Therapeutic Drug Monitoring in Critical Care: Optimizing Antibiotic Dosing in the Era of Precision Medicine
Abstract
Background: Critically ill patients present unique pharmacokinetic and pharmacodynamic challenges that significantly impact antibiotic efficacy and safety. Traditional fixed-dosing regimens often fail to achieve optimal therapeutic outcomes in this population due to altered drug disposition, variable protein binding, and dynamic pathophysiological changes.
Objective: This review examines the current evidence and clinical applications of therapeutic drug monitoring (TDM) for antibiotics in critical care, emphasizing its role in precision medicine approaches to optimize patient outcomes.
Methods: We conducted a comprehensive literature review of peer-reviewed articles published between 2019-2024, focusing on TDM applications for commonly used antibiotics in critically ill patients, including beta-lactams, vancomycin, aminoglycosides, and novel agents.
Results: TDM-guided antibiotic dosing demonstrates significant improvements in clinical outcomes including reduced mortality, decreased nephrotoxicity, shorter length of stay, and improved microbiological cure rates. Real-time TDM technologies and population pharmacokinetic models are emerging as practical tools for bedside implementation.
Conclusions: TDM represents a cornerstone of precision medicine in critical care, enabling individualized antibiotic therapy that maximizes efficacy while minimizing toxicity. Integration of TDM into routine critical care practice requires multidisciplinary collaboration and institutional commitment to infrastructure development.
Keywords: Therapeutic drug monitoring, critical care, antibiotics, precision medicine, pharmacokinetics, intensive care unit
1. Introduction
The management of critically ill patients represents one of the most complex challenges in modern medicine, with antimicrobial therapy serving as a cornerstone of treatment for sepsis and infection-related organ dysfunction. The physiological derangements characteristic of critical illness—including altered distribution volumes, variable protein binding, dynamic renal and hepatic function, and extracorporeal support therapies—create a perfect storm of pharmacokinetic unpredictability that renders traditional dosing strategies inadequate.¹
Therapeutic drug monitoring (TDM) has emerged as an essential tool in the critical care armamentarium, offering a pathway to precision medicine that optimizes antibiotic exposure while minimizing adverse effects. The concept of precision medicine in critical care extends beyond genomics to encompass real-time adaptation of therapy based on individual patient pharmacokinetic profiles and dynamic clinical status.²
The stakes of antibiotic optimization in critical care cannot be overstated. Subtherapeutic antibiotic concentrations are associated with treatment failure, increased mortality, and the emergence of antimicrobial resistance, while supratherapeutic levels increase the risk of dose-dependent toxicities.³ This narrow therapeutic window, combined with the pharmacokinetic volatility of critical illness, makes TDM not merely beneficial but often essential for optimal patient care.
2. Pharmacokinetic Alterations in Critical Illness
2.1 Absorption and Distribution Changes
Critical illness profoundly alters drug pharmacokinetics through multiple mechanisms. Increased capillary permeability and fluid resuscitation lead to expanded distribution volumes, particularly for hydrophilic antibiotics such as beta-lactams and aminoglycosides. Studies demonstrate that distribution volumes can increase by 50-100% in critically ill patients compared to healthy individuals, necessitating higher loading doses to achieve therapeutic concentrations.⁴
Altered protein binding represents another critical factor, particularly for highly protein-bound antibiotics. Hypoalbuminemia, common in critical illness, increases the free fraction of drugs like ceftriaxone and ertapenem, potentially altering both efficacy and toxicity profiles. Additionally, the presence of uremic toxins and inflammatory mediators can displace drugs from protein binding sites, further complicating dosing predictions.⁵
2.2 Clearance Mechanisms
Renal clearance variability represents perhaps the most significant challenge in antibiotic dosing for critically ill patients. Traditional markers of renal function, such as serum creatinine, often poorly correlate with actual drug clearance due to reduced muscle mass, altered creatinine production, and dynamic changes in glomerular filtration rate.⁶
Augmented renal clearance (ARC), defined as creatinine clearance >130 mL/min/1.73m², affects up to 65% of critically ill patients, particularly younger patients with trauma, burns, or neurological injuries. ARC leads to enhanced elimination of renally cleared antibiotics, potentially resulting in subtherapeutic concentrations despite standard dosing.⁷
