Probability of target attainment (PTA) was considered acceptable if it exceeded 50%, allowing for comparison of dosing schedules. Results indicated that the 50 mg/kg/day divided q12h regimen provided similar drug exposure to the q8h regimen for MICs below 2 mg/L (PTAs >50%). For a MIC of 2 mg/L, PTA was achieved with a higher dose of 30 mg/kg/dose q12h. However, for a MIC of 4 mg/L, the PTA criterion was not met. These findings suggest that a twice-daily dosing of 25 mg/kg/dose provides comparable bactericidal activity to the thrice-daily regimen for MICs between 0.06 and 1 mg/L. This simplified regimen may improve adherence and treatment implementation in children.

Dose Individualisation of Antimicrobials from a Pharmacometric Standpoint: The Current Landscape

Successful antimicrobial therapy depends on achieving optimal drug concentrations within individual patients. Inter-patient variability in pharmacokinetics (PK) and differences in pathogen susceptibility (reflected in the minimum inhibitory concentration, [MIC]) necessitate personalised approaches. Dose individualisation strategies aim to address this challenge, improving treatment outcomes and minimising the risk of toxicity and antimicrobial resistance. Therapeutic drug monitoring (TDM), with the application of population pharmacokinetic (popPK) models, enables model-informed precision dosing (MIPD). PopPK models mathematically describe drug behaviour across populations and can be combined with patient-specific TDM data to optimise dosing regimens. The integration of machine learning (ML) techniques promises to further enhance dose individualisation by identifying complex patterns within extensive datasets. Implementing these approaches involves challenges, including rigorous model selection and validation to ensure suitability for target populations. Understanding the relationship between drug exposure and clinical outcomes is crucial, as is striking a balance between model complexity and clinical usability. Additionally, regulatory compliance, outcome measurement, and practical considerations for software implementation will be addressed. Emerging technologies, such as real-time biosensors, hold the potential for revolutionising TDM by enabling continuous monitoring, immediate and frequent dose adjustments, and near patient testing. The ongoing integration of TDM, advanced modelling techniques, and ML within the evolving digital health care landscape offers a potential for enhancing antimicrobial therapy. Careful attention to model development, validation, and ethical considerations of the applied techniques is paramount for successfully optimising antimicrobial treatment for the individual patient.

Model-Informed Precision Dosing of Tacrolimus: A Systematic Review of Population Pharmacokinetic Models and a Benchmark Study of Software Tools

BACKGROUND AND OBJECTIVE

Tacrolimus is an immunosuppressant commonly administered after solid organ transplantation. It is characterized by a narrow therapeutic window and high variability in exposure, demanding personalized dosing. In recent years, population pharmacokinetic models have been suggested to guide model-informed precision dosing of tacrolimus. We aimed to provide a comprehensive overview of population pharmacokinetic models and model-informed precision dosing software modules of tacrolimus in all solid organ transplant settings, including a simulation-based investigation of the impact of covariates on exposure and target attainment.

METHODS

We performed a systematic literature search to identify population pharmacokinetic models of tacrolimus in solid organ transplant recipients. We integrated selected population pharmacokinetic models into an interactive software tool that allows dosing simulations, Bayesian forecasting, and investigation of the impact of covariates on exposure and target attainment. We conducted a web survey amongst model-informed precision dosing software tool providers and benchmarked publicly available tools in terms of models, target populations, and clinical integration.

RESULTS

We identified 80 population pharmacokinetic models, including 44 one-compartment and 36 two-compartment models. The most frequently retained covariates on clearance and distribution parameters were cytochrome P450 3A5 polymorphisms and body weight, respectively. Our simulation tool, hosted at https://lpmx.shinyapps.io/tacrolimus/ , allows thorough investigation of the impact of covariates on exposure and target attainment. We identified 15 model-informed precision dosing software tool providers, of which ten offer a tacrolimus solution and nine completed the survey.

CONCLUSIONS

Our work provides a comprehensive overview of the landscape of available tacrolimus population pharmacokinetic models and model-informed precision dosing software modules. Our simulation tool allows an interactive thorough exploration of covariates on exposure and target attainment.

