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Pediatr Pulmonol. Author manuscript; available in PMC 2012 October 24.
Published in final edited form as:
PMCID: PMC3479399
NIHMSID: NIHMS254911

Randomized Trial of Biofilm Testing to Select Antibiotics for Cystic Fibrosis Airway Infection*

SUMMARY

Rationale

In cystic fibrosis (CF), conventional antibiotic susceptibility results correlate poorly with clinical outcomes. We hypothesized that biofilm testing would more accurately reflect the susceptibilities of bacteria infecting CF airways.

Methods

A multi-center randomized pilot trial was conducted to assess the efficacy and safety of using biofilm susceptibility testing of Pseudomonas aeruginosa sputum isolates to guide antibiotic regimens for chronic airway infections in clinically stable adolescent and adult CF patients. Thirty-nine participants were randomized to biofilm or conventional treatment groups; 14-day courses of two antibiotics were selected according to an activity-based algorithm using the corresponding susceptibility results.

Results

Of the agents tested, meropenem was most active against biofilm-grown bacteria, and was included in regimens for about half of each study group. For nineteen of 39 randomized participants, randomization to the other study group would not have changed the antibiotic classes of the assigned regimen. Study groups were comparable at baseline, and had similar mean decreases in bacterial density, measured in log10 colony forming units per gram of sputum (biofilm, -2.94 [SD 2.83], versus conventional, -3.27 [SD 3.09]), and mean increases in forced expiratory volume in one second, measured in liters (0.18 [SD 0.20] versus 0.12 [SD 0.22]).

Conclusions

In this pilot study, antibiotic regimens based on biofilm testing did not differ significantly from regimens based on conventional testing in terms of microbiological and clinical responses. The predictive value of biofilm testing may nonetheless warrant evaluation in an adequately powered clinical trial in younger CF patients or those experiencing acute pulmonary exacerbation.

Keywords: Pseudomonas aeruginosa, intravenous antibiotics, antibiotic resistance, antibiotic susceptibility testing, broth microdilution testing, inhibitory quotient, sputum bacterial density, lung function

INTRODUCTION

Individuals with cystic fibrosis (CF) have chronic endobronchial infections punctuated by recurrent acute exacerbations, with progressive lung damage and premature death. Pseudomonas aeruginosa is the single most important pathogen in CF. Approximately 55% of CF patients overall and more than 75% of patients ≥ 18 years are infected with this organism.1,2 Surveillance cultures of airway secretions yield a mean of ~2.5 morphologically distinct isolates of P. aeruginosa per patient.3 Intravenous and inhaled antibiotics are mainstays of CF therapy; multi-drug combinations improve efficacy and minimize emergence of antibiotic resistance.4 However, resistance remains an important clinical problem. For example, the prevalence of tobramycin-resistant P. aeruginosa has increased from 11.8% to 30.4% over the past decade.3,5

Despite evidence that conventional susceptibility results do not reliably predict treatment responses in CF,6,7 current guidelines recommend that these be used to guide antibiotic selection.8 However, conventional susceptibility methods approved by the Clinical Laboratory Standards Institute (CLSI)9 do not account for the ability of P. aeruginosa to form biofilms within CF airways,10 or the marked differences in susceptibility of planktonic versus biofilm-grown P. aeruginosa.11

P. aeruginosa biofilms display marked resistance to antibiotics commonly used to treat CF airway infections.12,13 Bacterial cells in biofilms are generally slowly dividing, thus use of log phase cells in conventional susceptibility testing may not reflect the susceptibility of P. aeruginosa within CF airways. To evaluate the anti-biofilm activity of available antibiotics, clinically feasible biofilm susceptibility methods have been developed.11,14,15

The specific aims of this pilot study were to assess the safety and measure the microbiological and pulmonary effects of using anti-biofilm activity to assign antibiotic regimens for chronic CF airway infection. These aims were achieved by performing a randomized controlled trial of antibiotic regimens assigned on the basis of biofilm susceptibility testing as compared to conventional testing. The hypothesis was that participants receiving antibiotics based on anti-biofilm activity would have a greater decrease in P. aeruginosa sputum density than those receiving treatment based on conventional activity.

