Model-Based Prediction of Irinotecan-Induced Grade 4 Neutropenia in Cancer Patients: Influence of Incorporating Germline Genetic Factors in the Model.

Neutropenia is the major dose-limiting toxicity of irinotecan-based therapy. The objective of this study was to assess whether inclusion of germline genetic variants into a population pharmacokinetic/pharmacodynamic model can improve prediction of irinotecan-induced grade 4 neutropenia and identify novel variants of clinical value. A semimechanistic population pharmacokinetic/pharmacodynamic model was used to predict neutrophil response over time in 197 patients receiving irinotecan. Covariate analysis was performed for demographic/clinical factors and 4,781 genetic variants in 84 drug response- and toxicity-related genes to identify covariates associated with neutrophil response. We evaluated the predictive value of the model for grade 4 neutropenia reflecting different clinical scenarios of available data on identified demographic/clinical covariates, baseline and post-treatment absolute neutrophil counts (ANCs), individual pharmacokinetics, and germline genetic variation. Adding 8 genetic identified covariates (rs10929302 (UGT1A1), rs1042482 (DPYD), rs2859101 (HLA-DQB3), rs61754806 (NR3C1), rs9266271 (HLA-B), rs7294 (VKORC1), rs1051713 (ALOX5), and ABCB1 rare variant burden) to a model using only baseline ANCs improved prediction of irinotecan-induced grade 4 neutropenia from area under the receiver operating characteristic curve (AUC-ROC) of 50-64% (95% confidence interval (CI), 54-74%). Individual pharmacokinetics further improved the prediction to 74% (95% CI, 64-84%). When weekly ANC was available, the identified covariates and individual pharmacokinetics yielded no additional contribution to the prediction. The model including only ANCs at baseline and at week 1 achieved an AUC-ROC of 78% (95% CI, 69-88%). Germline DNA genetic variants may contribute to the prediction of irinotecan-induced grade 4 neutropenia when incorporated into a population pharmacokinetic/pharmacodynamic model. This approach is generalizable to drugs that induce neutropenia and ultimately allows for personalized intervention to enhance patient safety.

Distinguishing Inducible and Non-Inducible Resistance to Colistin in Pseudomonas aeruginosa by Quantitative and Systems Pharmacology Modeling at Low and Standard Inocula.

Colistin is a polymyxin and peptide antibiotic that can yield rapid bacterial killing, but also leads to resistance emergence. We aimed to develop a novel experimental and Quantitative and Systems Pharmacology approach to distinguish between inducible and non-inducible resistance. Viable count profiles for the total and less susceptible populations of Pseudomonas aeruginosa ATCC 27853 from static and dynamic in vitro infection models were simultaneously modeled. We studied low and normal initial inocula to distinguish between inducible and non-inducible resistance. A novel cutoff filter approach allowed us to describe the eradication and inter-conversion of bacterial populations. At all inocula, 4.84 mg/L of colistin (sulfate) yielded ≥4 log10 killing, followed by >4 log10 regrowth. A pre-existing, less susceptible population was present at standard but not at low inocula. Formation of a non-pre-existing, less susceptible population was most pronounced at intermediate colistin (sulfate) concentrations (0.9 to 5 mg/L). Both less susceptible populations inter-converted with the susceptible population. Simultaneously modeling of the total and less susceptible populations at low and standard inocula enabled us to identify the de novo formation of an inducible, less susceptible population. Inducible resistance at intermediate colistin concentrations highlights the importance of rapidly achieving efficacious polymyxin concentrations by front-loaded dosage regimens.

Global Brassicaceae phylogeny based on filtering of 1,000-gene dataset.

