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Background To perform a systematic review with meta-analysis with the dual intent of assessing the impact of attaining aggressive vs. conservative beta-lactams PK/PD target on the clinical efficacy for treating Gram-negative infections in critical patients, and of identifying predictive factors of failure in attaining aggressive PK/PD targets. Methods Two authors independently searched PubMed-MEDLINE and Scopus database from inception to 23rd December 2023, to retrieve studies comparing the impact of attaining aggressive vs. conservative PK/PD targets on clinical efficacy of beta-lactams. Independent predictive factors of failure in attaining aggressive PK/PD targets were also assessed. Aggressive PK/PD target was considered a100%fT >4xMIC , and clinical cure rate was selected as primary outcome. Meta-analysis was performed by pooling odds ratios (ORs) extrapolated from studies providing adjustment for confounders using a random-effects model with inverse variance method. Results A total of 20,364 articles were screened, and 21 observational studies were included in the meta-analysis (N = 4833; 2193 aggressive vs. 2640 conservative PK/PD target). Attaining aggressive PK/PD target was significantly associated with higher clinical cure rate (OR 1.69; 95% CI 1.15–2.49) and lower risk of beta-lactam resistance development (OR 0.06; 95% CI 0.01–0.29). Male gender, body mass index > 30 kg/m 2 , augmented renal clearance and MIC above the clinical breakpoint emerged as significant independent predictors of failure in attaining aggressive PK/PD targets, whereas prolonged/continuous infusion administration of beta-lactams resulted as protective factor. The risk of bias was moderate in 19 studies and severe in the other 2. Conclusions Attaining aggressive beta-lactams PK/PD targets provided significant clinical benefits in critical patients. Our analysis could be useful to stratify patients at high-risk of failure in attaining aggressive PK/PD targets.

Background Therapeutic drug monitoring (TDM) may represent an invaluable tool for optimizing antimicrobial therapy in septic patients, but extensive use is burdened by barriers. The aim of this study was to assess the impact of a newly established expert clinical pharmacological advice (ECPA) program in improving the clinical usefulness of an already existing TDM program for emerging candidates in tailoring antimicrobial therapy among critically ill patients. Methods This retrospective observational study included an organizational phase (OP) and an assessment phase (AP). During the OP (January–June 2021), specific actions were organized by MD clinical pharmacologists together with bioanalytical experts, clinical engineers, and ICU clinicians. During the AP (July–December 2021), the impact of these actions in optimizing antimicrobial treatment of the critically ill patients was assessed. Four indicators of performance of the TDM-guided real-time ECPA program were identified [total TDM-guided ECPAs July–December 2021/total TDM results July–December 2020; total ECPA dosing adjustments/total delivered ECPAs both at first assessment and overall; and turnaround time (TAT) of ECPAs, defined as optimal (< 12 h), quasi-optimal (12–24 h), acceptable (24–48 h), suboptimal (> 48 h)]. Results The OP allowed to implement new organizational procedures, to create a dedicated pathway in the intranet system, to offer educational webinars on clinical pharmacology of antimicrobials, and to establish a multidisciplinary team at the morning bedside ICU meeting. In the AP, a total of 640 ECPAs were provided for optimizing 261 courses of antimicrobial therapy in 166 critically ill patients. ECPAs concerned mainly piperacillin–tazobactam (41.8%) and meropenem (24.9%), and also other antimicrobials had ≥ 10 ECPAs (ceftazidime, ciprofloxacin, fluconazole, ganciclovir, levofloxacin, and linezolid). Overall, the pre–post-increase in TDM activity was of 13.3-fold. TDM-guided dosing adjustments were recommended at first assessment in 61.7% of ECPAs (10.7% increases and 51.0% decreases), and overall in 45.0% of ECPAs (10.0% increases and 35.0% decreases). The overall median TAT was optimal (7.7 h) and that of each single agent was always optimal or quasi-optimal. Conclusions Multidisciplinary approach and timely expert interpretation of TDM results by MD Clinical Pharmacologists could represent cornerstones in improving the cost-effectiveness of an antimicrobial TDM program for emerging TDM candidates.