MATERIALS AND METHODS

Participants were enrolled between February 2004 and October 2007 at seven US CF centers: Nationwide Children's Hospital (Columbus, Ohio), Children's Hospital of Pittsburgh (Pittsburgh, Pennsylvania), Washington University (St. Louis, Missouri), Baylor College of Medicine (Houston, Texas), the University of Iowa (Iowa City, Iowa), University Hospital (Cincinnati, Ohio), Seattle Children's Hospital (Seattle, Washington), and the University of Washington Medical Center (Seattle, Washington). The IRB at each site approved the protocol and amendments. Participants provided written informed consent (and assent when applicable). Inclusion and exclusion criteria were as described in Supplementary Material.

Sputum samples obtained at Visit 1 (Day -21 to -14) were cultured quantitatively.3 For each P. aeruginosa morphotype present at ≥10% of the most prevalent, antibiotic susceptibilities were determined by semi-automated broth microdilution3 (Sensititre System, AccuMed, Westlake, Ohio) and biofilm susceptibility testing.11 Multiresistance was defined as resistance to all agents in at least two of three classes (aminoglycosides, fluoroquinolones, beta-lactams) by either conventional or biofilm testing, based on CLSI breakpoints.16

Conventional and biofilm regimens of two antibiotics were selected centrally using a published algorithm,17 with not more than one drug from each antibiotic class, as follows: aminoglycosides (amikacin, tobramycin); beta-lactams (ceftazidime, meropenem, piperacillin-tazobactam, ticarcillin-clavulanate); fluoroquinolones (ciprofloxacin); macrolides (azithromycin). For each bacterial morphotype, the algorithm calculated the conventional minimum inhibitory quotient (MIQ) and the biofilm minimum inhibitory quotient (BIQ) of each drug, defined as achievable serum concentration divided by conventional or biofilm minimum inhibitory concentration (MIC or BIC), respectively. For each subject's isolate set, MIQ and BIQ composite scores were used to rank antibiotics from most to least active. For each testing method, the two most active drugs from different antibiotic classes were selected. When the most active antibiotics had the same composite scores, a tiebreaker rule based on ease of administration, cost, and likelihood of adverse drug reaction was applied (hierarchy, most to least preferred: azithromycin, ciprofloxacin, ceftazidime, meropenem, ticarcillin-clavulanate, piperacillin-tazobactam, tobramycin, amikacin). To define drug allergies, the beta-lactams were subdivided into penicillin, cephalosporin, and carbapenem subclasses. If a participant had a history of allergic reaction, that class or subclass of antibiotics was excluded from potential assignment.

Participants were assigned to treatment groups using a block randomization procedure, stratified by study site. Participants and site personnel were informed of antibiotic assignments, but were not told the testing method (conventional or biofilm) on which this was based. The effectiveness of this blinding was not evaluated.

At Visit 2 (Day 0), spirometry was performed,18 and participants started on a 14-day course of their assigned antibiotic regimen; recommended dosing was as described in Supplementary Material. Participants assigned to regimens that included an IV antibiotic had the option of home IV therapy (OptionCare, Buffalo Grove, Illinois) or admission to a General Clinical Research Center; all such participants who initiated treatment received the majority of the 14-day course at home. Visit 3 (Day 7 +/- 2 days) was an interim visit or telephone call to monitor adverse events and review medication use. Visit 4 (Day 14 +/- 2 days) was timed to occur 12–48 hours after the last antibiotic dose, a time at which residual concentrations in airway secretions were deemed unlikely to affect bacterial growth. A sputum sample was collected for quantitative culture and spirometry was performed.

The primary outcome measure was microbiological response, change in P. aeruginosa sputum density, calculated as log10 of end-of-treatment density minus log10 of screening density, in CFU/g. The secondary outcome measure was pulmonary response, change in forced expiratory volume in one second (FEV1), calculated as end-of-treatment FEV1 minus the baseline FEV1, in liters.

A CF Foundation Data Monitoring Committee conducted one interim review to assess study conduct and safety. A ≥10% rate of acute pulmonary exacerbation or need to change antibiotics in either treatment group was the pre-specified threshold for considering early study termination.

This pilot trial was designed to determine feasibility and estimate treatment effect and variability for planning a full-scale trial; owing to cost constraints, it was not powered to detect significant differences in microbiological or clinical efficacy between treatment groups. The target sample size was 20 randomized participants in each treatment group. Outcomes were analyzed using linear regression models that adjusted for baseline values, defined as sputum density measured at screening and FEV1 measured at initiation of antibiotic treatment. Analyses were performed using STATA™ (versions 9.2 and 10.0, College Station, TX) and S-plus (version 6.2, Insightful Corp., Seattle); modified intent-to-treat comparisons included all randomized participants who received at least one dose of their assigned regimen.