The mustard family (Brassicaceae) is a scientifically and economically important family, containing the model plant Arabidopsis thaliana and numerous crop species that feed billions worldwide. Despite its relevance, most phylogenetic trees of the family are incompletely sampled and often contain poorly supported branches. Here, we present the most complete Brassicaceae genus-level family phylogenies to date (Brassicaceae Tree of Life or BrassiToL) based on nuclear (1,081 genes, 319 of the 349 genera; 57 of the 58 tribes) and plastome (60 genes, 265 genera; all tribes) data. We found cytonuclear discordance between the two, which is likely a result of rampant hybridization among closely and more distantly related lineages. To evaluate the impact of such hybridization on the nuclear phylogeny reconstruction, we performed five different gene sampling routines, which increasingly removed putatively paralog genes. Our cleaned subset of 297 genes revealed high support for the tribes, whereas support for the main lineages (supertribes) was moderate. Calibration based on the 20 most clock-like nuclear genes suggests a late Eocene to late Oligocene origin of the family. Finally, our results strongly support a recently published new family classification, dividing the family into two subfamilies (one with five supertribes), together representing 58 tribes. This includes five recently described or re-established tribes, including Arabidopsideae, a monogeneric tribe accommodating Arabidopsis without any close relatives. With a worldwide community of thousands of researchers working on Brassicaceae and its diverse members, our new genus-level family phylogeny will be an indispensable tool for studies on biodiversity and plant biology.

Model-Based Prediction of Irinotecan-Induced Grade 4 Neutropenia in Advanced Cancer Patients: Influence of Demographic and Clinical Factors.

Severe neutropenia is the major dose-liming toxicity of irinotecan-based chemotherapy. The objective was to assess to what extent a population pharmacokinetic/pharmacodynamic model including patient-specific demographic/clinical characteristics, individual pharmacokinetics, and absolute neutrophil counts (ANCs) can predict irinotecan-induced grade 4 neutropenia. A semimechanistic population pharmacokinetic/pharmacodynamic model was developed to describe neutrophil response over time in 197 patients with cancer receiving irinotecan. For covariate analysis, sex, race, age, pretreatment total bilirubin, and body surface area were evaluated to identify significant covariates on system-related parameters (mean transit time (MTT) and É£) and sensitivity to neutropenia effects of irinotecan and SN-38 (SLOPE). The model-based simulation was performed to assess the contribution of the identified covariates, individual pharmacokinetics, and baseline ANC alone or with incremental addition of weekly ANC up to 3 weeks on predicting irinotecan-induced grade 4 neutropenia. The time course of neutrophil response was described using the model assuming that irinotecan and SN-38 have toxic effects on bone marrow proliferating cells. Sex and pretreatment total bilirubin explained 10.5% of interindividual variability in MTT. No covariates were identified for SLOPE and γ. Incorporating sex and pretreatment total bilirubin (area under the receiver operating characteristic curve (AUC-ROC): 50%, 95% CI 50-50%) or with the addition of individual pharmacokinetics (AUC-ROC: 62%, 95% CI 53-71%) in the model did not result in accurate prediction of grade 4 neutropenia. However, incorporating ANC only at baseline and week 1 in the model achieved a good prediction (AUC-ROC: 78%, 95% CI 69-88%). These results demonstrate the potential applicability of a model-based approach to predict irinotecan-induced neutropenia, which ultimately allows for personalized intervention to maximize treatment outcomes.

Integration of DNA sequencing with population pharmacokinetics to improve the prediction of irinotecan exposure in cancer patients.

BACKGROUND: Irinotecan (CPT-11) is an anticancer agent widely used to treat adult solid tumours. Large interindividual variability in the clearance of irinotecan and SN-38, its active and toxic metabolite, results in highly unpredictable toxicity. METHODS: In 217 cancer patients treated with intravenous irinotecan single agent or in combination, germline DNA was used to interrogate the variation in 84 genes by next-generation sequencing. A stepwise analytical framework including a population pharmacokinetic model with SNP- and gene-based testing was used to identify demographic/clinical/genetic factors that influence the clearance of irinotecan and SN-38. RESULTS: Irinotecan clearance was influenced by rs4149057 in SLCO1B1, body surface area, and co-administration of 5-fluorouracil/leucovorin/bevacizumab. SN-38 clearance was influenced by rs887829 in UGT1A1, pre-treatment total bilirubin, and EGFR rare variant burden. Within each UGT1A1 genotype group, elevated pre-treatment total bilirubin and/or presence of at least one rare variant in EGFR resulted in significantly lower SN-38 clearance. The model reduced the interindividual variability in irinotecan clearance from 38 to 34% and SN-38 clearance from 49 to 32%. CONCLUSIONS: This new model significantly reduced the interindividual variability in the clearance of irinotecan and SN-38. New genetic factors of variability in clearance have been identified.

