Abstract First-line antifungal therapies are limited to azoles, polyenes and echinocandins, the former two of which are associated with high occurrences of severe treatment-emergent adverse events or frequent drug interactions. Among antifungals, echinocandins present a unique value proposition given their lower rates of toxic events as compared with azoles and polyenes. However, with the emergence of echinocandin-resistant Candida species and the fact that a pharmacometric approach to the development of anti-infective agents was not a mainstream practice at the time these agents were developed, we question whether echinocandins are being dosed optimally. This review presents pharmacokinetic/pharmacodynamic (PK/PD) evaluations for approved echinocandins (anidulafungin, caspofungin and micafungin) and rezafungin (previously CD101), an investigational agent. PK/PD-optimized regimens were evaluated to extend the utility of approved echinocandins when treating patients with resistant isolates. Although the benefits of these regimens were apparent, it was also clear that anidulafungin and micafungin, regardless of dosing adjustments, are unlikely to provide therapeutic exposures sufficient to treat highly resistant isolates. Day 1 probabilities of PK/PD target attainment of 5.2% and 85.1%, respectively, were achieved at the C. glabrata MIC90 (0.12 mg/L) and MIC97 (0.06 mg/L) values, respectively, for these agents. However, evaluations of rezafungin demonstrated high probabilities of target attainment over 4 weeks of therapy (100%) after administration of a single-dose regimen at the MIC90 of 0.06 mg/L. This signals that although existing therapies are not optimal to treat resistant organisms, more potent new echinocandins (relative to achievable drug exposures) may be on the horizon. Introduction Clinicians today are provided a limited armamentarium regarding the therapies available to treat mycoses. Treatments are effectively limited to three drug classes: azoles, echinocandins and polyenes. Of these, the polyenes act by forming membrane pores through binding to ergosterol, a key structural component in fungal cell membranes. Thus, membrane permeability is increased, causing the leakage of intracellular potassium and other molecules. Azoles destabilize fungal cell membranes by preventing C-14α demethylation of lanosterol through binding to fungal cytochrome P-450 enzymes, resulting in decreased ergosterol production. However, the mechanisms by which these agents act present a double-edged sword. Non-specific binding of polyenes to cholesterol in mammalian cell membranes1 and of azoles to human cytochrome P-450 enzymes2 may result in drug-related toxicities. Development of therapies specific for fungi has been challenging given that, unlike bacteria, fungi are eukaryotic organisms. Thus, the targets for these agents are more likely to resemble those found in humans.3 Echinocandins are unique in that they target the cell wall. Given that this component is absent from mammalian cells, echinocandins are less likely to interact with human cells and therefore result in fewer toxic events as compared with azoles and polyenes. These agents reduce the integrity of fungal cell walls by disrupting glucan synthesis, their primary structural component, through inhibition of the 1,3-β-d-glucan synthase enzyme. These agents provide a safe and effective alternative to more traditional polyene and azole therapies. The first of these agents, caspofungin, received approval from the US FDA in 2001, which was later followed by approvals for micafungin and anidulafungin in 2005 and 2006, respectively. In the nearly two decades these agents have been available, no changes have been made to their recommended dosing regimens.4 Given that a pharmacometric approach to the development of anti-infective agents was not a mainstream practice at the time echinocandins were developed, the dosing of echinocandins may not be optimized for pharmacokinetics/pharmacodynamics (PK/PD). Moreover, the use of echinocandins5 has steadily increased and the prevalence of echinocandin resistance among Candida species,6–14 though still relatively rare, has also increased since these agents were introduced to the clinic. These trends are especially troubling in light of recent clinical studies which have indicated that treatment failures and patient mortality increase with caspofungin MIC.15,16 Thus, we are left questioning whether current dosing recommendations for these agents provide therapeutic drug concentrations in patients with infections due to resistant Candida. Herein, we will delve into this question and consider echinocandin dosing strategies, both traditional and novel. But we must first review how antimicrobial dosing regimens are derived. Dose fractionation: the first step towards regimen selection In essence, an optimized dosing regimen is one which