RESULTS

Enrollment and randomization

The flow of participants through the protocol is shown in Figure 1. Forty randomizations resulted in 39 participants assigned to treatment. One individual was randomized but withdrawn prior to treatment and subsequently re-randomized and treated; data from the completed treatment course are included here. One participant from each group discontinued treatment due to adverse events. Study groups were comparable at baseline with regard to age, race, genotype, pancreatic status, baseline lung function, and P. aeruginosa density and morphotype number (Table 1). The proportion of males was higher in the biofilm group.

Figure 1
Flow of participants through each stage of the protocol
Table 1
Baseline characteristics of randomized subjects, by study group.

Susceptibility testing results

Susceptibility results were analyzed in terms of both inhibitory concentrations and inhibitory quotients; the latter represents a normalization of the former to enable direct comparison of activities for different antibiotics. The inhibitory quotient (defined under “Methods”) is the converse of the inhibitory concentration, in that a higher inhibitory quotient indicates higher activity of a given drug against the set of tested organisms. Biofilm and conventional testing of P. aeruginosa isolates at screening indicated that most agents were less active against biofilm-grown organisms (Table 2). Meropenem was most active against biofilms, while piperacillin/tazobactam and meropenem were most active against planktonic organisms. In this set of isolates from CF adults, azithromycin showed poor activity by both methods, in contrast to the previous finding of good anti-biofilm activity against isolates from younger patients.11 The largest fold-difference between biofilm and conventional testing was for piperacillin/tazobactam (16-fold more active against planktonic organisms). Lesser differences were seen for ceftazidime (8-fold) and meropenem (4-fold). Six participants (three in each arm) had at least one multiresistant isolate; all three with a conventionally multiresistant isolate also had biofilm multiresistance.

Table 2
Antibiotic susceptibilities of P. aeruginosa isolated at screening from subsequently randomized subjects.

Antibiotic combinations

Participants were assigned to only 12 of 21 potential regimens (Table 3). The most frequent regimens included meropenem (52%) and ciprofloxacin (49%). Azithromycin-containing regimens were used for only 2 participants (5%), both in the biofilm group. No participant received ceftazidime and tobramycin, a combination commonly used in CF clinical practice; moreover, this combination would have been the biofilm regimen for only a single participant randomized to the conventional group, and would not have been the conventional regimen for any participant randomized to the biofilm group.

Table 3
Antibiotic regimens by study group.

For each participant, the treatment regimens based on each method were categorized according to drug class or subclass, and cross-tabulated (not shown). The observed agreement between drug class combinations selected by BIC and MIC methods was 49%. Of the 19 participants who would have received the same drug class combinations had they been assigned to the other study group, six received meropenem/ciprofloxacin and five each received meropenem/aminoglycoside or anti-pseudomonal penicillin/ciprofloxacin.

Microbiological and clinical outcomes

Changes in sputum density (primary outcome) and FEV1 (secondary outcome) were analyzed under a modified intent-to-treat principle, with inclusion of all participants who received at least one dose of their assigned regimen (Table 4). For all participants combined, the mean change in sputum density from baseline to end of treatment was -3.09 log10 CFU/g (95% CI, -4.15 to -2.02). For biofilm group relative to conventional group, the estimated treatment effects were 0.28 log10 CFU/g (95% CI, -1.98 to 2.54) for P. aeruginosa sputum density (i.e., the decrease in density was numerically greater in the conventional group) and 0.07 L (95% CI, -0.08 to 0.22) for FEV1 (i.e., the increase in FEV1 was numerically greater in the biofilm group), after adjustment for baseline values; these numerical differences were not statistically significant. Because the baseline sputum densities were somewhat imbalanced between groups (Table 1), the adjusted estimates of treatment effect shown in Table 4 were considered more conservative than unadjusted estimates. No within-participant relationship between changes in sputum density and FEV1 was discerned (data not shown). Among the 31 participants with microbiological endpoint data (17 in biofilm group, 14 in conventional group), 23 had ≥1 log10 CFU/g decrease in sputum density (13 in biofilm group, 10 in conventional group), and P. aeruginosa was not detected at the end of study in 7 of these (4 in biofilm group, 3 in conventional group). Lack of detectable P. aeruginosa at end of study did not correlate with initial sputum density (6.70 log10 CFU/g, vs 7.67 for non-eradicators), mucoidy of isolates on initial culture, or antibiotic combination received (data not shown).

