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Abstract An estimated 70% of critically ill patients receive antibiotics, most frequently beta-lactams. The pharmacokinetic properties of these substances in this patient population are poorly predictable. Therapeutic drug monitoring (TDM) is helpful in making personalized decisions in this field, but its overall impact as a clinical decision-supporting tool is debated. We aimed to evaluate the clinical implications of adjusting beta-lactam dosages based on TDM in the critically ill population by performing a systematic review and meta-analysis of available investigations. Randomized controlled trials and observational studies were retrieved by searching three major databases. The intervention group received TDM-guided beta-lactam treatment, that is, at least one dose reconsideration based on the result of the measurement of drug concentrations, while TDM-unadjusted dosing was employed in the comparison group. The outcomes were evaluated using forest plots with random-effects modeling and subgroup analysis. Eight eligible studies were identified, including 1044 patients in total. TDM-guided beta-lactam treatment was associated with improved clinical cure from infection [odds ratio (OR): 2.22 (95% confidence interval (CI): 1.78–2.76)] and microbiological eradication [OR: 1.72 (CI: 1.05–2.80)], as well as a lower probability of treatment failure [OR: 0.47 (CI: 0.36–0.62)], but the heterogeneity of studies was remarkably high, especially in terms of mortality (70%). The risk of bias was moderate. While the TDM-guided administration of beta-lactams to critically ill patients has a favorable impact, standardized study designs and larger sample sizes are required for developing evidence-based protocols in this field.

Our aim was to compare the performance of complementary clinical laboratory approaches to monitoring exposure to apixaban and rivaroxaban, the most prescribed direct-acting oral anticoagulants (DOAC’s): an automated commercial anti-Xa chromogenic assay suitable for emergency and pre-surgery testing and a laboratory-developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) method employed for non-emergency analysis in plasma and in dried blood volumetric absorptive microsamples (VAMS) collectible by the patients in their homes. The full validation of the LC-MS/MS method was performed. Cross-validation of the methodologies was accomplished by processing 60 specimens collected for whole blood count and DOAC monitoring in a central clinical laboratory. For VAMS samples, dried plasma and whole blood calibrators were found to be suitable, and a cycle run for seven days could be implemented for rational and economic sample processing. The anti-Xa chromogrenic assay and the LC-MS/MS method delivered discordant plasma analyte concentrations. Moreover, the lack of agreement between plasma and VAMS concentrations was observed. Clinical laboratories must be aware of the differences between the performance of apixaban and rivaroxaban LC-MS/MS and anti-Xa assays. Hematocrit must always be measured along with VAMS samples to obtain accurate results.

Population pharmacokinetic (pop-PK) models constructed for model-informed precision dosing often have limited utility due to the low number of patients recruited. To augment such models, an approach is presented for generating fully artificial quasi-models which can be employed to make individual estimates of pharmacokinetic parameters. Based on 72 concentrations obtained in 12 patients, one- and two-compartment pop-PK models with or without creatinine clearance as a covariate were generated for piperacillin using the nonparametric adaptive grid algorithm. Thirty quasi-models were subsequently generated for each model type, and nonparametric maximum a posteriori probability Bayesian estimates were established for each patient. A significant difference in performance was found between one- and two-compartment models. Acceptable agreement was found between predicted and observed piperacillin concentrations, and between the estimates of the random-effect pharmacokinetic variables obtained using the so-called support points of the pop-PK models or the quasi-models as priors. The mean squared errors of the predictions made using the quasi-models were similar to, or even considerably lower than those obtained when employing the pop-PK models. Conclusion: fully artificial nonparametric quasi-models can efficiently augment pop-PK models containing few support points, to make individual pharmacokinetic estimates in the clinical setting.

Abstract Background Reduced cardiovascular risk in premenopausal women has been the focus of research in recent decades. Previous hypothesis-driven experiments have highlighted the role of sex hormones on distinct inflammatory responses, mitochondrial proteins, extracellular remodeling and estrogen-mediated cardioprotective signaling pathways related to post-ischemic recovery, which were associated with better cardiac functional outcomes in females. We aimed to investigate the early, sex-specific functional and proteomic changes following myocardial ischemia in an unbiased approach. Methods Ischemia was induced in male (M-Isch) and female (F-Isch) rats with sc. injection of isoproterenol (85 mg/kg) daily for 2 days, while controls (M-Co, F-Co) received sc. saline solution. At 48 h after the first injection pressure–volume analysis was carried out to assess left ventricular function. FFPE tissue slides were scanned and analyzed digitally, while myocardial proteins were quantified by liquid chromatography–tandem mass spectrometry (LC–MS/MS) using isobaric labeling. Concentrations of circulating steroid hormones were measured with LC–MS/MS. Feature selection (PLS and PLS-DA) was used to examine associations among functional, proteomic and hormonal datasets. Results Induction of ischemia resulted in 38% vs 17% mortality in M-Isch and F-Isch respectively. The extent of ischemic damage to surviving rats was comparable between the sexes. Systolic dysfunction was more pronounced in males, while females developed a more severe impairment of diastolic function. 2224 proteins were quantified, with 520 showing sex-specific differential regulation. Our analysis identified transcriptional, cytoskeletal, contractile, and mitochondrial proteins, molecular chaperones and the extracellular matrix as sources of disparity between the sexes. Bioinformatics highlighted possible associations of estrogens and their metabolites with early functional and proteomic alterations. Conclusions Our study has highlighted sex-specific alterations in systolic and diastolic function shortly after ischemia, and provided a comprehensive look at the underlying proteomic changes and the influence of estrogens and their metabolites. According to our bioinformatic analysis, inflammatory, mitochondrial, chaperone, cytoskeletal, extracellular and matricellular proteins are major sources of intersex disparity, and may be promising targets for early sex-specific pharmacologic interventions. Graphical Abstract