Background Darunavir is an anti-HIV protease inhibitor repurposed for SARS-CoV-2 treatment. Objective The aim of this study was to assess the population pharmacokinetics of darunavir in SARS-CoV-2 patients compared with HIV patients. Methods Two separate models were created by means of a nonlinear mixed-effect approach. The influence of clinical covariates on each basic model was tested and the association of significant covariates with darunavir parameters was assessed at multivariate regression and classification and regression tree (CART) analyses. Monte Carlo simulation assessed the influence of covariates on the darunavir concentration versus time profile. Results A one-compartment model well-described darunavir concentrations in both groups. In SARS-CoV-2 patients ( n  = 30), interleukin (IL)-6 and body surface area were covariates associated with darunavir oral clearance (CL/F) and volume of distribution ( V d ), respectively; no covariates were identified in HIV patients ( n  = 25). Darunavir CL/F was significantly lower in SARS-CoV-2 patients compared with HIV patients (4.1 vs. 10.3 L/h; p  < 0.001). CART analysis found that an IL-6 level of 18 pg/mL may split the SARS-CoV-2 population in patients with low versus high darunavir CL/F (mean ± standard deviation 3.47 ± 1.90 vs. 8.03 ± 3.24 L/h; proportion of reduction in error = 0.46). Median (interquartile range) darunavir CL/F was significantly lower in SARS-CoV-2 patients with IL-6 levels ≥ 18 pg/mL than in SARS-CoV-2 patients with IL-6 levels < 18 pg/mL or HIV patients (2.78 [2.16–4.47] vs. 7.24 [5.88–10.38] vs. 9.75 [8.45–13.79] L/h, respectively; p  < 0.0001). Increasing IL-6 levels affected darunavir concentration versus time simulated profiles. We hypothesized that increases in IL-6 levels associated with severe SARS-CoV-2 disease may downregulate the cytochrome P450 (CYP) 3A4-mediated metabolism of darunavir. Conclusions This is a proof-of-concept of SARS-CoV-2 disease–drug interactions, and may support the need for optimal dose selection of sensitive CYP3A4 substrates in severe SARS-CoV-2 patients.

Patients with Gram-negative bloodstream infections (GN-BSI) are classified as non-immunocompromised (n-IC) or immunocompromised (IC). However, immunosuppressive condition should not be considered univocally. To investigate epidemiological characteristics, management and outcome of GN-BSI in IC and non-IC patients. Retrospective single-center study of hospitalized patients with GN-BSI conducted over a 7-year period. Patients with GN-BSI were divided in: solid organ transplant (SOT) recipients, patients with hematologic malignancy (HM), patients with metastatic solid cancer (mSC), and non-major IC patients (nm-IC). 3544 patients analysed: 76.7% nm-IC, 6.5% SOT, 8.0% HM and 8.8% mSC. SOT and HM patients were younger (SOT: 56.6 ± 13.1 years; HM: 56.4 ± 14.5; nm-IC: 72.4 ± 16.1; mSC: 68.6 ± 13.1, p < 0.001) and had lower CCI value (SOT: 4.5 ± 2.4; HM: 4.1 ± 2.1; nm-IC: 5.5 ± 2.6; mSC: 9.7 ± 2.5, p < 0.001). Urinary tract infection was the most common source of BSI in nm-IC (nm-IC: 50.1%, HM:15%; SOT: 33.3%; mSC: 25.9%, p < 0.001), intra-abdominal infection was the more frequent source among SOT and mSC (SOT:42.3%; mSC: 49.3%, nm-IC: 27.8%, HM:29%; p < 0.001). Primary BSI was the first cause of GN-BSI in HM (HM: 62.1%; SOT: 18.5%; nm-IC: 17.2%; mSC: 10.6%, p < 0.001). The lowest rate of death was observed in SOT and the highest in mSC (SOT 8.2%; nm-IC 13.4%; HM 14.9%; mSC 19.9%, p < 0.001). Relapse rate was highest in SOT (SOT: 18.8%; HM: 11.8%; NMIC: 7.2%; aST: 7.1%, p < 0.001). Follow-up bloodcultures were associated with a lower mortality only among NMIC (HR = 0.317, 95% CI 0.178-0.563, p < 0.001) and aST (HR = 0.198, 95% CI 0.058-0.673, p = 0.010). The role of treatment duration on relapse was not evident in any group, conversely receiving at least 7 days of treatment was associated with a lower risk of 90-day mortality in SOT and HM patients. The characteristics and outcome of GN-BSI are peculiar between specific IC categories, therefore a personalized management should be implemented.