Hepatic metabolism is similarly altered in critical illness through multiple mechanisms including reduced hepatic blood flow, altered enzyme activity, and drug-drug interactions. These changes particularly affect antibiotics metabolized through the cytochrome P450 system, such as certain azoles and macrolides.⁸
2.3 Impact of Extracorporeal Therapies
Continuous renal replacement therapy (CRRT), extracorporeal membrane oxygenation (ECMO), and plasmapheresis significantly alter antibiotic pharmacokinetics through drug removal, adsorption to circuit components, and changes in distribution volumes. The clearance of antibiotics during CRRT depends on multiple factors including molecular weight, protein binding, filter characteristics, and treatment modalities.⁹
ECMO circuits can sequester significant amounts of lipophilic drugs through adsorption to circuit components, while also altering distribution volumes through priming solutions and increased cardiac output. These effects are particularly pronounced for drugs like vancomycin and linezolid.¹⁰
3. Principles of Therapeutic Drug Monitoring
3.1 Pharmacokinetic/Pharmacodynamic Relationships
Understanding the pharmacokinetic/pharmacodynamic (PK/PD) relationship of antibiotics is fundamental to implementing effective TDM strategies. Antibiotics can be broadly classified into three PK/PD categories: concentration-dependent killing (aminoglycosides, fluoroquinolones), time-dependent killing (beta-lactams), and concentration-dependent with prolonged post-antibiotic effect (vancomycin, lincomycin).¹¹
For concentration-dependent antibiotics, the peak concentration (Cmax) to minimum inhibitory concentration (MIC) ratio or area under the curve (AUC) to MIC ratio correlates with efficacy. Time-dependent antibiotics achieve optimal killing when free drug concentrations remain above the MIC for a specified percentage of the dosing interval (fT>MIC). Understanding these relationships guides both sampling strategies and therapeutic targets for TDM.¹²
3.2 Therapeutic Targets and Sampling Strategies
Establishing appropriate therapeutic targets requires integration of PK/PD principles with clinical evidence. For vancomycin, the 2020 consensus guidelines recommend AUC/MIC ratios of 400-600 for serious MRSA infections, representing a paradigm shift from trough-based monitoring.¹³ This change was driven by evidence linking AUC-guided dosing with improved efficacy and reduced nephrotoxicity compared to trough-based approaches.
Beta-lactam antibiotics require different sampling strategies focused on achieving adequate fT>MIC. For critically ill patients, targets of 100% fT>4×MIC are often recommended to account for increased MIC variability and altered pharmacokinetics. This frequently necessitates extended or continuous infusion strategies guided by TDM.¹⁴
3.3 Analytical Methods and Turnaround Times
The clinical utility of TDM depends heavily on analytical capabilities and turnaround times. Traditional methods such as high-performance liquid chromatography (HPLC) and immunoassays provide accurate results but often require 4-12 hours for processing, limiting real-time clinical decision-making.¹⁵
Emerging point-of-care technologies, including biosensors and rapid immunoassays, promise to reduce turnaround times to minutes or hours, enabling more responsive dosing adjustments. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) represents another promising technology for rapid, simultaneous measurement of multiple antibiotics.¹⁶
4. Drug-Specific TDM Applications
4.1 Vancomycin
Vancomycin TDM has evolved significantly following the 2020 consensus guidelines emphasizing AUC-guided dosing. The recommended AUC₀₋₂₄ target of 400-600 mg·h/L for serious MRSA infections requires sophisticated pharmacokinetic modeling, often implemented through Bayesian forecasting software.¹⁷
Clinical studies demonstrate that AUC-guided dosing reduces nephrotoxicity by 25-30% compared to trough-based monitoring while maintaining or improving efficacy. The implementation requires institutional investment in pharmacokinetic software and clinical pharmacist support, but the benefits in terms of patient outcomes and reduced adverse events justify these resources.¹⁸
4.2 Beta-Lactam Antibiotics
Beta-lactam TDM has gained increasing acceptance as evidence mounts for improved outcomes with optimized dosing. The time-dependent killing profile of beta-lactams necessitates maintaining free drug concentrations above the MIC for optimal efficacy. In critically ill patients, achieving 100% fT>4×MIC often requires dose escalation, extended infusions, or continuous infusion strategies.¹⁹