best balances the competing needs for high efficacy and low toxicity. Early investigations for dose selection are ideally performed pre-clinically. In vivo and in vitro infection models are utilized to characterize the relationship between drug exposures and fungal density (primarily measured as log10 cfu). Critical to our understanding of this relationship is recognizing the fact that not all antifungal agents exhibit the same patterns of fungicidal activity.17 Some drugs exhibit what is known as concentration-dependent activity, meaning that, as drug concentrations increase, so too do the rate and extent of pathogen killing.18 This pattern of activity is best captured by expressing drug exposures indexed to a pathogen’s degree of susceptibility to the agent in question. The PK/PD indices frequently assessed to evaluate such agents are the AUC:MIC and Cmax:MIC ratios. Conversely, for some drugs the rate and extent of bacterial killing are not increased over a wide range of drug concentrations. The activity of these agents is time dependent and their effects are largely dependent upon the time during which exposures remain above a target threshold. This is best captured by the percentage of time that drug concentrations remain above a pathogen’s MIC (%T>MIC). Collectively, the AUC:MIC ratio, Cmax:MIC ratio and %T>MIC are the three most common PK/PD indices used to characterize the relationship between exposure and efficacy. Determining the PK/PD index most associated with efficacy for a given antifungal allows investigators to determine the magnitudes of these indices associated with different levels of bacterial reduction (i.e. PK/PD targets for efficacy). Such information can be used to identify PK/PD-optimized dosing regimens for development. The determination of the PK/PD index is made by conducting dose-fractionation studies, whereby fungicidal activity is evaluated by administering the same total dose of an agent over a multitude of dosing intervals. Multiple doses are administered in this manner to obtain a range of exposures. Figure 1 shows data obtained from a dose-fraction study conducted by Andes et al.,19 in which neutropenic mice were infected with Candida glabrata and administered one of 20 anidulafungin dosing regimens. Total doses of 1.25, 5, 20, 80 or 320 mg/kg were administered over 96 h as one, two, four, or six divided doses (i.e. doses were given every 96, 48, 24 or 16 h, respectively).19 Using Hill-type models, relationships between the change in fungal density in homogenized tissue relative to baseline and the three PK/PD indices discussed previously were evaluated. As shown in Figure 1, these data demonstrated that fungal density was most closely associated with anidulafungin AUC:MIC and Cmax:MIC ratios, indicating that this agent exhibits a concentration-dependent pattern of fungicidal activity. The ideal regimen for this agent is one that optimizes anidulafungin exposures to maximize fungal killing while minimizing drug-induced toxicities. Figure 1. View largeDownload slide Relationships between change in log10 cfu from baseline at 24 h and anidulafungin total-drug AUC:MIC ratio, Cmax:MIC ratio and %T>MIC. This figure is based on data from Andes et al.19 Figure 1. View largeDownload slide Relationships between change in log10 cfu from baseline at 24 h and anidulafungin total-drug AUC:MIC ratio, Cmax:MIC ratio and %T>MIC. This figure is based on data from Andes et al.19 Front-loading: answering the unexplored questions of efficacy While data from dose-fractionation studies lay the foundation for the determination of target exposures and provide preliminary guidance for the selection of maintenance therapy (i.e. the data inform dosing frequency and magnitude), these studies are not designed to support the selection of the optimal duration of therapy. Moreover, they cannot assess what impact a loading dose will have on efficacy. However, Okusanya et al.20 elegantly demonstrated how these factors impact efficacy of azithromycin in an evaluation of gerbils with Haemophilus influenzae middle ear infections. A front-loading experiment design was utilized, in which each animal was administered intermittent bolus doses to simulate human concentration–time profiles for one of three azithromycin dosing regimens containing the same total dose: (i) a 500 mg loading dose on Day 1 followed by 250 mg daily; (ii) 500 mg daily for 3 days; or (iii) a single 1500 mg dose on Day 1. Plasma concentrations and cfu counts were measured pre-dose and at 1, 2, 3, 4, 5, 6, 12, 24, 48 and 72 h to facilitate the creation of PK and PK/PD models. The observed and model-predicted data generated are shown in Figure 2. These data revealed that killing was most extensive and rapid following administration of the single azithromycin 1500 mg dose, suggesting that optimal outcomes could be achieved by administering a single