Polymyxins for the treatment of lower respiratory tract infections: lessons learned from the integration of clinical pharmacokinetic studies and clinical outcomes.

The global rise in nosocomial pneumonia caused by multidrug-resistant (MDR) Gram-negative pathogens and the increasingly limited antibiotic treatment options are growing threats to modern medicine. As a result, older antibiotics such as polymyxins are being used as last-resort drugs for MDR nosocomial pneumonia. Polymyxins are bactericidal against most aerobic Gram-negative bacilli. High-dose intravenous (IV) adminsitration of polymyxins, however, results in subtherapeutic concentrations at the site of infection making treatment challenging. Alternative forms of polymyxin delivery have been considered in order to better achieve the necessary concentrations at the site of infection. Several studies have evaluated the effectiveness of aerosolised polymyxins in patients with nosocomial pneumonia caused by MDR Gram-negative pathogens such as Pseudomonas aeruginosa, Acinetobacter baumannii and Klebsiella pneumoniae. Here we evaluated the pharmacokinetic data supporting the use of inhaled polymyxins in nosocomial pneumonia and provide insight into the limitations and challenges that future studies should address. We have also reviewed the literature published between 2006 and 2020 on the use of aerosolised polymyxins for the treatment of nosocomial pneumonia, including ventilator-associated pneumonia, in patients without cystic fibrosis to evaluate their safety and efficacy as monotherapy or as an adjunct to IV antimicrobials. This review highlights the need for well-designed multicentre studies with standardised methodologies to further evaluate the effectiveness of inhaled polymyxins and to provide reliable pharmacokinetic/pharmacodynamic data in order to redefine appropriate dosing strategies.

Optimal Sampling Strategies for Irinotecan (CPT-11) and its Active Metabolite (SN-38) in Cancer Patients.

Irinotecan (CPT-11) is an anticancer agent widely used in the treatment of a variety of adult solid tumors. The objective of this study was to develop an optimal sampling strategy model that accurately estimates pharmacokinetic parameters of CPT-11 and its active metabolite, SN-38. This study included 221 patients with advanced solid tumors or lymphoma receiving CPT-11 single or combination therapy with 5-fluorouracil (5-FU)/leucovorin (LV) (FOLFIRI) plus bevacizumab from 4 separate clinical trials. Population pharmacokinetic analysis of CPT-11 and SN-38 was performed by non-linear mixed effects modeling. The optimal sampling strategy model was developed using D-optimality with expected distribution approach. The pharmacokinetic profiles of CPT-11 and SN-38 were best described by a 3- and 2-compartment model, respectively, with first-order elimination. Body surface area and co-administration with 5-FU/LV plus bevacizumab were significant covariates (p < 0.01) for volumes of the central compartment of CPT-11 and SN-38, and clearance of CPT-11. Pre-treatment total bilirubin and co-administration with 5-FU/LV and bevacizumab were significant covariates (p < 0.01) for clearance of SN-38. Accurate and precise predictive performance (r2 > 0.99, -2 < bias (%ME) < 0, precision (% RMSE) < 12) of both CPT-11 and SN-38 was achieved using: (i) 6 fixed sampling times collected at 1.5, 3.5, 4, 5.75, 22, 23.5 hours post-infusion; or (ii) 1 fixed time and 2 sampling windows collected at 1.5, [3-5.75], [22-23.5] hours post-infusion. The present study demonstrates that an optimal sampling design with three blood samples achieves accurate and precise pharmacokinetic parameter estimates for both CPT-11 and SN-38.

Synergistic Combination of Polymyxin B and Enrofloxacin Induced Metabolic Perturbations in Extensive Drug-Resistant Pseudomonas aeruginosa.