Piperacillin-tazobactam represents a prime example where TDM demonstrates clear clinical benefits. Studies show that patients achieving target piperacillin concentrations have significantly higher cure rates and lower mortality compared to those with subtherapeutic levels. The challenge lies in the drug's short half-life and need for frequent sampling or sophisticated modeling.²⁰
Meropenem TDM is particularly valuable in critically ill patients where standard dosing frequently results in subtherapeutic concentrations. Extended infusion strategies guided by TDM can improve the probability of target attainment while potentially reducing total daily doses and associated costs.²¹
4.3 Aminoglycosides
Aminoglycoside TDM represents one of the most established applications in critical care, with decades of evidence supporting improved outcomes and reduced toxicity. The concentration-dependent killing profile and narrow therapeutic window make TDM essential for optimizing the Cmax/MIC ratio while avoiding ototoxicity and nephrotoxicity.²²
Extended-interval dosing strategies, guided by TDM, have become standard practice in many institutions. These approaches capitalize on the post-antibiotic effect of aminoglycosides while minimizing toxicity through extended dosing intervals that allow drug clearance from tissues.²³
4.4 Novel Antibiotics
Newer antibiotics such as ceftaroline, ceftolozane-tazobactam, and meropenem-vaborbactam present unique TDM challenges due to limited pharmacokinetic data in critically ill populations. Early studies suggest that these agents may exhibit similar pharmacokinetic alterations as established beta-lactams, potentially requiring TDM for optimal outcomes.²⁴
Linezolid TDM has gained attention due to concerns about both efficacy and toxicity. Subtherapeutic concentrations are associated with treatment failure and resistance development, while excessive levels increase the risk of thrombocytopenia and peripheral neuropathy. The drug's variable pharmacokinetics in critical illness, compounded by drug-drug interactions, support the need for routine TDM.²⁵
5. Implementation Strategies and Clinical Integration
5.1 Multidisciplinary Team Approach
Successful TDM implementation requires a coordinated multidisciplinary approach involving intensivists, clinical pharmacists, laboratory personnel, and nursing staff. Clinical pharmacists play a central role in TDM programs, providing expertise in pharmacokinetic interpretation, dosing recommendations, and education.²⁶
The establishment of clear protocols and communication pathways ensures timely sampling, rapid result reporting, and prompt dosing adjustments. Regular multidisciplinary rounds should incorporate TDM data into clinical decision-making, fostering a culture that values precision dosing approaches.²⁷
5.2 Technology Integration
Modern TDM programs increasingly rely on sophisticated software platforms that integrate laboratory results with patient data to provide real-time dosing recommendations. Bayesian forecasting software, such as MwPharm, PrecisePK, and DoseMeRx, enable clinicians to optimize dosing based on individual patient pharmacokinetic parameters.²⁸
Electronic health record integration streamlines TDM workflows by automating sampling reminders, facilitating result review, and tracking dosing adjustments. Decision support tools can provide real-time alerts for subtherapeutic or supratherapeutic levels, prompting immediate clinical review.²⁹
5.3 Quality Improvement and Outcome Monitoring
Continuous quality improvement is essential for successful TDM programs. Key performance indicators should include target attainment rates, turnaround times for results, appropriateness of dosing adjustments, and clinical outcomes such as cure rates, length of stay, and adverse events.³⁰
Regular program evaluation should assess both process measures (adherence to sampling protocols, timely dosing adjustments) and outcome measures (clinical cure, mortality, toxicity rates). This data guides program refinements and demonstrates value to institutional stakeholders.³¹
6. Emerging Technologies and Future Directions
6.1 Real-Time Monitoring Technologies
The future of TDM lies in real-time, continuous monitoring technologies that provide immediate feedback on drug concentrations. Biosensor technologies, including aptamer-based sensors and molecularly imprinted polymers, show promise for continuous antibiotic monitoring.³²
Microdialysis techniques enable real-time monitoring of free drug concentrations in target tissues, providing unprecedented insights into antibiotic penetration and tissue exposure. While currently research tools, these technologies may eventually find clinical applications in specialized settings.³³
6.2 Artificial Intelligence and Machine Learning