dose of azithromycin, which maximizes exposures early in therapy and produces sustained therapeutic concentrations to maintain antimicrobial activity. These analyses also served to demonstrate that, for some agents, the shape of the drug exposure is a determinant of efficacy. Figure 2. View largeDownload slide Plots of gerbil plasma concentration–time and changes in bacterial density superimposed over observed data and the model-predicted function for the rate of bacterial death. Figure 2. View largeDownload slide Plots of gerbil plasma concentration–time and changes in bacterial density superimposed over observed data and the model-predicted function for the rate of bacterial death. When does exposure shape matter? The hypothesis that the shape of the drug exposure can impact efficacy was also explored for the lipoglycopeptide oritavancin.21 In that evaluation, the authors provided support for the use of an oritavancin 1200 mg single-dose regimen for the treatment of acute bacterial skin and skin structure infections (ABSSSIs), which is now an approved treatment for such patients. This regimen was chosen with two considerations in mind, the first being that oritavancin demonstrates concentration-dependent bacterial killing. Second, oritavancin exhibits a very long terminal half-life of ∼245 h.22 Azithromycin, for which the PK/PD index associated with efficacy is AUC:MIC ratio23,24 and which has a relatively short terminal half-life of 68 h, also exhibits these characteristics.25 Consequently, without the use of a loading dose, it would take weeks for these agents to achieve steady-state concentrations. Conversely, when a front-loaded regimen is administered, the maximal rate and extent of bacterial killing can be achieved early in therapy, as previously shown with azithromycin.20 The applicability of this concept to clinical practice was demonstrated through the results of a Phase 2 study in which 302 patients with ABSSSI were randomized to receive one of three oritavancin treatment regimens: (i) 200 mg daily for 3–7 days; (ii) 800 mg on Day 1 plus 400 mg on Day 5 (at the discretion of the treating physician); or (iii) a single 1200 mg dose on Day 1.26 Evaluation of data from patients across multiple analysis populations in this study revealed that clinical outcomes improved as the magnitude of exposures early in therapy increased. Data from two Phase 3 studies served to confirm the efficacy and safety of the single 1200 mg oritavancin dosing regimen in patients with ABSSSI.27,28 The above-described data demonstrate that the shape of exposure impacts efficacy when an antibacterial agent exhibits a concentration-dependent pattern of bacterial killing and has a long half-life in plasma. Thus, such attributes together provide a basis for assessing candidate anti-infective agents for single or extended-interval dosing regimens. We can now enquire as to whether or not these same principles can be applied to antifungal agents. Rethinking echinocandin dosing As previously stated, the dosing of echinocandins has remained largely unchanged since these agents were brought to the clinic, whereas echinocandin-resistant Candida spp. have been increasingly emerging over this period.6–14 The most notable of these resistant pathogens has been C. glabrata, owing to this organism’s natural predisposition for expressing resistance mutations.29 As mentioned above, increases in C. glabrata MIC values have been associated with increases in treatment failures and mortality.15,16 Consequently, the consideration of treatment options for patients with these resistant organisms has become a priority. Clinical studies have been conducted to establish differences in efficacy between approved caspofungin and micafungin dosing regimens and regimens with higher doses (70 mg followed by 50 mg daily versus 150 mg daily and 100 mg daily versus 150 mg daily, respectively).30–32 However, none of these studies demonstrated statistically significant differences in clinical outcomes between the standard and high-dose treatment regimens. These results are not surprising given that treatment differences are more likely to be seen when treating patients with isolates at the upper end of the MIC distribution, a population that is often too limited in sample size. When the MIC distributions for both agents were reported for these studies, the drug concentrations required to inhibit 90% of isolates (MIC90) were ≤0.03 mg/L across all non-C. parapsilosis spp.30,31 These data suggest that exposures for both treatment regimens should have exceeded non-clinical PK/PD targets for the majority of isolates. However, the number of patients in clinical studies infected with pathogens with higher MIC values is often too limited to discriminate between dosing regimens. Given the limitations of the data described above, results of PK/PD target attainment analyses can be