Background: Emerging data suggest that more aggressive beta-lactam PK/PD targets could minimize the occurrence of microbiological failure and/or resistance development. This study aims to assess whether a PK/PD target threshold of continuous infusion (CI) beta-lactams may be useful in preventing microbiological failure and/or resistance development in critically ill patients affected by documented Gram-negative infections. Methods: Patients admitted to intensive care units from December 2020 to July 2021 receiving continuous infusion beta-lactams for documented Gram-negative infections and having at least one therapeutic drug monitoring in the first 72 h of treatment were included. A receiver operating characteristic (ROC) curve analysis was performed using the ratio between steady-state concentration and minimum inhibitory concentration (Css/MIC) ratio as the test variable and occurrence of microbiological failure as the state variable. Area under the curve (AUC) and 95% confidence interval (CI) were calculated. Independent risk factors for the occurrence of microbiological failure were investigated using logistic regression. Results: Overall, 116 patients were included. Microbiological failure occurred in 26 cases (22.4%). A Css/MIC ratio ≤ 5 was identified as PK/PD target cut-off with sensitivity of 80.8% (CI 60.6–93.4%) and specificity of 90.5% (CI 74.2–94.4%), and with an AUC of 0.868 (95%CI 0.793–0.924; p < 0.001). At multivariate regression, independent predictors of microbiological failure were Css/MIC ratio ≤ 5 (odds ratio [OR] 34.54; 95%CI 7.45–160.11; p < 0.001) and Pseudomonas aeruginosa infection (OR 4.79; 95%CI 1.11–20.79; p = 0.036). Conclusions: Early targeting of CI beta-lactams at Css/MIC ratio > 5 during the treatment of documented Gram-negative infections may be helpful in preventing microbiological failure and/or resistance development in critically ill patients.

Isavuconazole is a newer broad-spectrum triazole approved for the treatment of invasive fungal disease. The objective of this study was to conduct a population pharmacokinetic and pharmacodynamic analysis of isavuconazole in a retrospective cohort of hospitalized patients. A nonlinear mixed-effect approach with Monte Carlo simulations was conducted to assess the probability of target attainment (PTA) of an area under the concentration–time curve (AUC24 h)/minimum inhibitory concentration (MIC) ratio of 33.4 (defined as efficacy threshold against A. fumigatus and A. flavus) associated with a maintenance dose (MD) of 100, 200 and 300 mg daily after loading. The cumulative fraction of response (CFR) against the EUCAST MIC distributions of A. fumigatus and A. flavus was calculated as well. The proportion of trough concentrations (Ctrough) exceeding a defined threshold of toxicity (>5.13 mg/L) was estimated. A total of 50 patients, with a median age of 61.5 years, provided 199 plasma isavuconazole concentrations. Invasive pulmonary aspergillosis was the prevalent type of infection and accounted for 80% (40/50) of cases. No clinical covariates were retained by the model. With the standard MD of 200 mg daily, CFRs were always ≥90% during the first two months of treatment. The risk of Ctrough < 1.0 mg/L was around 1%, and that of Ctrough > 5.13 mg/L was 27.7 and 39.2% at 28 and 60 days, respectively, due to isavuconazole accumulation over time. Our findings suggest that TDM for isavuconazole should not be considered as mandatory as for the other mold-active azoles voriconazole and posaconazole.

Dalbavancin (DBV) is a long-acting antistaphylococcal lypoglycopeptide that is being increasingly used for long-term treatment of a wide range of subacute and/or chronic infections, mainly osteo-articular infections (OAI). Population pharmacokinetic studies showed that two 1500 mg doses 1 week apart can ensure effective treatment for several weeks. In this scenario, therapeutic drug monitoring (TDM) can be a helpful tool for providing clinicians with real-time feedback on the duration of optimal treatment by measuring drug concentrations over time in each single patient. The aim of this study was to develop and validate a fast and simple analytical method based on the Liquid Chromatography-Isotope Dilution Tandem Mass Spectrometry (ITD LC-MS/MS) technique for measuring DBV concentrations in human plasma microsamples. It will allow an innovative, very convenient and minimally invasive way of sampling. Analysis was performed by simple single-step sample preparation and very short instrumental run time (4 min). Analytical performance met all criteria in terms of specificity, sensitivity, linearity, precision, accuracy, matrix effect, extraction recovery, limit of quantification, dilution integrity and stability under different conditions set by the European Medicines Agency (EMA) for drug quantification by means of bioanalytical methods. The method was successfully applied for measuring DBV concentrations (range = 2.0–77.0 mg/L) in a cohort of patients receiving long-term DBV treatment of subacute and/or chronic infections.