Orally administered, small-molecule anticancer drugs with tumor-specific cellular protein targets (OACD) have revolutionized oncological pharmacotherapy. Nevertheless, the differences in exposure to these drugs in the systemic circulation and extravascular fluid compartments have led to several cases of therapeutic failure, in addition to posing unknown risks of toxicity. The therapeutic drug monitoring (TDM) of OACDs in therapeutically relevant peripheral fluid compartments is therefore essential. In this work, the available knowledge regarding exposure to OACD concentrations in these fluid spaces is summarized. A review of the literature was conducted by searching Embase, PubMed, and Web of Science for clinical research articles and case reports published between 10 May 2001 and 31 August 2022. Results show that, to date, penetration into cerebrospinal fluid has been studied especially intensively, in addition to breast milk, leukocytes, peripheral blood mononuclear cells, peritoneal fluid, pleural fluid, saliva and semen. The typical clinical indications of peripheral fluid TDM of OACDs were (1) primary malignancy, (2) secondary malignancy, (3) mental disorder, and (4) the assessment of toxicity. Liquid chromatography–tandem mass spectrometry was most commonly applied for analysis. The TDM of OACDs in therapeutically relevant peripheral fluid spaces is often indispensable for efficient and safe treatments.

Abstract The inadequate adherence of patients whose hyperlipidemia is treated with atorvastatin (ATR) to medical instructions presents a serious health risk. Our aim was to develop a flexible approach based on therapeutic drug monitoring (TDM), nonparametric population pharmacokinetic modeling, and Monte Carlo simulation to differentiate adherent patients from partially and nonadherent individuals in a nonrandomized, unicentric, observational study. Sixty‐five subjects were enrolled. Nonparametric, mixed‐effect population pharmacokinetic models of the sums of atorvastatin and atorvastatin lactone concentrations (ATR+ATRL) and of the concentrations of the acid and lactone forms of ATR and its 2‐ and 4‐hydroxylated pharmacologically active metabolites (ATR+MET) were elaborated by including the TDM results obtained in 128 samples collected from thirty‐nine subjects. Monte Carlo simulation was performed based on the elaborated models to establish the probabilities of attaining a specific ATR+ATRL or ATR+MET concentration in the range of 0.002–10 nmol (mg dose)−1 L−1 at 1–24 h postdose by adherent, partially adherent, and nonadherent patients. The results of the simulations were processed to allow the estimation of the adherence of further 26 subjects who were phlebotomized at sampling times of 2–20 h postdose by calculating the probabilities of attaining the ATR+ATRL and ATR+MET concentrations measured in these subjects in adherent, partially adherent, and nonadherent individuals. The best predictive values of the estimates of adherence could be obtained with sampling at early sampling times. 61.54% and 38.46% of subjects in the adherence testing set were estimated to be fully and partially adherent, respectively, while in all cases the probability of nonadherence was extremely low. The evaluation of patient adherence to ATR therapy based on pharmacokinetic modeling and Monte Carlo simulation has important advantages over the collection of trough samples and the use of therapeutic ranges.

Severe community-acquired pneumonia (CAP) is a condition that frequently requires intensive care and, eventually, can cause to death. Piperacillin/tazobactam antibiotic therapy is employed as an empiric intravenous regimen, in many cases supplemented with intravenous bolus hydrocortisone treatment. The individual and condition-dependent pharmacokinetic properties of these drugs may lead to therapeutic failure. The impact of systemic inflammation, as well as of hydrocortisone on the altered pharmacokinetics of piperacillin is largely unknown. The protocol of a clinical study aimed at the characterization of the pharmacokinetics of piperacillin and tazobactam and its association with the concentrations of inflammatory markers and adrenal steroids during CAP therapy will be investigated in up to 40 critically ill patients. The serum concentrations of piperacillin and tazobactam, cortisol, cortisone, corticosterone and 11-deoxycortisol and interleukin-6 levels, as well as routine clinical chemistry and hematology parameters will be monitored from the beginning of treatment for up to five days. Nonparametric population pharmacokinetic modeling and Monte-Carlo simulations will be performed to make estimates of the pharmacokinetics of piperacillin and tazobactam and the probability of pharmacokinetic-pharmacodynamic target attainment. The observed individual characteristics and changes will be correlated with clinical and laboratory findings. The protocol of the observational study will be designed following the STROBE guideline.