utilized to forecast the efficacy of different dosing regimen at fixed MIC values, including those that are higher but less frequently encountered. Recent analyses that we conducted33 served to assess the adequacy of approved echinocandin dosing regimens for the treatment of patients with candidaemia in the context of contemporary in vitro surveillance data for C. glabrata.34 In that evaluation, Monte Carlo simulation was used to generate daily AUC values for simulated patients following the administration of 200 mg of anidulafungin followed by 100 mg daily, 70 mg of caspofungin followed by 50 mg daily, or 100 mg of micafungin daily. The simulated AUC values obtained from these analyses were evaluated relative to AUC:MIC ratio targets associated with net fungal stasis to assess the likelihood of achieving PK/PD targets associated with efficacy among highly resistant isolates.35 Relative to MIC90 values, caspofungin and micafungin were likely to achieve therapeutic drug exposures in the majority of simulated patients, whereas anidulafungin was unlikely to achieve target exposures in the majority of simulated patients (Figure 3). However, when evaluating micafungin one dilution above the MIC90 (0.06 mg/L), the percentage probabilities of PK/PD target attainment were less favourable, ranging from 10.3% to 49.9% over Days 1–14. These results are in contrast with caspofungin’s highly favourable percentage probabilities of PK/PD target attainment when evaluated relative to one dilution above the C. glabrata MIC90 of 0.12 mg/L (100% across the entire 14 day treatment period). In response to these findings, PK/PD-optimized dosing regimens were proposed with the goal of providing therapeutic exposures early in therapy and maintaining these over a 2 week course of therapy. Increasing the anidulafungin dosing to 300 mg followed by 200 mg resulted in percentage probabilities of PK/PD target attainment across Days 1–14 improving from 0%–0.95% to 5%–54.3% for approved dosing at the C. glabrata MIC90 of 0.12 mg/L. Similarly, improvements were observed when a micafungin regimen of 200 mg followed by 150 mg daily was evaluated (from 10.3%–49.9% to 85.1%–87.5%) at the C. glabrata MIC97 of 0.06 mg/L. These results suggest that the current dosing regimens for caspofungin and micafungin are able to combat C. glabrata isolates up to and including the MIC90 values for these agents. However, this was not the case for micafungin if the C. glabrata MIC90 shifts upward even if only by one dilution. This is concerning given that resistance rates among C. glabrata isolates have been reported to be as high as 12% and acquired echinocandin resistance has been observed among various Candida spp.,36,37 all of which support the need for new therapies. Figure 3. View largeDownload slide Distributions of free-drug plasma AUC:MIC ratio based on C. glabrata MIC90 values (mg/L) for each respective FDA-approved echinocandin administered. The boxplot whiskers denote the 5th and 95th percentiles among simulated patients. Free-drug plasma AUC:MIC ratio PK/PD targets associated with net fungal stasis for each echinocandin are indicated by dashed lines. Figure 3. View largeDownload slide Distributions of free-drug plasma AUC:MIC ratio based on C. glabrata MIC90 values (mg/L) for each respective FDA-approved echinocandin administered. The boxplot whiskers denote the 5th and 95th percentiles among simulated patients. Free-drug plasma AUC:MIC ratio PK/PD targets associated with net fungal stasis for each echinocandin are indicated by dashed lines. One question that remains is whether the approved echinocandins can achieve greater efficacy when administered in larger quantities over extended intervals. It is well established that currently approved echinocandin agents exhibit a concentration-dependent pattern of fungal killing both in vivo and in vitro.17,38 Moreover, anidulafungin and caspofungin exhibit relatively long terminal half-lives in human plasma (40–50 h).39,40 Conversely, micafungin exhibits a more typical half-life of 13–17 h.41 However, despite micafungin’s short half-life relative to anidulafungin and caspofungin, murine disseminated candidiasis model studies have been conducted utilizing humanized single-dose and extended-interval dosing regimens.42,43 Although these studies showed promise for the use of single and extended-interval dosing of micafungin, clinical data evaluating such regimens are lacking. However, recent work has been conducted to demonstrate the potential for single-dose administration of rezafungin acetate (previously CD101), a novel echinocandin in Phase 2 of development for the treatment of candidaemia and invasive candidiasis that has activity against Aspergillus and Candida spp., including azole- and echinocandin-resistant isolates. Lakota et al.44 evaluated rezafungin in a neutropenic murine disseminated candidiasis model, in