The New Delhi metallo-β-lactamase-1 biosensor rapidly and accurately detected antibiotic plasma concentrations in cefuroxime-treated patients

OBJECTIVES

Therapeutic drug monitoring (TDM) of β-lactam antibiotics in critically ill patients may benefit dose optimisation, thus improving therapeutic outcomes. However, rapidly and accurately detecting these antibiotics in blood remains a challenge. This research group recently developed a thermometric biosensor called the New Delhi metallo-β-lactamase-1 (NDM-1) biosensor, which detects multiple classes of β-lactam antibiotics in spiked plasma samples.

METHODS

This study assessed the NDM-1 biosensor's effectiveness in detecting plasma concentrations of β-lactam antibiotics in treated patients. Seven patients receiving cefuroxime were studied. Plasma samples collected pre- and post-antibiotic treatment were analysed using the NDM-1 biosensor and compared with liquid chromatography coupled with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).

RESULTS

The biosensor detected plasma samples without dilution, and a brief pre-treatment using a polyvinylidene fluoride filter significantly lowered matrix effects, reducing the running time to 5-8 minutes per sample. The assay's linear range for cefuroxime (6.25-200 mg/L) covered target concentrations during the trough phase of pharmacokinetics in critically ill patients. The pharmacokinetic properties of cefuroxime in treated patients determined by the NDM-1 biosensor and the UPLC-MS/MS were comparable, and the cefuroxime plasma concentrations measured by the two methods showed statistically good consistency.

CONCLUSION

These data demonstrate that the NDM-1 biosensor assay is a fast, sensitive, and accurate method for detecting cefuroxime plasma concentrations in treated patients and highlights the NDM-1 biosensor as a promising tool for on-site TDM of β-lactam antibiotics in critically ill patients.

Development of a rapid LC-MS/MS method for simultaneous quantification of ten commonly used antibiotic drugs in human serum

The use of TDM in clinical practice to monitor the plasma levels of antibiotics administered to critically ill patients is a well-established approach that allows for optimization of the patient's response to drug therapy, considering the characteristics of the drug, the clinical and physiological status of the patient and any peculiar of the pathogen that caused the clinical picture. In our laboratory, we have developed a single LC-MS/MS analysis for dosing the serum concentration of an antibacterial panel composed of eight antibacterial and two selective inhibitors. The method presented used a certified material furnished by a commercial company and was internally validated using the EMA guidelines. The results have shown high sensitivity, precision, and accuracy, a lower matrix effect combined with simple sample preparation and a time-saving procedure. We have evaluated the recovery rate and matrix effect by testing serum samples without pathological index and serum pools obtained from haemolysed, icteric, or lipemic samples. The assay has shown a recovery range between 94% and 101%.

Implementation of Modern Therapeutic Drug Monitoring and Lipidomics Approaches in Clinical Practice: A Case Study with Colistin Treatment

Nowadays, lipidomics plays a crucial role in the investigation of novel biomarkers of various diseases. Its implementation into the field of clinical analysis led to the identification of specific lipids and/or significant changes in their plasma levels in patients suffering from cancer, Alzheimer's disease, sepsis, and many other diseases and pathological conditions. Profiling of lipids and determination of their plasma concentrations could also be helpful in the case of drug therapy management, especially in combination with therapeutic drug monitoring (TDM). Here, for the first time, a combined approach based on the TDM of colistin, a last-resort antibiotic, and lipidomic profiling is presented in a case study of a critically ill male patient suffering from Pseudomonas aeruginosa-induced pneumonia. Implementation of innovative analytical approaches for TDM (online combination of capillary electrophoresis with tandem mass spectrometry, CZE-MS/MS) and lipidomics (liquid chromatography-tandem mass spectrometry, LC-MS/MS) was demonstrated. The CZE-MS/MS strategy confirmed the chosen colistin drug dosing regimen, leading to stable colistin concentrations in plasma samples. The determined colistin concentrations in plasma samples reached the required minimal inhibitory concentration of 1 μg/mL. The complex lipidomics approach led to monitoring 545 lipids in collected patient plasma samples during and after the therapy. Some changes in specific individual lipids were in good agreement with previous lipidomics studies dealing with sepsis. The presented case study represents a good starting point for identifying particular individual lipids that could correlate with antimicrobial and inflammation therapeutic management.