Polymyxins are used as a last-resort class of antibiotics against multidrug-resistant (MDR) Gram-negative Pseudomonas aeruginosa. As polymyxin monotherapy is associated with potential development of resistance, combination therapy is highly recommended. This study investigated the mechanism underlying the synergistic killing of polymyxin B and enrofloxacin against extensive drug-resistant (XDR) P. aeruginosa. An XDR isolate P. aeruginosa 12196 was treated with clinically relevant concentrations of polymyxin B (2 mg/L) and enrofloxacin (1 mg/L) alone or in combination. Metabolome profiles were investigated from bacterial samples collected at 1-and 4-h posttreatment using liquid chromatography with tandem mass spectrometry (LC-MS/MS), and data were analyzed using univariate and multivariate statistics. Significantly perturbed metabolites (q < 0.05, fold change ≥ 2) were subjected to pathway analysis. The synergistic killing by polymyxin B-enrofloxacin combination was initially driven by polymyxin B as indicated by the perturbation of lipid metabolites at 1 h in particular. The killing was subsequently driven by enrofloxacin via the inhibition of DNA replication, resulting in the accumulation of nucleotides at 4 h. Furthermore, the combination uniquely altered levels of metabolites in energy metabolism and cell envelope biogenesis. Most importantly, the combination significantly minimized polymyxin resistance via the inhibition of lipid A modification pathway, which was most evident at 4 h. This is the first study to elucidate the synergistic mechanism of polymyxin B-enrofloxacin combination against XDR P. aeruginosa. The metabolomics approach taken in this study highlights its power to elucidate the mechanism of synergistic killing by antibiotic combinations at the systems level.

Clinical Pharmacokinetics, Pharmacodynamics and Toxicodynamics of Polymyxins: Implications for Therapeutic Use.

The availability of sensitive, accurate and specific analytical methods for the measurement of polymyxins in biological fluids has enabled an understanding of the pharmacokinetics of these important antibiotics in healthy humans and patients. Colistin is administered as its inactive prodrug colistin methanesulfonate (CMS) and has especially complex pharmacokinetics. CMS undergoes conversion in vivo to the active entity colistin, but the rate of conversion varies from brand to brand and possibly from batch to batch. The extent of conversion is generally quite low and depends on the relative magnitudes of the conversion clearance and other clearance pathways for CMS of which renal excretion is a major component. Formed colistin in the systemic circulation undergoes very extensive tubular reabsorption; the same mechanism operates for polymyxin B which is administered in its active form. The extensive renal tubular reabsorption undoubtedly contributes to the propensity for the polymyxins to cause nephrotoxicity. While there are some aspects of pharmacokinetic behaviour that are similar between the two clinically used polymyxins, there are also substantial differences. In this chapter, the pharmacokinetics of colistin, administered as CMS, and polymyxin B are reviewed, and the therapeutic implications are discussed.

Pharmacokinetic/Pharmacodynamic Evaluation of Solithromycin against Streptococcus pneumoniae Using Data from a Neutropenic Murine Lung Infection Model.

Solithromycin (CEM-101) is a novel fluoroketolide antimicrobial agent with activity against typical and atypical pathogens associated with community-acquired bacterial pneumonia. Using a neutropenic murine lung infection model, the objectives of this study were to identify the pharmacokinetic/pharmacodynamic (PK/PD) index most closely associated with efficacy and the magnitude of such indices associated with solithromycin efficacy against Streptococcus pneumoniae Plasma and epithelial lining fluid (ELF) samples for pharmacokinetics (PK) were collected serially over 24 hours from healthy mice administered single doses of solithromycin (0.625 to 40 mg/kg). Neutropenic CD-1 mice infected with 108 CFUs of one of five S. pneumoniae isolates were administered solithromycin (0.156 to 160 mg/kg/day) via oral gavage. Doses were administered in a fractionated manner for mice infected with one isolate, while mice infected with the remaining four isolates received solithromycin as either a regimen every 6 hours or every 12 hours. A three-compartment model best described solithromycin PK in the plasma and ELF (r2 = 0.935 and 0.831, respectively). The ratio of total-drug ELF to free-drug plasma area under the concentration-time curve (AUC) from time 0 to 24 hours was 2.7. Free-drug plasma and total-drug ELF AUC to minimum inhibitory concentration ratios (AUC/MIC ratios) were most predictive of efficacy (r2 = 0.851 and 0.850, respectively). The magnitude of free-drug plasma/total-drug ELF AUC/MIC ratios associated with net bacterial stasis and a 1- and 2-log10 CFU reduction from baseline was 1.65/1.26, 6.31/15.1, and 12.8/59.8, respectively. These data provided dose selection support for solithromycin for clinical trials in patients with community-acquired bacterial pneumonia.