which rezafungin 2 mg/kg was administered using either a single-dose, twice weekly, or daily regimen. Across these regimens, reductions in fungal density 168 h post-dose increased in parallel with the intensity of early exposures (Figure 4). The same exposure was administered to each animal, but the magnitudes of fungal killing varied greatly, indicating that the shape of rezafungin exposure impacts efficacy. This should come as no surprise considering rezafungin, like other echinocandins, demonstrates a concentration-dependent pattern of fungal killing45 and exhibits a very long half-life in humans (133 h).46 Figure 4. View largeDownload slide Mean (bar) and range (error bars) change in log10 cfu from baseline at 168 h after administration of 2 mg/kg rezafungin by a fractionation schedule. This figure is reproduced from reference 44 with kind permission from the American Society for Microbiology. Figure 4. View largeDownload slide Mean (bar) and range (error bars) change in log10 cfu from baseline at 168 h after administration of 2 mg/kg rezafungin by a fractionation schedule. This figure is reproduced from reference 44 with kind permission from the American Society for Microbiology. In order to translate these findings to humans infected with C. glabrata, we conducted PK/PD target attainment analyses utilizing the methodology previously employed in our evaluation of approved echinocandins.33 A rezafungin free-drug plasma AUC0–168:MIC ratio target associated with net fungal stasis of 0.5 was utilized.47 Three dosing regimens were evaluated over 4 weeks: (i) 400 mg single dose; (ii) 400 mg weekly for 3 weeks; and (iii) 400 mg × 1 for Week 1 followed by 200 mg weekly for 2 weeks. Each of the dosing regimens evaluated performed well at the C. glabrata MIC90 of 0.06 mg/L,48 including the single-dose 400 mg regimen. This regimen achieved percentage probabilities of PK/PD target attainment of 100% across Weeks 1–4 at this high MIC benchmark. In order to further evaluate these dosing regimens, PK/PD target attainment analyses were conducted utilizing a free-drug plasma AUC:MIC0–168 ratio target associated with a 1 log10 cfu reduction in C. glabrata of 2.94, and as described above for the net fungal stasis endpoint, all regimens achieved probabilities of PK/PD target attainment of 100% across Weeks 1–4 (Figure 5). Figure 5. View largeDownload slide Distributions of free-drug AUC0–168:MIC ratios for C. glabrata based on MIC90. The boxplot whiskers denote the 5th and 95th percentiles among simulated patients. The rezafungin free-drug plasma AUC0–168:MIC ratio PK/PD target associated with a 1 log10 cfu reduction in C. glabrata from baseline is indicated by dashed lines. Figure 5. View largeDownload slide Distributions of free-drug AUC0–168:MIC ratios for C. glabrata based on MIC90. The boxplot whiskers denote the 5th and 95th percentiles among simulated patients. The rezafungin free-drug plasma AUC0–168:MIC ratio PK/PD target associated with a 1 log10 cfu reduction in C. glabrata from baseline is indicated by dashed lines. Concluding remarks Herein, we described PK/PD target attainment analyses as a mechanism to evaluate labelled doses of approved echinocandins in the context of contemporary in vitro surveillance data and to ‘pre-screen’ revised regimens prior to conducting clinical assessments. The benefits of evaluating additional regimens were apparent in extending the utility of micafungin, which has been safely administered up to doses of 900 mg with limited occurrences of serious adverse events,49,50,51 against C. glabrata up to the MIC90 value of 0.03 mg/L. However, the revised anidulafungin dosing regimen presented was not predicted to result in clinically meaningful increases in the likelihood of achieving efficacious drug exposures. Moreover, the doses included in this regimen, 200 and 300 mg, have only been assessed when administered intermittently over 48 and 72 h intervals, respectively.52 Thus, the safety data associated with daily administration of these doses are lacking to date. Regardless, it is evident that these agents, regardless of dosing adjustments, are unlikely to provide therapeutic exposures to treat isolates with elevated MIC values (e.g. those one dilution above the MIC90). Consequently, we evaluated rezafungin, a novel echinocandin, and conducted PK/PD target attainment analyses to demonstrate the potential to administer a single-dose regimen and provide exposures associated with efficacy for up to 4 weeks. This finding is significant in that such a regimen presents the opportunity to deliver drug exposures in a PK/PD-optimized manner, improve patient compliance and reduce the resources required for therapeutic drug monitoring over a long treatment period. In summary, existing echinocandin regimens can be PK/PD optimized to better balance the competing needs for high efficacy and low toxicity