Overview of therapeutic drug monitoring and clinical practice

With the rapid development of clinical pharmacy in China, therapeutic drug monitoring (TDM) has become an essential tool for guiding rational clinical drug use and is widely concerned. TDM is a tool that combines pharmacokinetic and pharmacodynamic knowledge to optimize personalized drug therapy, which can improve treatment outcomes, reduce drug-drug toxicity, and avoid the risk of developing drug resistance. To effectively implement TDM, accurate and sophisticated analytical methods are required. By researching the literature published in recent years, we summarize the types of commonly monitored drugs, therapeutic windows, and clinical assays and track the trends and hot spots of therapeutic drug monitoring. The purpose is to provide guidelines for clinical blood drug concentration monitoring, to implement individualized drug delivery programs better, to ensure the rational use of drugs for patients, and to provide a reference for the group to carry out related topics in the future.

External evaluation of the predictive performance of published population pharmacokinetic models of linezolid in adult patients

OBJECTIVES

Several linezolid population pharmacokinetic (popPK) models have been established to facilitate optimal therapy; however, their extrapolated predictive performance to other clinical sites is unknown. This study aimed to externally evaluate the predictive performance of published pharmacokinetic models of linezolid in adult patients.

METHODS

For the evaluation dataset, 150 samples were collected from 70 adult patients (72.9% of which were critically ill) treated with linezolid at our center. Twenty-five published popPK models were identified from PubMed and Embase. Model predictability was evaluated using prediction-based, simulation-based, and Bayesian forecasting-based approaches to assess model predictability.

RESULTS

Prediction-based diagnostics found that the prediction error within ±30% (F30) was less than 40% in all models, indicating unsatisfactory predictability. The simulation-based prediction- and variability-corrected visual predictive check and normalized prediction distribution error test indicated large discrepancies between the observations and simulations in most of the models. Bayesian forecasting with one or two prior observations significantly improved the models' predictive performance.

CONCLUSION

The published linezolid popPK models showed insufficient predictive ability. Therefore, their sole use is not recommended, and incorporating therapeutic drug monitoring of linezolid in clinical applications is necessary.

A novel strategy for therapeutic drug monitoring: application of biosensors to quantify antimicrobials in biological matrices

Over the past few years, therapeutic drug monitoring (TDM) has gained practical significance in antimicrobial precision therapy. Yet two categories of mainstream TDM techniques (chromatographic analysis and immunoassays) that are widely adopted nowadays retain certain inherent limitations. The use of biosensors, an innovative strategy for rapid evaluation of antimicrobial concentrations in biological samples, enables the implementation of point-of-care testing (POCT) and continuous monitoring, which may circumvent the constraints of conventional TDM and provide strong technological support for individualized antimicrobial treatment. This comprehensive review summarizes the investigations that have harnessed biosensors to detect antimicrobial drugs in biological matrices, provides insights into the performance and characteristics of each sensing form, and explores the feasibility of translating them into clinical practice. Furthermore, the future trends and obstacles to achieving POCT and continuous monitoring are discussed. More efforts are necessary to address the four key 'appropriateness' challenges to deploy biosensors in clinical practice, paving the way for personalized antimicrobial stewardship.

Analytical validation of a novel UHPLC-MS/MS method for 19 antibiotics quantification in plasma: Implementation in a LC-MS/MS Kit

BACKGROUND

Therapeutic drug monitoring (TDM) for antibiotic drugs represents a consolidated practice to optimize the effectiveness and to limit the toxicity of specific drugs by guiding dosage adjustments. The comparison of TDM results with drug-specific pharmacokinetic/pharmacodynamic (PK/PD) parameters, based on killing dynamics and bacterial susceptibility, increases the probability of therapeutic success.

PURPOSE

The aim of this study was the analytical validation of a new UHPLC-MS/MS assay for the quantification of 19 antibiotics divided in two different sets considering their chemical/pharmacological properties. This method has been implemented in an analytical LC-MS/MS Kit System by CoQua Lab s.r.l (Turin).

METHODS

The analytical validation is developed in accordance with "ICH Harmonized Guideline M10 on bioanalytical method validation and study sample analysis" and "Guidelines for regulatory auditing of quality management system of medical device manufacturers". Method suitability in the clinical context was tested by analysing clinical samples from patients treated with antibiotic drugs.