Machine learning algorithms are increasingly being applied to TDM data to improve dosing predictions and identify patients at risk for therapeutic failure or toxicity. These approaches can integrate multiple data sources including patient demographics, laboratory values, and clinical parameters to provide more accurate dosing recommendations.³⁴
Population pharmacokinetic models enhanced by machine learning can adapt to institutional patient populations and provide more precise dosing guidance. These models can continuously learn from TDM data to improve accuracy over time.³⁵
6.3 Personalized Medicine Integration
The integration of pharmacogenomics with TDM represents the next frontier in precision antibiotic therapy. Genetic polymorphisms affecting drug metabolism, transport, and targets can significantly influence antibiotic pharmacokinetics and pharmacodynamics.³⁶
Biomarker-guided therapy, incorporating inflammatory markers, organ function indicators, and pathogen characteristics, may enable more precise therapeutic targeting. This holistic approach to precision medicine could optimize not only drug exposure but also treatment duration and combination therapy selection.³⁷
7. Economic Considerations and Cost-Effectiveness
7.1 Cost-Benefit Analysis
The economic impact of TDM programs extends beyond direct analytical costs to include personnel time, technology infrastructure, and training expenses. However, these costs must be weighed against the substantial benefits of improved patient outcomes, reduced adverse events, and decreased length of stay.³⁸
Studies consistently demonstrate that TDM programs are cost-effective when considering the total cost of care. Reduced nephrotoxicity from vancomycin optimization alone can save thousands of dollars per patient through avoided dialysis and extended hospitalizations.³⁹
7.2 Resource Allocation and Prioritization
Given resource constraints, institutions must prioritize TDM applications based on patient populations, drug characteristics, and potential impact. High-risk patients (severe illness, renal dysfunction, multiple organ failure) and high-risk drugs (narrow therapeutic windows, significant toxicity) should receive priority for TDM implementation.⁴⁰
Cost-effectiveness models can guide resource allocation decisions by identifying patient populations and clinical scenarios where TDM provides the greatest return on investment. These analyses should consider both short-term costs and long-term outcomes.⁴¹
8. Challenges and Limitations
8.1 Technical and Analytical Challenges
Despite advances in analytical technology, several technical challenges remain in TDM implementation. Assay standardization across laboratories can lead to variability in results and therapeutic targets. Matrix effects, drug stability, and interference from other medications can affect assay accuracy.⁴²
The complexity of pharmacokinetic modeling in critically ill patients presents ongoing challenges. Population pharmacokinetic models may not accurately predict individual patient pharmacokinetics, particularly in patients with multiple organ dysfunction or receiving extracorporeal therapies.⁴³
8.2 Clinical and Operational Barriers
Clinical acceptance of TDM remains variable among practitioners who may be unfamiliar with pharmacokinetic principles or skeptical of complex dosing algorithms. Education and training are essential to overcome these barriers and ensure appropriate TDM utilization.⁴⁴
Operational challenges include ensuring appropriate sampling times, maintaining sample integrity during transport, and coordinating dosing adjustments across nursing shifts. These logistical issues can significantly impact TDM effectiveness if not properly addressed.⁴⁵
8.3 Evidence Gaps and Research Needs
While evidence for TDM benefits continues to grow, significant gaps remain in our understanding of optimal targets for many antibiotics, particularly newer agents. Large-scale randomized controlled trials are needed to definitively establish the clinical benefits of TDM for various drug-pathogen combinations.⁴⁶
The relationship between drug concentrations and clinical outcomes may be more complex than current PK/PD models suggest, particularly in the setting of polymicrobial infections, biofilms, and immunocompromised hosts. Further research is needed to refine therapeutic targets for these complex clinical scenarios.⁴⁷
9. Conclusions
Therapeutic drug monitoring represents a paradigm shift toward precision medicine in critical care antibiotic therapy. The physiological derangements of critical illness create pharmacokinetic unpredictability that makes TDM not just beneficial but essential for optimizing patient outcomes. The evidence base supporting TDM continues to grow, with studies consistently demonstrating improved efficacy, reduced toxicity, and enhanced cost-effectiveness.