This study investigates the use of Neural Ordinary Differential Equations (NODEs) as an alternative to traditional compartmental models and Nonlinear Mixed-Effects (NLME) models for drug concentration prediction in pharmacokinetics. Unlike standard models that rely on strong assumptions and often struggle with high-dimensional covariate relationships, NODEs offer a data-driven approach, learning differential equations directly from data while integrating covariates. To evaluate their performance, NODEs were applied to a real-world Dalbavancin pharmacokinetic dataset comprising 218 patients and compared against a two-compartment model and an NLME within a cross-validation framework, which ensures an evaluation of robustness. Given the challenge of limited data availability, a data augmentation strategy was employed to pre-train NODEs. Their predictive performance was assessed both with and without covariates, while model explainability was analyzed using Shapley additive explanations (SHAP) values. Results show that, in the absence of covariates, NODEs performed comparably to state-of-the-art NLME models. However, when covariates were incorporated, NODEs demonstrated superior predictive accuracy. SHAP analyses further revealed how NODEs leverage covariates in their predictions. These results establish NODEs as a promising alternative for pharmacokinetic modeling, particularly in capturing complex covariate interactions, even when dealing with sparse and small datasets, thus paving the way for improved drug concentration predictions and personalized treatment strategies in precision medicine.

Cefiderocol (C) is a parenteral siderophore cephalosporin with relevant inter-individual pharmacokinetic variability among critically ill patients, which may potentially affect effective drug exposure. Therapeutic drug monitoring (TDM) may concur in improving the real-time management of C therapy in clinics. In this study, we developed and validated a fast and sensitive Liquid Chromatography-Isotope Dilution Tandem Mass Spectrometry (LC-ITD-MS/MS) method for measuring C in human plasma microsamples, as small as 3 microliters. Analysis was preceded by a user-friendly pre-analytical single-step and was performed by means of a very fast chromatographic run of 4 min, followed by positive electrospray ionization and detection on a high sensitivity triple quadrupole tandem mass spectrometer operated in multiple reaction monitoring mode. The straightforward analytical procedure was successfully validated, based on the European Medicines Agency (EMA) guidelines, in terms of specificity, sensitivity, linearity, precision, accuracy, matrix effect, extraction recovery, limit of quantification, and stability. The novel method was successfully applied to TDM of C in more than 50 cases of critically carbapenem-resistant Gram-negative bacterial infections and enabled us to optimize antibiotic therapy.

A population pharmacokinetic analysis of dalbavancin was conducted in patients with different infection sites. Non-linear mixed effect modeling was used for pharmacokinetic analysis and covariate evaluation. Monte Carlo simulations assessed the probability of target attainment (PTA) of total dalbavancin concentration ≥ 8.04 mg/L over time (associated with ≥90% probability of optimal pharmacodynamic target attainment of fAUC24h/MIC > 111.1 against S. aureus) associated with a single or double dosage, one week apart, of 1000 or 1500 mg in patients with different classes of renal function. Sixty-nine patients with 289 concentrations were included. Most of them (53/69, 76.8%) had bone and joint infections. A two-compartment model adequately fitted dalbavancin concentration–time data. Creatinine clearance (CLCR) was the only covariate associated with dalbavancin clearance. Monte Carlo simulations showed that, in patients with severe renal dysfunction, the 1000 mg single or double one week apart dosage may ensure optimal PTAs of 2 and 5 weeks, respectively. In patients with preserved renal function, the 1500 mg single or double one-week apart dosage may ensure optimal PTAs of 2 and 4 to 6 weeks, respectively. Therapeutic drug monitoring should be considered mandatory for managing inter-individual variability and for supporting clinicians in long-term treatments of subacute and chronic infections.