RESULTS

This method allows for simultaneous TDM of the following molecules: dalbavancin, daptomycin, linezolid, tedizolid, levofloxacin, moxifloxacin, meropenem, ertapenem, vaborbactam, avibactam, sulbactam, tazobactam, ceftazidime, ceftriaxone, ceftolozane, ceftobiprole, cefiderocol, ceftaroline and piperacillin. These drugs were quantified showing analytical performance parameters compliant with guidelines in terms of repeatability, reproducibility, robustness, bias, LOD, LOQ and linearity. The method was capable to successfully monitor drug concentrations in 65 samples from 52 patients undergoing treatment.

CONCLUSION

The UHPLC-MS/MS method described in this work can be useful for TDM of the reported antimicrobial agents. The analytical protocol is rapid and suitable to be used in routine analysis.

Individualised antimicrobial dose optimisation: a systematic review and meta-analysis of randomised controlled trials

BACKGROUND

Therapeutic drug management (TDM) and model-informed precision dosing (MIPD) allow dose individualisation to increase drug effectivity and reduce toxicity.

OBJECTIVES

Evaluate the available evidence on the clinical efficacy of individualised antimicrobial dosing optimisation.

METHODS

Data sources: Pubmed, Embase, Web of Science, and Cochrane Library databases from database inception to the 11th of November 2022.

STUDY ELIGIBILITY CRITERIA

Published peer-reviewed Randomised Controlled Trials (RCTs).

PARTICIPANTS

Human subjects aged ≥18 years receiving an antibiotic or antifungal drug.

INTERVENTIONS

Patients receiving individualised antimicrobial dose adjustment. Assessment of risk of bias: Cochrane risk-of-bias tool for randomised trials (RoB2). Methods of data synthesis: Primary outcome was the risk of mortality. Secondary outcomes included target attainment, treatment failure, clinical and microbiological cure, length of stay, treatment duration and adverse events. Effect sizes were pooled using a random-effects model. Statistical heterogeneity was assessed by inconsistency testing (I²).

RESULTS

Ten RCTs were included in the meta-analysis (1,241 participants; n= 624 in the TDM group, n = 617 in the control group). Individualised antimicrobial dose optimisation was associated with a numerical decrease in mortality (RR = 0.86; 95% CI 0.71-1.05), without reaching statistical significance. Moreover, it was associated with significantly higher target attainment rates (RR = 1.41; 95% CI, 1.13-1.76) and a significant decrease in treatment failure (RR = 0.70; 95% CI, 0.54-0.92). Individualised antimicrobial dose optimisation was also associated with improvement, but not significant in clinical cure (RR = 1.33; 95% CI, 0.94-1.33) and microbiological outcome (RR = 1.25; CI, 1.00-1.57), as well as with a significant decrease in the risk of nephrotoxicity (RR = 0.55; 95% CI, 0.31-0.97).

CONCLUSIONS

This meta-analysis demonstrates that target attainment, treatment failure, and nephrotoxicity were significantly improved in patients who underwent individualised antimicrobial dose optimisation. However, it did not show a significant decrease in mortality, clinical cure or microbiological outcome.

Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients

In individualized therapy, the Bayesian approach integrated with population pharmacokinetic models (PopPK) for predictions together with therapeutic drug monitoring (TDM) to maintain adequate objectives is useful to maximize the efficacy and minimize the probability of toxicity of vancomycin in critically ill patients. Although there are limitations to implementation, model-informed precision dosing (MIPD) is an approach to integrate these elements, which has the potential to optimize the TDM process and maximize the success of antibacterial therapy. The objective of this work was to present an app for individualized therapy and perform a validation of the implemented vancomycin PopPK models. A pragmatic approach was used for selecting the models of Llopis, Goti and Revilla for developing a Shiny app with R. Through ordinary differential equation (ODE)-based mixed effects models from the mlxR package, the app simulates the concentrations' behavior, estimates whether the model was simulated without variability and predicts whether the model was simulated with variability. Moreover, we evaluated the predictive performance with retrospective trough concentration data from patients admitted to the adult critical care unit. Although there were no significant differences in the performance of the estimates, the Llopis model showed better accuracy (mean 80.88%; SD 46.5%); however, it had greater bias (mean -34.47%, SD 63.38%) compared to the Revilla et al. (mean 10.61%, SD 66.37%) and Goti et al. (mean of 13.54%, SD 64.93%) models. With respect to the RMSE (root mean square error), the Llopis (mean of 10.69 mg/L, SD 12.23 mg/L) and Revilla models (mean of 10.65 mg/L, SD 12.81 mg/L) were comparable, and the lowest RMSE was found in the Goti model (mean 9.06 mg/L, SD 9 mg/L). Regarding the predictions, this behavior did not change, and the results varied relatively little. Although our results are satisfactory, the predictive performance in recent studies with vancomycin is heterogeneous, and although these three models have proven to be useful for clinical application, further research and adaptation of PopPK models is required, as well as implementation in the clinical practice of MIPD and TDM in real time.