when treating patients with resistant Candida isolates. There may also be an opportunity in the future to utilize rezafungin and administer it as a single-dose regimen. Funding This article is part of a Supplement sponsored by Cidara Therapeutics, Inc. Editorial support was provided by T. Chung (Scribant Medical) with funding from Cidara. Transparency declarations The Institute for Clinical Pharmacodynamics, Inc. (J. C. B., S. M. B. and P. G. A.) has received research support from and/or provides consulting for Achaogen Inc., Actelion Pharmaceuticals, Actavis Generics, AiCuris GmbH, Arsanis Inc., Basilea Pharmaceutica, Cellceutix Corporation, Cempra Pharmaceuticals, Cidara Therapeutics Inc., Contrafect Corporation, Debiopharm International SA, Emergent, Entasis Therapeutics, Geom Therapeutics, Inc., GlaxoSmithKline, Horizon, Insmed Inc., Kalyra Pharmaceuticals, The Medicines Company, Meiji Seika Pharma Co., Ltd., Melinta Therapeutics, The Menarini Group, Merck Sharpe & Dohme., Nabriva Therapeutics, Naeja RGM Pharmaceuticals Inc., Nexcida Therapeutics, Inc., Northern Antibiotics, Novartis International, NuCana Biomed, Paratek Pharmaceuticals, Pernix Therapeutics, Polyphor Ltd., Polypid Ltd., Prothena Corporation, Regeneron Pharmaceuticals, Roche Bioscience, Shionogi, Inc., Sofinnova Ventures, Inc., Spero Therapeutics, Takeda Pharma, Theravance Biopharma Pharmaceutica, Tetraphase Pharmaceuticals, Turing Pharmaceuticals, VenatoRx, Wockhardt Ltd. and Zavante Therapeutics. In addition, P. G. A. is a consultant for Duke University. D. R. A. is an employee of the University of Wisconsin and has received research support from Astellas Pharma, Scynexis Inc., Cidara Therapeutics Inc., Actelion Pharmaceuticals, Zavante Therapeutics, Paratek Pharmaceuticals, Geom Therapeutics Inc., Melinta Therapeutics, Theravance Biopharma, and serves as a consultant for Astellas Pharma, Scynexis Inc., Cidara Therapeutics Inc., Viamet Pharmaceuticals Inc., Zavante Therapeutics and Theravance Biopharma. References 1 Brajtburg J, Powerderly WG, Kobayashi GS et al. Amphotericin B: current understanding of mechanisms of action. Antimicrob Agents Chemother 1990; 34: 183– 8. http://dx.doi.org/10.1128/AAC.34.2.183 Google Scholar CrossRef Search ADS PubMed 2 Katz HI. Drug interactions of the newer oral antifungal agents. Br J Dermatol 1999; 141: 26– 32. http://dx.doi.org/10.1046/j.1365-2133.1999.00011.x Google Scholar CrossRef Search ADS PubMed 3 Wiederhold NP, Lewis RE. The echinocandin antifungals: an overview of the pharmacology, spectrum and clinical efficacy. Expert Opin Investig Drugs 2003; 12: 1313– 27. http://dx.doi.org/10.1517/13543718.104.22.1683 Google Scholar CrossRef Search ADS PubMed 4 United States Food and Drug Administration. Drugs@FDA: FDA approved drug products database. https://www.accessdata.fda.gov/scripts/cder/daf/. 5 Fekkar A, Dannoui E, Meyer I et al. Emergence of echinocandin-resistant Candida spp. in a hospital setting: a consequence of 10 years of increasing use of antifungal therapy? Eur J Clin Microbiol Infect Dis 2014; 33: 1489– 96. Google Scholar CrossRef Search ADS PubMed 6 Forastiero A, Garcia-Gil V, Rivero-Menendez O et al. Rapid development of Candida krusei echinocandin resistance during caspofungin therapy. Antimicrob Agents Chemother 2015; 59: 6975– 82. Google Scholar CrossRef Search ADS PubMed 7 Kofteridis DP, Lewis RE, Kontoyiannis DP. Caspofungin-non-susceptible Candida isolates in cancer patients. J Antimicrob Chemother 2010; 65: 293– 5. http://dx.doi.org/10.1093/jac/dkp444 Google Scholar CrossRef Search ADS PubMed 8 Pfeiffer CD, Garcia-Effron G, Zaas AK et al. Breakthrough invasive candidiasis in patients on micafungin. J Clin Microbiol 2010; 48: 2373– 80. http://dx.doi.org/10.1128/JCM.02390-09 Google Scholar CrossRef Search ADS PubMed 9 Prigent G, Ait-Ammar N, Levesque E et al. Echinocandin resistance in Candida species isolates from liver transplant recipients. Antimicrob Agents Chemother 2017; 61: e01229– 16. Google Scholar PubMed 10 Ruggero MA, Topal JE. Development of echinocandin-resistant Candida albicans candidemia following brief prophylactic exposure to micafungin therapy. Transpl Infect Dis 2014; 16: 469– 72. http://dx.doi.org/10.1111/tid.12230 Google Scholar CrossRef Search ADS PubMed 11 Pfaller M, Boyken L, Hollis R et al. Use of epidemiological cutoff values to examine 9-year trends in susceptibility of Candida species to anidulafungin, caspofungin, and micafungin. J Clin Microbiol 2011; 49: 624– 9. http://dx.doi.org/10.1128/JCM.02120-10 Google Scholar CrossRef Search ADS PubMed 12 Sun HY, Singh N. Characterisation of breakthrough invasive mycoses in echinocandin recipients: an evidence-based review. Int J Antimicrob Agents 2010; 35: 211– 8. http://dx.doi.org/10.1016/j.ijantimicag.2009.09.020 Google Scholar CrossRef Search ADS PubMed 13 Zimbeck AJ, Iqbal N, Ahlquist AM et al. FKS mutations