The successful implementation of TDM programs requires institutional commitment, multidisciplinary collaboration, and investment in both technology and personnel. While challenges remain, including technical limitations, clinical acceptance, and evidence gaps, the trajectory toward broader TDM adoption is clear and compelling.
As we advance into an era of increasingly sophisticated critical care medicine, TDM will play an essential role in ensuring that our most vulnerable patients receive optimal antibiotic therapy. The integration of emerging technologies, artificial intelligence, and personalized medicine approaches promises to further enhance the precision and effectiveness of TDM-guided therapy.
The future of antibiotic therapy in critical care lies not in one-size-fits-all dosing regimens but in individualized approaches that account for the unique pathophysiology of each patient. TDM provides the foundation for this precision medicine approach, offering clinicians the tools necessary to optimize antibiotic therapy in our most challenging patients.
References
Roberts JA, Abdul-Aziz MH, Lipman J, et al. Individualised antibiotic dosing for patients who are critically ill: challenges and potential solutions. Lancet Infect Dis. 2014;14(6):498-509.
Evans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021;47(11):1181-1247.
Abdul-Aziz MH, Lipman J, Akova M, et al. Is prolonged infusion of piperacillin/tazobactam and meropenem in critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient outcomes? An observation from the Defining Antibiotic Levels in Intensive care unit patients (DALI) cohort. J Antimicrob Chemother. 2016;71(1):196-207.
Baptista JP, Sousa E, Martins PJ, Pimentel JM. Augmented renal clearance in septic patients and implications for vancomycin optimisation. Int J Antimicrob Agents. 2012;39(5):420-423.
Joynt GM, Lipman J, Gomersall CD, et al. The pharmacokinetics of once-daily dosing of ceftriaxone in critically ill patients. J Antimicrob Chemother. 2001;47(4):421-429.
Udy AA, Varghese JM, Altukroni M, et al. Subtherapeutic initial β-lactam concentrations in select critically ill patients: association between augmented renal clearance and low trough drug concentrations. Chest. 2012;142(1):30-39.
Cook AM, Hatton-Kolpek J. Augmented renal clearance. Pharmacotherapy. 2019;39(3):346-354.
Vet NJ, Kleijer BC, Ista E, et al. Disposition of different antibiotic classes in critically ill children and adults. Clin Pharmacokinet. 2016;55(12):1551-1566.
Villa G, Zaragoza JJ, Sharma A, et al. Cytokine removal with high cut-off membrane: review of literature. Blood Purif. 2014;38(3-4):167-173.
Shekar K, Fraser JF, Smith MT, Roberts JA. Pharmacokinetic changes in patients receiving extracorporeal membrane oxygenation. J Crit Care. 2012;27(6):741.e9-18.
Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis. 1998;26(1):1-10.
Mouton JW, Dudley MN, Cars O, et al. Standardization of pharmacokinetic/pharmacodynamic (PK/PD) terminology for anti-infective drugs: an update. J Antimicrob Chemother. 2005;55(5):601-607.
Rybak MJ, Le J, Lodise TP, et al. Therapeutic monitoring of vancomycin for serious methicillin-resistant Staphylococcus aureus infections: a revised consensus guideline and review by the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, the Pediatric Infectious Diseases Society, and the Society of Infectious Diseases Pharmacists. Am J Health Syst Pharm. 2020;77(11):835-864.