International Consensus Guidelines for the Optimal Use of the Polymyxins: Endorsed by the American College of Clinical Pharmacy (ACCP), European Society of Clinical Microbiology and Infectious Diseases (ESCMID), Infectious Diseases Society of America (IDSA), International Society for Anti-infective Pharmacology (ISAP), Society of Critical Care Medicine (SCCM), and Society of Infectious Diseases Pharmacists (SIDP).

The polymyxin antibiotics colistin (polymyxin E) and polymyxin B became available in the 1950s and thus did not undergo contemporary drug development procedures. Their clinical use has recently resurged, assuming an important role as salvage therapy for otherwise untreatable gram-negative infections. Since their reintroduction into the clinic, significant confusion remains due to the existence of several different conventions used to describe doses of the polymyxins, differences in their formulations, outdated product information, and uncertainties about susceptibility testing that has led to lack of clarity on how to optimally utilize and dose colistin and polymyxin B. We report consensus therapeutic guidelines for agent selection and dosing of the polymyxin antibiotics for optimal use in adult patients, as endorsed by the American College of Clinical Pharmacy (ACCP), Infectious Diseases Society of America (IDSA), International Society of Anti-Infective Pharmacology (ISAP), Society for Critical Care Medicine (SCCM), and Society of Infectious Diseases Pharmacists (SIDP). The European Society for Clinical Microbiology and Infectious Diseases (ESCMID) endorses this document as a consensus statement. The overall conclusions in the document are endorsed by the European Committee on Antimicrobial Susceptibility Testing (EUCAST). We established a diverse international expert panel to make therapeutic recommendations regarding the pharmacokinetic and pharmacodynamic properties of the drugs and pharmacokinetic targets, polymyxin agent selection, dosing, dosage adjustment and monitoring of colistin and polymyxin B, use of polymyxin-based combination therapy, intrathecal therapy, inhalation therapy, toxicity, and prevention of renal failure. The treatment guidelines provide the first ever consensus recommendations for colistin and polymyxin B therapy that are intended to guide optimal clinical use.

Predicting Efavirenz Concentrations in the Brain Tissue of HIV-Infected Individuals and Exploring their Relationship to Neurocognitive Impairment.

Sparse data exist on the penetration of antiretrovirals into brain tissue. In this work, we present a framework to use efavirenz (EFV) pharmacokinetic (PK) data in plasma, cerebrospinal fluid (CSF), and brain tissue of eight rhesus macaques to predict brain tissue concentrations in HIV-infected individuals. We then perform exposure-response analysis with the model-predicted EFV area under the concentration-time curve (AUC) and neurocognitive scores collected from a group of 24 HIV-infected participants. Adult rhesus macaques were dosed daily with 200 mg EFV (as part of a four-drug regimen) for 10 days. Plasma was collected at 8 time points over 10 days and at necropsy, whereas CSF and brain tissue were collected at necropsy. In the clinical study, data were obtained from one paired plasma and CSF sample of participants prescribed EFV, and neuropsychological test evaluations were administered across 15 domains. PK modeling was performed using ADAPT version 5.0 Biomedical Simulation Resource, Los Angeles, CA) with the iterative two-stage estimation method. An eight-compartment model best described EFV distribution across the plasma, CSF, and brain tissue of rhesus macaques and humans. Model-predicted median brain tissue concentrations in humans were 31 and 8,000 ng/mL, respectively. Model-predicted brain tissue AUC was highly correlated with plasma AUC (γ = 0.99, P < 0.001) but not CSF AUC (γ = 0.34, P = 0.1) and did not show any relationship with neurocognitive scores (γ < 0.05, P > 0.05). This analysis provides an approach to estimate PK the brain tissue in order to perform PK/pharmacodynamic analyses at the target site.