and elevated echinocandin MIC values among Candida glabrata isolates from U.S. population-based surveillance. Antimicrob Agents Chemother 2010; 54: 5042– 7. Google Scholar CrossRef Search ADS PubMed 14 Perlin DS, Shor E, Zhao Y. Update on antifungal drug resistance. Curr Clin Microbiol Rep 2015; 2: 84– 95. http://dx.doi.org/10.1007/s40588-015-0015-1 Google Scholar CrossRef Search ADS PubMed 15 Beyda N, John J, Kilic A et al. FKS mutant Candida glabrata: risk factors and outcomes in patients with candidemia. Clin Infect Dis 2014; 59: 819– 25. http://dx.doi.org/10.1093/cid/ciu407 Google Scholar CrossRef Search ADS PubMed 16 Farmakiotis D, Tarrand JJ, Dimitrios KP. Drug-resistant Candida glabrata infection in cancer patients. Emerg Infect Dis 2014; 20: 1833– 40. Google Scholar CrossRef Search ADS PubMed 17 Andes D. Pharmacokinetics and pharmacodynamics of antifungals. Infect Dis Clin North Am 2006; 20: 679– 97. http://dx.doi.org/10.1016/j.idc.2006.06.007 Google Scholar CrossRef Search ADS PubMed 18 Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis 1998; 26: 1– 10. http://dx.doi.org/10.1086/516284 Google Scholar CrossRef Search ADS PubMed 19 Andes D, Diekema DJ, Pfaller MA et al. In vivo pharmacodynamic characterization of anidulafungin in a neutropenic murine candidiasis model. Antimicrob Agents Chemother 2008; 52: 539– 50. http://dx.doi.org/10.1128/AAC.01061-07 Google Scholar CrossRef Search ADS PubMed 20 Okusanya OO, Forrest A, Booker BM et al. Pharmacokinetics and pharmacodynamics of azithromycin in gerbils with Haemophilus influenzae middle ear infection. In: Abstracts of the Annual Meeting of the American Society for Clinical Pharmacology and Therapeutics, Philadelphia, PA, USA, 2005. Abstract 77, p. 89. American Society for Clinical Pharmacology and Therapeutics, VA, USA. 21 Ambrose PG, Drusano GL, Craig WA. In vivo activity of oritavancin in animal infection models and rationale for a new dosing regimen in humans. Clin Infect Dis 2012; 54 Suppl 3: S220– 8. Google Scholar CrossRef Search ADS PubMed 22 The Medicines Company. Orbactiv® injection Package Insert. 2016. 23 Drusano GL, Craig WA. Relevance of pharmacokinetics and pharmacodynamics in the selection of antibiotics for respiratory tract infections. J Chemother 1997; 9 Suppl 3: 38– 44. Google Scholar CrossRef Search ADS PubMed 24 Craig WA. The hidden impact of antibacterial resistance in respiratory tract infection. Re-evaluating current antibiotic therapy. Respir Med 2001; 95 Suppl A: S12– 9. Google Scholar CrossRef Search ADS PubMed 25 Pfizer Inc. Zithromax® injection Package Insert. 2017. 26 Dunbar LM, Milata J, McClure T et al. Comparison of the efficacy and safety of oritavancin in front-loaded dosing regimens to daily dosing: an analysis of the SIMPLIFI trial. Antimicrob Agents Chemother 2011; 55: 3476– 84. http://dx.doi.org/10.1128/AAC.00029-11 Google Scholar CrossRef Search ADS PubMed 27 Corey GR, Kabler H, Mehra P et al. Single-dose oritavancin in the treatment of acute bacterial skin infections. N Engl J Med 2014; 370: 2180– 90. http://dx.doi.org/10.1056/NEJMoa1310422 Google Scholar CrossRef Search ADS PubMed 28 Corey R, Good S, Jiang H et al. Single-dose oritavancin versus 7-10 days of vancomycin in the treatment of Gram-positive acute bacterial skin and skin structure infections: the SOLO II noninferiority study. Clin Infect Dis 2015; 60: 254– 62. http://dx.doi.org/10.1093/cid/ciu778 Google Scholar CrossRef Search ADS PubMed 29 Otto SP, Gerstein AC. The evolution of haploidy and diploidy. Curr Biol 2008; 18: R1121– 4. Google Scholar CrossRef Search ADS PubMed 30 Wet N, Llanos-Cuentas A, Suleiman J et al. A randomized, double-blind, parallel-group, dose-response study of micafungin compared with fluconazole for the treatment of esophageal candidiasis in HIV-positive patients. Clin Infect Dis 2004; 39: 842– 9. http://dx.doi.org/10.1086/423377 Google Scholar CrossRef Search ADS PubMed 31 Pappas PG, Rotstein C, Betts RF et al. Micafungin versus caspofungin for treatment of candidemia and other forms of invasive candidiasis. Clin Infect Dis 2007; 45: 883– 93. http://dx.doi.org/10.1086/520980 Google Scholar CrossRef Search ADS PubMed 32 Betts RF, Nucci M, Talwar D et al. A multicenter, double-blind trial of a high-dose caspofungin treatment regimen versus a standard caspofungin treatment regimen for adult patients with invasive candidiasis. Clin Infect Dis 2009; 48: 1676– 84. http://dx.doi.org/10.1086/598933 Google Scholar CrossRef Search ADS PubMed 33 Bader JC, Lakota EA, Bhavnani SM et al. Emerging Candida glabrata resistance and echinocandin dosing: a call to arms! In: Abstracts of the Infectious Diseases Society of America IDWeek, New Orleans, LA, USA, 2016. Abstract 1973. Infectious Diseases Society of America, Arlington, VA, USA. 34 Castanheira M, Deshpande LM, Davis AP et al. Monitoring antifungal resistance in a global collection of