Table 4
Changes in Pseudomonas sputum density and FEV1, by study group.

Among participants with microbiological endpoint data, a post-hoc analysis compared those infected with at least one multiresistant isolate (n=5) and those infected with only susceptible isolates (n=26), irrespective of study group assignment. The change in P. aeruginosa sputum density for these post-hoc groups was comparable: -3.4 log10 CFU/g (SD 1.5) versus -3.0 log10 CFU/g (SD 3.1), respectively.

A second post-hoc analysis compared those receiving two IV agents (i.e., beta-lactam plus aminoglycoside, n=15) and those receiving a single oral agent (i.e., ciprofloxacin or azithromycin) plus a single IV agent (n=18; 15 with microbiological endpoint data), irrespective of study group assignment. For the former, the change in sputum density was -4.0 log10 CFU/g (SD 2.5), whereas for the latter it was -2.2 log10 CFU/g (SD 3.2) (p=0.09). This trend toward a significant difference was not seen for lung function (data not shown).

Safety

Seventy treatment-emergent adverse events were reported (33 in biofilm group, 37 in conventional group). Thirteen participants in each group experienced ≥1 adverse event. No adverse event was judged serious. The most commonly reported adverse events were diarrhea (n=6), fatigue (n=6), headache (n=5), and oral candidiasis (n=4).

DISCUSSION

This pilot study of adults and adolescents with clinically stable CF airway infection confirmed the feasibility and safety of assigning systemic antibiotic regimens based on biofilm testing, and demonstrated an effect on P. aeruginosa sputum density and FEV1 comparable to treatment based on conventional testing. Its failure to detect differences in outcome between the biofilm and conventional groups may be attributable to several factors, including small sample size (thus limiting statistical power), the clinical stability (i.e., lack of pulmonary exacerbations) of the participants, and the antibiotic susceptibilities of P. aeruginosa with which they were infected. Potentially compounding this last factor is the extreme variability of sputum antibiograms in individual CF patients with chronic P. aeruginosa infection, wherein morphologically indistinguishable isolates can exhibit markedly variable resistance phenotypes (on average, three antibiograms per morphotype).19

A previous retrospective study of P. aeruginosa from younger patients demonstrated marked differences between biofilm and conventional susceptibilities.11 In the present study, differences between biofilm and conventional susceptibilities were less substantial, and for half of those randomized, being switched to the other study group would not have changed either of the assigned drug classes. We surmise that as patients age, repeated antibiotic exposure of their individual strains results in selection of subclones with diminished planktonic and biofilm susceptibility (or more consistently detectable resistance) across all drug classes. Thus, even an adequately powered study of older CF patients at clinical baseline might not detect a differential treatment effect of biofilm and conventional regimens. Nonetheless, this study provides data enabling the statistical power of IV antibiotic trials in this patient population (clinically stable adults with CF) to be calculated with precision for the first time.

In this study, FEV1 % predicted improved 7.4% relative to baseline for all participants combined, similar to the effect of inhaled antibiotics.20,21P. aeruginosa sputum density decreased ~3 log10 CFU/g in both study groups (which is greater than the microbiological effect of inhaled antibiotics),20,21 and also in a post-hoc group with multiresistant isolates. More surprisingly, for 7 of 39 participants (18%), P. aeruginosa was not detected at end of treatment. For CF clinicians who question the prevailing US approach of using IV antibiotics only during acute pulmonary exacerbations, these data suggest that elective IV therapy may be warranted in some clinically stable patients.

The microbiological response observed in both study groups and in those with multiresistant isolates may have reflected our approach to assigning antibiotics based on drug activity. We used a selection algorithm that prioritized drugs according to inhibitory quotient, which compares achievable serum concentration to in vitro susceptibility.17 Thus, we picked the drugs for which the MIC or BIC of the isolates was the farthest below the corresponding achievable serum concentration. Meropenem was highly active against both planktonic and biofilm-grown bacteria, and was included in about half of the regimens in each study group. Although historically popular as a first-line regimen, the combination of ceftazidime and tobramycin was not assigned during the study. This may presage a clinical trend towards decreasing ceftazidime use and increasing meropenem use, owing to the greater activity of the latter against contemporary CF isolates.22