Ibrutinib (IBR) is an oral anticancer medication that inhibits Bruton tyrosine kinase irreversibly. Due to the high risk of adverse effects and its pharmacokinetic variability, the safe and effective use of IBR is expected to be facilitated by precision dosing. Delivering suitable clinical laboratory information on IBR is a prerequisite of constructing fit-for-purpose population and individual pharmacokinetic models. The validation of a dedicated high-throughput method using liquid chromatography–mass spectrometry is presented for the simultaneous analysis of IBR and its pharmacologically active metabolite dihydrodiol ibrutinib (DIB) in human plasma. The 6 h benchtop stability of IBR, DIB, and the active moiety (IBR + DIB) was assessed in whole blood and in plasma to identify any risk of degradation before samples reach the laboratory. In addition, four regression algorithms were tested to determine the optimal assay error equations of IBR, DIB, and the active moiety, which are essential for the correct estimation of the error of their future nonparametric pharmacokinetic models. The noncompartmental pharmacokinetic properties of IBR and the active moiety were evaluated in three patients diagnosed with chronic lymphocytic leukemia to provide a proof of concept. The presented methodology allows clinical laboratories to efficiently support pharmacokinetics-based precision pharmacotherapy with IBR.

BACKGROUND:The clinical value of therapeutic drug monitoring can be increased most significantly by integrating assay results into clinical pharmacokinetic models for optimal dosing. The correct weighting in the modeling process is 1/variance, therefore, knowledge of the standard deviations (SD) of each measured concentration is important. Because bioanalytical methods are heteroscedastic, the concentration-SD relationship must be modeled using assay error equations (AEE). We describe a methodology of establishing AEE's for liquid chromatography-tandem mass spectrometry (LC-MS/MS) drug assays using carbamazepine, fluconazole, lamotrigine and levetiracetam as model analytes. METHODS:Following method validation, three independent experiments were conducted to develop AEE's using various least squares linear or nonlinear, and median-based linear regression techniques. SD's were determined from zero concentration to the high end of the assayed range. In each experiment, precision profiles of 6 ("small" sample sets) or 20 ("large" sample sets) out of 24 independent, spiked specimens were evaluated. Combinatorial calculations were performed to attain the most suitable regression approach. The final AEE's were developed by combining the SD's of the assay results, established in 24 specimens/spiking level and using all spiking levels, into a single precision profile. The effects of gross hyperbilirubinemia, hemolysis and lipemia as laboratory interferences were investigated. RESULTS:Precision profiles were best characterized by linear regression when 20 spiking levels, each having 24 specimens and obtained by performing 3 independent experiments, were combined. Theil's regression with the Siegel estimator was the most consistent and robust in providing acceptable agreement between measured and predicted SD's, including SD's below the lower limit of quantification. CONCLUSIONS:In the framework of precision pharmacotherapy, establishing the AEE of assayed drugs is the responsibility of the therapeutic drug monitoring service. This permits optimal dosages by providing the correct weighting factor of assay results in the development of population and individual pharmacokinetic models.

The antihyerlipidemic drug atorvastatin (ATR) is used worldwide as part of the strategy to prevent cardiovascular events. The high prevalence of patient nonadherence remains an important challenge which could be addressed efficiently by precision pharmacotherapy based on therapeutic drug monitoring (TDM). ATR is metabolized to pharmacologically active metabolites, and evidence shows that the sums of ATR acid and lactone form concentrations (ATR + ATRL), or of ATR and hydroxylated metabolites (ATR + MET) should be assayed. A method is presented for the analysis of these substances in serum. Method validation included the estimation of the quantitative relationship between the concentrations and the standard deviations (SD), which supports the optimal incorporation of TDM results into nonparametric pharmacokinetic models. The concentrations of the analytes were evaluated in human subjects receiving ATR. The method’s performance improved by taking the sums of acid and lactone concentrations into account. The concentration–SD relationship was linear, and we recommend applying Theil’s regression for estimating the assay error. All analytes could be detected by 2 h post dose in the samples of human subjects. The changes in metabolite/parent drug concentration ratios in time depended on the dose. The method is suitable for the TDM of ATR with a focus on precision pharmacotherapy.

The philosophy, practice, and clinical impact of therapeutic drug monitoring (TDM) has changed profoundly with the appearance of widely available and, in a technical sense, commonly applicable modeling, simulation, and dosing software tools in the past decade [...]