invasive yeasts and moulds: application of CLSI epidemiological cutoff values and whole genome sequencing analysis for detection of azole resistance in Candida albicans. Antimicrob Agents Chemother 2017; 61: pii= e00906– 17. Google Scholar PubMed 35 Andes DR, Diekema DJ, Pfaller MA et al. In vivo comparison of the pharmacodynamic targets for echinocandin drugs against Candida species. Antimicrob Agents Chemother 2010; 54: 2497– 506. http://dx.doi.org/10.1128/AAC.01584-09 Google Scholar CrossRef Search ADS PubMed 36 Alexander BD, Johnson MD, Pfeiffer CD et al. Increasing echinocandin resistance in Candida glabrata: clinical failure correlates with presence of FKS mutations and elevated minimum inhibitory concentrations. Clin Infect Dis 2013; 56: 1724– 32. http://dx.doi.org/10.1093/cid/cit136 Google Scholar CrossRef Search ADS PubMed 37 Kullberg BJ, Arendrup MC. Invasive candidiasis. N Engl J Med 2015; 373: 1445– 56. http://dx.doi.org/10.1056/NEJMra1315399 Google Scholar CrossRef Search ADS PubMed 38 Pound MW, Townsend ML, Drew RH. Echinocandin pharmacodynamics: review and clinical implications. J Antimicrob Chemother 2010; 65: 1108– 18. http://dx.doi.org/10.1093/jac/dkq081 Google Scholar CrossRef Search ADS PubMed 39 Pfizer Inc. Eraxis® injection Package Insert. 2016. 40 Merck Sharpe & Dohme Corp. Cancidas® injection Package Insert. 2017. 41 Astellas Pharma US, Inc. Mycamine® injection Package Insert. 2016. 42 Gumbo T, Drusano GL, Liu W et al. Once-weekly micafungin therapy is as effective as daily therapy for disseminated candidiasis in mice with persistent neutropenia. Antimicrob Agents Chemother 2007; 51: 968– 74. http://dx.doi.org/10.1128/AAC.01337-06 Google Scholar CrossRef Search ADS PubMed 43 Lepak A, Marchillo K, VanHecker J et al. Efficacy of extended-interval dosing of micafungin evaluated using a pharmacokinetic/pharmacodynamic study with humanized doses in mice. Antimicrob Agents Chemother 2016; 60: 674– 7. http://dx.doi.org/10.1128/AAC.02124-15 Google Scholar CrossRef Search ADS 44 Lakota EA, Bader JC, Ong V et al. Pharmacological basis of CD101 efficacy: exposure shape matters. Antimicrob Agents Chemother 2017; 61: pii=e00758-17. 45 Hall D, Shinabarger DL, Pillar CM et al. Evaluation of the fungicidal activity of CD101, a novel echinocandin, and comparators against recent clinical isolates of Candida spp. In Abstracts of the 55th Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, CA, 2015. Abstract M-825. American Society for Microbiology. 46 Sandison T, Ong V, Lee J et al. Safety and pharmacokinetics of CD101 IV, a novel echinocandin, in healthy adults. Antimicrob Agents Chemother 2017; 61: e01627– 16. Google Scholar CrossRef Search ADS PubMed 47 Lepak AJ, Zhao M, VanScoy BA et al. In vivo pharmacokinetic/pharmacodynamic (PK/PD) target characterization of the novel, long acting echinocandin CD101 against C. albicans and C. glabrata in the neutropenic murine disseminated candidiasis model. In: Abstracts of the Infectious Diseases Society of America IDWeek, San Diego, CA, USA, 2017. Abstract 1528. Infectious Diseases Society of America, Arlington, VA, USA. 48 Pfaller MA, Messer SA, Rhomberg PR et al. Activity of a long-acting echinocandin (CD101) and seven comparator antifungal agents tested against a global collection of contemporary invasive fungal isolates in the SENTRY 2014 antifungal surveillance program. Antimicrob Agents Chemother 2016; 61: e02045– 16. 49 Hiemenz J, Cagnoni P, Simpson D et al. Pharmacokinetic and maximum tolerated dose study of micafungin in combination with fluconazole versus fluconazole alone for prophylaxis of fungal infections in adult patients undergoing a bone marrow or peripheral stem cell transplant. Antimicrob Agents Chemother 2005; 49: 1331– 6. http://dx.doi.org/10.1128/AAC.49.4.1331-1336.2005 Google Scholar CrossRef Search ADS PubMed 50 Sirohi B, Powles RL, Chopra R et al. A study to determine the safety profile and maximum tolerated dose of micafungin (FK463) in patients undergoing haematopoietic stem cell transplantation. Bone Marrow Transplant 2006; 38: 47– 51. http://dx.doi.org/10.1038/sj.bmt.1705398 Google Scholar CrossRef Search ADS PubMed 51 Hall RG, Swancutt MA, Gumbo T. Fractal geometry and the pharmacometrics of micafungin in overweight, obese, and extremely obese people. Antimicrob Agents Chemother 2011; 55: 5107– 12. http://dx.doi.org/10.1128/AAC.05193-11 Google Scholar CrossRef Search ADS PubMed 52 Bruggemann RJ, Van Der Velden WJ, Knibbe CA et al. A rationale for reduced-frequency dosing of anidulafungin for antifungal prophylaxis in immunocompromised patients. J Antimicrob Chemother 2015; 70: 1166– 74. Google Scholar PubMed © The Author 2018. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: email@example.com.
Journal of Antimicrobial Chemotherapy – Oxford University Press
Published: Jan 1, 2018
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