Critically Ill Patients with Renal Hyperfiltration: Optimizing Antibiotic Dose

Renal hyperfiltration (RHF) is a prevalent phenomenon in critically ill patients characterized by augmented renal clearance (ARC) and increased of elimination of renally eliminated medications. Multiple risk factors had been described and potential mechanisms may contribute to the occurrence of this condition. RHF and ARC are associated with the risk of suboptimal exposure to antibiotics increasing the risk of treatment failure and unfavorable patient outcomes. The current review discusses the available evidence related to the RHF phenomenon, including definition, epidemiology, risk factors, pathophysiology, pharmacokinetic variability, and considerations for optimizing the dosage of antibiotics in critically ill patients.

Wearable microneedle-based electrochemical aptamer biosensing for precision dosing of drugs with narrow therapeutic windows

Therapeutic drug monitoring is essential for dosing pharmaceuticals with narrow therapeutic windows. Nevertheless, standard methods are imprecise and involve invasive/resource-intensive procedures with long turnaround times. Overcoming these limitations, we present a microneedle-based electrochemical aptamer biosensing patch (μNEAB-patch) that minimally invasively probes the interstitial fluid (ISF) and renders correlated, continuous, and real-time measurements of the circulating drugs' pharmacokinetics. The μNEAB-patch is created following an introduced low-cost fabrication scheme, which transforms a shortened clinical-grade needle into a high-quality gold nanoparticle-based substrate for robust aptamer immobilization and efficient electrochemical signal retrieval. This enables the reliable in vivo detection of a wide library of ISF analytes-especially those with nonexistent natural recognition elements. Accordingly, we developed μNEABs targeting various drugs, including antibiotics with narrow therapeutic windows (tobramycin and vancomycin). Through in vivo animal studies, we demonstrated the strong correlation between the ISF/circulating drug levels and the device's potential clinical use for timely prediction of total drug exposure.

How Surface-Enhanced Raman Spectroscopy Could Contribute to Medical Diagnoses

In the last decade, there has been a rapid increase in the number of surface-enhanced Raman scattering (SERS) spectroscopy applications in medical research. In this article we review some recent, and in our opinion, most interesting and promising applications of SERS spectroscopy in medical diagnostics, including those that permit multiplexing within the range important for clinical samples. We focus on the SERS-based detection of markers of various diseases (or those whose presence significantly increases the chance of developing a given disease), and on drug monitoring. We present selected examples of the SERS detection of particular fragments of DNA or RNA, or of bacteria, viruses, and disease-related proteins. We also describe a very promising and elegant ‘lab-on-chip’ approach used to carry out practical SERS measurements via a pad whose action is similar to that of a pregnancy test. The fundamental theoretical background of SERS spectroscopy, which should allow a better understanding of the operation of the sensors described, is also briefly outlined. We hope that this review article will be useful for researchers planning to enter this fascinating field.

Importance and Reality of TDM for Antibiotics Not Covered by Insurance in Japan

Under the Japanese health insurance system, medicines undergoing therapeutic drug monitoring (TDM) can be billed for medical fees if they meet the specified requirements. In Japan, TDM of vancomycin, teicoplanin, aminoglycosides, and voriconazole, which are used for the treatment of infectious diseases, is common practice. This means the levels of antibiotics are measured in-house using chromatography or other methods. In some facilities, the blood and/or tissue concentrations of other non-TDM drugs are measured by HPLC and are applied to treatment, which is necessary for personalized medicine. This review describes personalized medicine based on the use of chromatography as a result of the current situation in Japan.