Novel Polymyxin Combination with the Antiretroviral Zidovudine Exerts Synergistic Killing against NDM-Producing Multidrug-Resistant Klebsiella pneumoniae.

Polymyxins are used as a last-line therapy against multidrug-resistant (MDR) New Delhi metallo-ß-lactamase (NDM)-producing Klebsiella pneumoniae However, polymyxin resistance can emerge with monotherapy; therefore, novel strategies are urgently needed to minimize the resistance and maintain their clinical utility. This study aimed to investigate the pharmacodynamics of polymyxin B in combination with the antiretroviral drug zidovudine against K. pneumoniae Three isolates were evaluated in static time-kill studies (0 to 64 mg/liter) over 48 h. An in vitro one-compartment pharmacokinetic/pharmacodynamic (PK/PD) model (IVM) was used to simulate humanized dosage regimens of polymyxin B (4 mg/liter as continuous infusion) and zidovudine (as bolus dose thrice daily to achieve maximum concentration of drug in broth [Cmax] of 6 mg/liter) against K. pneumoniae BM1 over 72 h. The antimicrobial synergy of the combination was further evaluated in a murine thigh infection model against K. pneumoniae 02. In the static time-kill studies, polymyxin B monotherapy produced rapid and extensive killing against all three isolates followed by extensive regrowth, whereas zidovudine produced modest killing followed by significant regrowth at 24 h. Polymyxin B in combination with zidovudine significantly enhanced the antimicrobial activity (≥4 log10 CFU/ml) and minimized bacterial regrowth. In the IVM, the combination was synergistic and the total bacterial loads were below the limit of detection for up to 72 h. In the murine thigh infection model, the bacterial burden at 24 h in the combination group was ≥3 log10 CFU/thigh lower than each monotherapy against K. pneumoniae 02. Overall, the polymyxin B-zidovudine combination demonstrates superior antimicrobial efficacy and minimized emergence of resistance to polymyxins.

Definition and Validation of a Novel Metric of Erythropoiesis-Stimulating Agent Response in Hemodialysis Patients.

Erythropoiesis-stimulating agents (eg, epoetin alfa) are the primary treatment for anemia in patients with end-stage renal disease. Hemoglobin variability in and out of a narrow target range is common and associated with higher morbidity and mortality risk. More robust erythropoiesis-stimulating agent response metrics are needed to define optimal dosing and their association with clinical outcomes. In this cross-sectional, single-center, retrospective study, 49 patients with end-stage renal disease on hemodialysis were followed over 12 months. To quantify hemoglobin deviations outside the target range (10-12 g/dL), the area under the curve of hemoglobin versus time over a 12-month period (AUC-HGB) was calculated using the trapezoidal rule. Patients were categorized into 4 responder groups based on AUC-HGB quartiles. Comparative analyses of demographic and clinical characteristics between responder groups were performed. Correlations between AUC-HGB, erythropoietin resistance index, and time within therapeutic range were calculated. There were no significant differences in laboratory and dialysis parameters between responder groups except hemoglobin concentration and epoetin alfa dose. There was a negative correlation between AUC-HGB and time within therapeutic range (r = -.92; P < .001) and hemoglobin concentration (r = -.85; P < .01), indicating internal validity of the metric. There was a positive correlation between AUC-HGB and erythropoietin resistance index (r = .70; P < .001) indicating external validity. The poor response group received a higher median epoetin alfa dose (160 U/kg/week) compared to the excellent response group (68.8 U/kg/week; P < .001) with a similar number of dose changes between the groups. AUC-HGB is a valid marker of epoetin alfa response and should be considered in future analyses of larger populations.

Macroevolutionary dynamics of nectar spurs, a key evolutionary innovation.