Roberts JA, Paul SK, Akova M, et al. DALI: defining antibiotic levels in intensive care unit patients: are current β-lactam antibiotic doses sufficient for critically ill patients? Clin Infect Dis. 2014;58(8):1072-1083.
Carlier M, Stove V, Wallis SC, et al. Assays for therapeutic drug monitoring of β-lactam antibiotics: a structured review. Int J Antimicrob Agents. 2015;46(4):367-375.
Finch NA, Koeth L, El-Hawl B, et al. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry for simultaneous determination of multiple antibiotics in human serum: a systematic review. Ther Drug Monit. 2020;42(3):361-372.
Neely MN, Youn G, Jones B, et al. Are vancomycin trough concentrations adequate for optimal dosing? Antimicrob Agents Chemother. 2014;58(1):309-316.
Lodise TP, Rosenkranz SL, Finnemeyer M, et al. The emperor's new clothes: PRospective Observational Evaluation of the Association Between Initial VancomycIn Exposure and Failure Rates Among ADult HospitaliZed Patients With MRSA Bloodstream Infections (PROVIDE). Clin Infect Dis. 2020;70(8):1536-1545.
Abdul-Aziz MH, Sulaiman H, Mat-Nor MB, et al. Beta-lactam infusion in severe sepsis (BLISS): a prospective, two-centre, open-labelled randomised controlled trial of continuous versus intermittent beta-lactam infusion in critically ill patients with severe sepsis. Intensive Care Med. 2016;42(10):1535-1545.
Tam VH, McKinnon PS, Akins RL, et al. Pharmacokinetics and pharmacodynamics of cefepime in patients with various degrees of renal function. Antimicrob Agents Chemother. 2003;47(6):1853-1861.
Dhaese SAM, Farkas A, Colin P, et al. Population pharmacokinetics and evaluation of the predictive performance of pharmacokinetic models in critically ill patients receiving continuous infusion meropenem: a comparison of eight pharmacokinetic models. J Antimicrob Chemother. 2019;74(2):432-441.
Moore RD, Lietman PS, Smith CR. Clinical response to aminoglycoside therapy: importance of the ratio of peak concentration to minimal inhibitory concentration. J Infect Dis. 1987;155(1):93-99.
Freeman CD, Nicolau DP, Belliveau PP, Nightingale CH. Once-daily dosing of aminoglycosides: review and recommendations for clinical practice. J Antimicrob Chemother. 1997;39(6):677-686.
Kuti JL, Nicolau DP. Critical analysis of ceftolozane-tazobactam pharmacokinetics and clinical trials in healthy volunteers, volunteers with renal impairment, and patients with bacterial infections. Clin Pharmacokinet. 2018;57(4):433-465.
Cattaneo D, Gervasoni C, Cozzi V, et al. Therapeutic drug monitoring of linezolid in critically ill patients. Ther Drug Monit. 2016;38(4):466-471.
Bond CA, Raehl CL. Clinical pharmacy services, pharmacy staffing, and hospital mortality rates. Pharmacotherapy. 2007;27(4):481-493.
MacVane SH, Kuti JL, Nicolau DP. Clinical pharmacokinetics of antipseudomonal cephalosporins in the intensive care unit. Clin Pharmacokinet. 2014;53(7):585-595.
Darwich AS, Polasek TM, Aronson JK, et al. Model-informed precision dosing: background, requirements, validation, implementation, and forward trajectory of individualizing drug therapy. Annu Rev Pharmacol Toxicol. 2021;61:225-245.
Sendi P, Banderet F, Grandgirard D, Leib SL. Antibiotic brain penetration and efficacy in brain abscesses. Expert Rev Anti Infect Ther. 2009;7(9):1063-1069.
Sinkeler SJ, de Winter BC, Mulder AE, et al. Clinical pharmacy services in the intensive care unit: an opinion paper. Int J Clin Pharm. 2013;35(5):686-691.