Use of the pharmacodynamic concept of drug activity, which is seldom implemented in chronic CF airway infection, was intended to avoid bias associated with choosing drugs based on clinical judgment or arbitrary guidelines. Drug activity also accounts for potential sub-inhibitory or supra-inhibitory antibiotic effects that dichotomization of susceptibility results (i.e., interpretation as “susceptible” or “resistant”) may obscure. To implement this approach, clinical laboratories that perform broth microdilution or Etest would simply report the raw susceptibility data; a publicly available computer-based algorithm would then be used to calculate inhibitory quotients and assign drug regimens.17

In CF patients with acute exacerbation of non-multiresistant P. aeruginosa airway infection, randomized trials of single drugs or two-drug combinations have demonstrated decreases of 1 to 5 log10 CFU/g,4,22-24 with particularly favorable effects observed for meropenem.22 In contrast, in multiresistant P. aeruginosa infection, both a retrospective study of clinically assigned regimens and a randomized controlled trial of regimens based on multiple combination bactericidal testing (MCBT) have shown only minor decreases in sputum bacterial density.25,26 Moreover, a post-hoc analysis of participants in the placebo arm of the inhaled tobramycin trial treated for acute exacerbation found no correlation between MIC results and changes in FEV1; sputum bacterial density was not examined.6 Such studies have cast doubt on whether susceptibility testing can predict clinical outcomes, leading some to suggest that CF clinicians should forego susceptibility testing altogether.7,27

To assume that growth of biofilms in a 96-well plate in the clinical laboratory can adequately represent the complex biochemical milieu and microbial ecology that shape CF airway infection would be naïve. The structure and physiology of biofilms in the CF airway probably reflect various factors (e.g., bacterial alginate, neutrophil DNA, respiratory mucins) that may be difficult to simulate in current testing systems.28 However, post-hoc analysis of isolates from the MCBT trial suggests that biofilm testing might improve microbiological and clinical outcomes in CF airway infection.29 That analysis compared outcomes according to whether biofilms formed by isolates cultured from adults with CF at onset of acute exacerbation were susceptible to the agents with which they had been treated. Participants with at least one biofilm-susceptible isolate (n=61) had significant decreases in sputum bacterial density (p=0.02) and length of stay (p=0.04), and trends toward less treatment failure and prolonged time to next exacerbation, compared to those with none (n=49). Conversely, post-hoc analysis of isolates from an inhaled tobramycin eradication trial performed in CF patients <6 yrs at clinical baseline with recent acquisition of P. aeruginosa30 showed that initial isolates from children in whom eradication failed had higher tobramycin BICs than those in whom eradication occurred, despite similar initial tobramycin MICs in both groups, suggesting that biofilm testing may predict those at risk of treatment failure (Lucas Hoffman, Jessica Foster, S.M.M., J.C.E., J.L.B., and R.L.G., unpublished results). Taken together, these findings suggest that adequately powered trials are needed to evaluate whether biofilm susceptibility testing has predictive value for CF adults experiencing acute exacerbation of chronic P. aeruginosa airway infection, as well as for clinically stable younger patients with recent acquisition of P. aeruginosa.

Supplementary Material

on-line supplement

ACKNOWLEDGMENTS

The authors acknowledge the vital work of the Biofilm Study Research Coordinators: Laura Raterman and Terri Johnson, Nationwide Children's Hospital, Columbus, OH; Elizabeth Hartigan, Children's Hospital of Pittsburgh, PA; Mary Boyle, Washington University School of Medicine, St. Louis, MO; Suzanne Cummings, Baylor College of Medicine, Houston, TX; Mary Teresi and Cheri Lux, University of Iowa, Iowa City, IA; Melenie Meyers, University Hospital, Cincinnati, OH; and Alan Genatossio, Seattle Children's Research Institute, Seattle, WA. The authors thank the following for their contributions to the study: Jessica Foster, Janine Jijina, Maxine Smith, Molly Andrina, Emily Sasnett, Jenny Stapp, Anne Marie Buccat, Adam Griffith, Morty Cohen, Lucas Hoffman, Chris Goss, Bonnie Ramsey, Wayne Morgan, and Option Care Inc. (now Walgreens-OptionCare).