Floral nectar spurs are widely considered a key innovation promoting diversification in angiosperms by means of pollinator shifts. We investigated the macroevolutionary dynamics of nectar spurs in the tribe Antirrhineae (Plantaginaceae), which contains 29 genera and 300-400 species (70-80% spurred). The effect of nectar spurs on diversification was tested, with special focus on Linaria, the genus with the highest number of species. We generated the most comprehensive phylogeny of Antirrhineae to date and reconstructed the evolution of nectar spurs. Diversification rate heterogeneity was investigated using trait-dependent and trait-independent methods, and accounting for taxonomic uncertainty. The association between changes in spur length and speciation was examined within Linaria using model testing and ancestral state reconstructions. We inferred four independent acquisitions of nectar spurs. Diversification analyses revealed that nectar spurs are loosely associated with increased diversification rates. Detected rate shifts were delayed by 5-15 Myr with respect to the acquisition of the trait. Active evolution of spur length, fitting a speciational model, was inferred in Linaria, which is consistent with a scenario of pollinator shifts driving diversification. Nectar spurs played a role in diversification of the Antirrhineae, but diversification dynamics can only be fully explained by the complex interaction of multiple biotic and abiotic factors.

Challenges and Solutions for Future Pharmacy Practice in the Era of Precision Medicine.

As precision medicine research and its clinical applications continue to advance, it is critical for pharmacists to be involved in these developments to deliver optimal, tailored drug therapies for patients. To ensure pharmacists remain leaders in the field, the annual Pharmaceutical Sciences Conference convened by the University of North Carolina at Chapel Hill Eshelman School of Pharmacy focused on the role of pharmacy within precision medicine. This is a summary of the conference, highlighting the major challenges and solutions that will help advance individualized pharmacological methods within practice and research.

Population Pharmacokinetic Analyses for Ertapenem in Subjects with a Wide Range of Body Sizes.

Despite a number of studies reporting that ertapenem pharmacokinetic parameters differ considerably in obese patients from those in healthy volunteers, functions describing the relationships between this agent's pharmacokinetics and indicators of body size have not been developed. The aim of this analysis was to develop an ertapenem population pharmacokinetic model using data from a previously described study in normal-weight, obese, and morbidly obese healthy volunteers. A single ertapenem 1-g dose administered intravenously was evaluated in 30 subjects within different body mass index (BMI) categories. The population pharmacokinetic model was developed using the first-order conditional estimation method with interaction (FOCE-I) algorithm within NONMEM. The ability of age, sex, renal function, and various body size measures (total body weight, height, body mass index, ideal body weight, fat-free mass, and body surface area [BSA]) to explain a portion of the interindividual variability on select pharmacokinetic parameters was explored using stepwise forward selection (α = 0.01) and backward elimination (α = 0.001). The data were best described using a linear three-compartment model with total body weight as a covariate on clearance (CL = 1.79 · [weight/95.90]0.278) and BSA as a covariate on central volume (Vc = 4.76 · [BSA/2.06]1.86). After accounting for fixed effects, the estimated interindividual variability was very low (<10% for all clearance and volume terms). Goodness-of-fit diagnostics indicated a precise and unbiased fit to the data. Using the developed population pharmacokinetic model and simulation, reliable estimates of ertapenem serum exposures, which can be utilized to evaluate various dosing regimens in subjects with a wide range of body sizes, are expected.

Personalizing Polymyxin B Dosing Using an Adaptive Feedback Control Algorithm.

Polymyxin B is used as an antibiotic of last resort for patients with multidrug-resistant Gram-negative bacterial infections; however, it carries a significant risk of nephrotoxicity. Herein we present a polymyxin B therapeutic window based on target area under the concentration-time curve (AUC) values and an adaptive feedback control algorithm (algorithm) which allows for the personalization of polymyxin B dosing. The upper bound of this therapeutic window was determined through a pharmacometric meta-analysis of polymyxin B nephrotoxicity data, and the lower bound was derived from murine thigh infection pharmacokinetic (PK)/pharmacodynamic (PD) studies. A previously developed polymyxin B population pharmacokinetic model was used as the backbone for the algorithm. Monte Carlo simulations (MCS) were performed to evaluate the performance of the algorithm using different sparse PK sampling strategies. The results of the nephrotoxicity meta-analysis showed that nephrotoxicity rate was significantly correlated with polymyxin B exposure. Based on this analysis and previously reported murine PK/PD studies, the target AUC0-24 (AUC from 0 to 24 h) window was determined to be 50 to 100 mg · h/liter. MCS showed that with standard polymyxin B dosing without adaptive feedback control, only 71% of simulated subjects achieved AUC values within this window. Using a single PK sample collected at 24 h and the algorithm, personalized dosing regimens could be computed, which resulted in >95% of simulated subjects achieving AUC0-24 values within the target window. Target attainment further increased when more samples were used. Our algorithm increases the probability of target attainment by using as few as one pharmacokinetic sample and enables precise, personalized dosing in a vulnerable patient population.