Hughes DW, Lynch JP. Antimicrobial dosing in critically ill patients receiving continuous venovenous hemofiltration. Clin Infect Dis. 2005;40(8):1133-1144.
Sharma A, Jain N, Sareen R. Biosensors: their fundamentals, designs, types and most recent impactful applications: a review. J Biosens Bioelectron. 2018;9(1):1-9.
Wenzler E, Fraidenburg DR, Scardina T, Danziger LH. Inhaled antibiotics for Gram-negative respiratory infections. Clin Microbiol Rev. 2016;29(3):581-632.
Alffenaar JW, Dijkstra JA, Kettings I, et al. Personalized therapeutic drug monitoring of mycophenolic acid in transplant recipients: a randomized controlled trial. Clin Pharmacol Ther. 2021;110(1):150-157.
Tang BH, Wu YE, Kou C, et al. Population pharmacokinetics and dosing optimization of amoxicillin in neonates and young infants. Antimicrob Agents Chemother. 2019;63(2):e02336-18.
Swen JJ, Nijenhuis M, de Boer A, et al. Pharmacogenetics: from bench to byte—an update of guidelines. Clin Pharmacol Ther. 2011;89(5):662-673.
Wicha SG, Märtson AG, Nielsen EI, et al. From therapeutic drug monitoring to model-informed precision dosing for antibiotics. Clin Pharmacol Ther. 2021;109(4):928-941.
Cardone KE, Grabe DW, Meade LB, et al. An evaluation of the clinical and economic impact of a pharmacist-managed vancomycin dosing service versus conventional physician-managed dosing. Hosp Pharm. 2014;49(12):1142-1147.
Rybak MJ, Lomaestro BM, Rotschafer JC, et al. Vancomycin therapeutic guidelines: a summary of consensus recommendations from the infectious diseases Society of America, the American Society of Health-System Pharmacists, and the Society of Infectious Diseases Pharmacists. Clin Infect Dis. 2009;49(3):325-327.
De Waele JJ, Carrette S, Carlier M, et al. Therapeutic drug monitoring-based dose optimisation of piperacillin and meropenem: a randomised controlled trial. Intensive Care Med. 2014;40(3):380-387.
Pea F, Viale P, Cojutti P, et al. Therapeutic drug monitoring may improve safety outcomes of long-term treatment with linezolid in adult patients. J Antimicrob Chemother. 2012;67(8):2034-2042.
Carlier M, Stove V, Wallis SC, et al. Assays for therapeutic drug monitoring of β-lactam antibiotics: a structured review. Int J Antimicrob Agents. 2015;46(4):367-375.
Dorn C, Kratzer A, Liebchen U, et al. Impact of experimental design on the parameter estimation of population pharmacokinetic models for continuous infusion meropenem in critically ill patients. Eur J Drug Metab Pharmacokinet. 2018;43(3):313-321.
Roberts JA, Kirkpatrick CM, Roberts MS, et al. First-dose and steady-state population pharmacokinetics and pharmacodynamics of piperacillin by continuous or intermittent dosing in critically ill patients with sepsis. Int J Antimicrob Agents. 2010;35(2):156-163.
Sime FB, Roberts MS, Tiong IS, et al. Can therapeutic drug monitoring optimize exposure to piperacillin in febrile neutropenic patients with haematological malignancies? A randomized controlled trial. J Antimicrob Chemother. 2015;70(8):2369-2375.
Abdul-Aziz MH, Lipman J, Akova M, et al. Is prolonged infusion of piperacillin/tazobactam and meropenem in critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient outcomes? An observation from the Defining Antibiotic Levels in Intensive care unit patients (DALI) cohort. J Antimicrob Chemother. 2016;71(1):196-207.
Vardakas KZ, Voulgaris GL, Maliaros A, et al. Prolonged versus short-term intravenous infusion of antipseudomonal β-lactams for patients with sepsis: a systematic review and meta-analysis of randomised trials. Lancet Infect Dis. 2018;18(1):108-120.
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