Funding. This study was supported through a Clinical Research Grant from the Cystic Fibrosis Foundation (BURNS03A0), as well as Clinical and Translational Science Center and General Clinical Research Center Awards from the National Center for Research Resources (UL1 RR025014 and M01 RR000037 – University of Washington, Seattle; UL1 RR025755 and M01 RR000034 – Ohio State University, Columbus; UL1 RR024153 and M01 RR000084 – University of Pittsburgh; UL1 RR024992 and M01 RR000036 – Washington University, St. Louis; M01 RR000188 – Baylor College of Medicine, Houston; UL1 RR024979 and M01 RR000059 – University of Iowa; UL1 RR026314 – University of Cincinnati; and M01 RR008084 – Children's Hospital Medical Center, Cincinnati). S.M.M. was supported in part through a Clinician Scientist Career Development Award from the National Heart Lung and Blood Institute (K08 HL067903).

This work was performed at Barnes Jewish Hospital (St. Louis), Baylor College of Medicine (Houston), Children's Hospital of Pittsburgh of UPMC, Nationwide Children's Hospital (Columbus), Seattle Children's Hospital, University Hospital (Cincinnati), and University of Iowa Hospitals and Clinics (Iowa City).

The Cystic Fibrosis Foundation [Grant BURNS03A0], the National Heart Lung and Blood Institute [Grant K08HL067903 - Samuel M. Moskowitz, principal investigator], and the National Center for Research Resources [Grants UL1RR025014, M01RR000037, UL1RR025755, M01RR000034, UL1RR024153, M01RR000084, UL1RR024992, M01RR000036, M01RR000188, UL1RR024979, M01RR000059, UL1RR026314, and M01RR008084] provided funding for this study.

Abbreviations

BIC
biofilm inhibitory concentration
BIC50
50th percentile of biofilm inhibitory concentration
BIC90
90th percentile of biofilm inhibitory concentration
BIQ
biofilm inhibitory quotient
BIQ50
50th percentile of biofilm inhibitory quotient
BIQ90
90th percentile of biofilm inhibitory quotient
CF
cystic fibrosis
CFTR
CF transmembrane conductance regulator gene
CFU
colony forming units
CI
confidence interval
CLSI
Clinical Laboratory Standards Institute
FEF25-75
forced expiratory flow between 25% and 75% of FVC
FEV1
forced expiratory volume in one second
FVC
forced vital capacity
IRB
Institutional Review Board
IV
intravenous
log10
logarithm10
MCBT
multiple combination bactericidal testing
MIC
minimum inhibitory concentration
MIC50
50th percentile of minimum inhibitory concentration
MIC90
90th percentile of minimum inhibitory concentration
MIQ
minimum inhibitory quotient
MIQ50
50th percentile of minimum inhibitory quotient
MIQ90
90th percentile of minimum inhibitory quotient
SD
standard deviation

Footnotes

Some of the data in this manuscript were presented as part of a symposium at the 22nd annual North American Cystic Fibrosis Conference (Orlando, Florida) in October 2008.

Potential conflict of interest. S.M.M. serves as a consultant to Kala Pharmaceuticals, and has received honoraria from the France Foundation for speaking engagements. J.C.E., no conflict. S.McN., no conflict. R.D.S., no conflict. D.M.O., no conflict. D.R., no conflict. M.F.K. has received honoraria from Novartis, Genentech, and Gilead Sciences for speaking engagements and consulting, and has received funding from Gilead Sciences for clinical research. R.A. has received funding from Gilead Sciences, Boehringer-Ingelheim Pharmaceuticals, Transave, and Vertex for clinical research. D.H. has received honoraria from Pfizer and Boehringer-Ingelheim Pharmaceuticals for speaking engagements, and serves on advisory boards for Pfizer and Genentech. P.M.J., no conflict. R.L.G. has received funding from Gilead Sciences for clinical research. M.L.A. has received honoraria from the CF Foundation for speaking engagements, and has received funding from Transave, PTC Pharmaceuticals, Vertex, and Pharmaxis for clinical research. W.W.B. is an employee of Actelion Pharmaceuticals. J.L.B. has received funding from Transave, Gilead Sciences, Vertex, KaloBios, and Chiesi for clinical research.

Contributions of authors. S.M.M., J.C.E., and J.L.B. wrote the manuscript, and S.McN., R.D.S., D.M.O., D.R., M.F.K., R.A., D.H., P.M.J., and R.L.G. edited it. S.M.M., J.C.E., and J.L.B. had full access to all of the data in the study and take full responsibility for the integrity of all of the data and the accuracy of the data analysis, including all adverse effects.

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