Polymyxin B in Combination with Enrofloxacin Exerts Synergistic Killing against Extensively Drug-Resistant Pseudomonas aeruginosa.

Polymyxins are increasingly used as a last-resort class of antibiotics against extensively drug-resistant (XDR) Gram-negative bacteria. However, resistance to polymyxins can emerge with monotherapy. As nephrotoxicity is the major dose-limiting factor for polymyxin monotherapy, dose escalation to suppress the emergence of polymyxin resistance is not a viable option. Therefore, novel approaches are needed to preserve this last-line class of antibiotics. This study aimed to investigate the antimicrobial synergy of polymyxin B combined with enrofloxacin against Pseudomonas aeruginosa Static time-kill studies were conducted over 24 h with polymyxin B (1 to 4 mg/liter) and enrofloxacin (1 to 4 mg/liter) alone or in combination. Additionally, in vitro one-compartment model (IVM) and hollow-fiber infection model (HFIM) experiments were performed against P. aeruginosa 12196. Polymyxin B and enrofloxacin in monotherapy were ineffective against all of the P. aeruginosa isolates examined, whereas polymyxin B-enrofloxacin in combination was synergistic against P. aeruginosa, with ≥2 to 4 log10 kill at 24 h in the static time-kill studies. In both IVM and HFIM, the combination was synergistic, and the bacterial counting values were below the limit of quantification on day 5 in the HFIM. A population analysis profile indicated that the combination inhibited the emergence of polymyxin resistance in P. aeruginosa 12196. The mechanism-based modeling suggests that the synergistic killing is a result of the combination of mechanistic and subpopulation synergy. Overall, this is the first preclinical study to demonstrate that the polymyxin-enrofloxacin combination is of considerable utility for the treatment of XDR P. aeruginosa infections and warrants future clinical evaluations.

Mechanism-Based Pharmacokinetic/Pharmacodynamic Modeling of Aerosolized Colistin in a Mouse Lung Infection Model.

Optimized dosage regimens of aerosolized colistin (as colistin methanesulfonate [CMS]) are urgently required to maximize bacterial killing against multidrug-resistant Gram-negative bacteria while minimizing toxicity. This study aimed to develop a mechanism-based pharmacokinetic (PK)/pharmacodynamic (PD) model (MBM) for aerosolized colistin based upon PK/PD data in neutropenic infected mice and to perform a deterministic simulation with the PK of aerosolized colistin (as CMS) in critically ill patients. In vivo time-kill experiments were carried out with three different strains of Pseudomonas aeruginosa An MBM was developed in S-ADAPT and evaluated by assessing its ability to predict the PK/PD index associated with efficacy in mice. A deterministic simulation with human PK data was undertaken to predict the efficacy of current dosage regimens of aerosolized colistin in critically ill patients. In the final MBM, the total bacterial population for each isolate consisted of colistin-susceptible and -resistant subpopulations. The antimicrobial efficacy of aerosolized colistin was best described by a sigmoidal Emax model whereby colistin enhanced the rate of bacterial death. Deterministic simulation with human PK data predicted that an inhalational dosage regimen of 60 mg colistin base activity (CBA) every 12 h is needed to achieve a ≥2-log10 bacterial reduction (as the number of CFU per lung) in critically ill patients at 24 h after commencement of inhaled therapy. In conclusion, the developed MBM is a useful tool for optimizing inhalational dosage regimens of colistin. Clinical studies are warranted to validate and refine our MBM for aerosolized colistin.