The concentration-dependent nature of in vitro amphotericin B–itraconazole interaction against Aspergillus fumigatus: isobolographic and response surface analysis of complex pharmacodynamic interactions

International Journal of Antimicrobial Agents 28 (2006) 439–449

The concentration-dependent nature of in vitro amphotericin B–itraconazole interaction against Aspergillus fumigatus: isobolographic and response surface analysis of complex pharmacodynamic interactions Joseph Meletiadis a,∗ , Debbie T.A. te Dorsthorst b , Paul E. Verweij b b

a National Cancer Institute, Pediatric Oncology Branch, Bethesda, MD, USA Department of Medical Microbiology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands

Received 8 February 2006; accepted 11 May 2006

Abstract The interaction between polyenes and azoles is not well understood. We therefore explored the in vitro combination of amphotericin B with itraconazole against 14 clinical Aspergillus fumigatus isolates (9 itraconazole susceptible and 5 itraconazole resistant) with a colorimetric broth microdilution checkerboard technique using two drug interaction models able to explore complicated patterns of interactions: the response surface analysis of Bliss independence and the isobolographic analysis of Loewe additivity zero interaction theories. Synergy was found at combinations with low concentrations of amphotericin B (<0.125 mg/L), whereas antagonism was found at combinations with higher concentrations of amphotericin B. For itraconazole-resistant isolates, synergistic interactions were observed at high concentrations of itraconazole (>0.5 mg/L). Synergy was more frequently observed for the itraconazole-resistant isolates than for the itraconazole-susceptible isolates. © 2006 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved. Keywords: Antifungal interaction; Isobolography; Synergy and antagonism; Bliss independence; Loewe additivity; Response surface analysis

1. Introduction Combination therapy with polyenes and azoles is frequently used for treating invasive aspergillosis, although its merit is vague [1]. It was initially assumed that this combination might be antagonistic because azoles inhibit biosynthesis of membrane ergosterol, the target of polyenes [2]. However, the interaction between polyenes and azoles appears to be more complicated [1,3] since (i) polyenes may interfere with a cell membrane-associated permease likely to be involved in azole entry into the cell [4], (ii) membrane damage caused by ∗ Corresponding author. Present address: Bg.10/CRC Rm.1C-5750, 10 Center Drive MSC 1100, Pediatric Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Tel.: +1 301 451 7036; fax: +1 301 480 2308. E-mail address: [email protected] (J. Meletiadis).

polyenes may interfere with azole influx [5] and (iii) accumulation of azoles in the cell membrane may prevent polyenes binding to ergosterol [6,7]. On the other hand, synergistic interactions were explained by increased azole influx due to polyene-induced damage to the cell membrane [8]. Given the expected complexity of polyene–azole interactions, we investigated the in vitro combination of amphotericin B with itraconazole against itraconazole-susceptible and -resistant Aspergillus fumigatus isolates with two powerful drug interaction models capable of detecting complicated types of pharmacodynamic drug interactions: the response surface analysis of Bliss independence and the isobolographic analysis of Loewe additivity [9]. The Bliss independence zero interaction theory is based on the assumption that two drugs that do not interact will act independently in a probabilistic sense and therefore effects of non-interactive drug combinations can be calculated with the probability law for

0924-8579/$ – see front matter © 2006 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved. doi:10.1016/j.ijantimicag.2006.07.011

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joint independent events [10,11]. On the other hand, Loewe additivity is based on the idea that a drug, by definition, cannot interact with itself and therefore effects of non-interactive combinations can be calculated as if the drugs were simple dilutions of each other [12]. Both models were recently found to correlate well with the in vivo results of combination therapy for treating experimental invasive pulmonary aspergillosis [13] and therefore their results could help to optimise polyene–azole combination therapy.

2. Materials and methods 2.1. Isolates Fourteen clinical isolates of A. fumigatus from the private collection of the Department of Medical Microbiology, Radboud University Nijmegen Medical Center, Nijmegen, were tested. These included nine itraconazole-susceptible (ITCS) isolates (AZN 5161, AZN 7151, AZN 7319, AZN 7820, AZN v02-31, AZN v02-32, AZN v02-33, AZN v02-40 and AZN v02-41) and five itraconazole-resistant (ITC-R) isolates (AZN 58, AZN 59, AZN 5241, AZN 5242 and AZG 7). The isolates were kept at −70 ◦ C in 50% glycerol and revived by subculturing twice on potato flake agar at 35 ◦ C for 5–7 days. All tests were performed in triplicate. Candida parapsilosis (ATCC 22019) and Candida krusei (ATCC 6258) were used for quality control in all experiments. 2.2. Antifungal agents Amphotericin B (AMB) (Bristol-Myers Squibb, Woerden, The Netherlands) and itraconazole (ITC) (Janssen Pharmaceutica B.V., Tilburg, The Netherlands) were obtained as pure powders and dissolved in dimethyl sulfoxide at a concentration of 6.400 mg/L. 2.3. Medium RPMI 1640 (with l-glutamine, without bicarbonate) (GIBCO BRL, Life Technologies, Woerden, The Netherlands) buffered to pH 7.0 with 0.165 M morpholinepropanesulfonic acid (MOPS) (Sigma–Aldrich Chemie GmbH, Steinheim, Germany) was used throughout. 2.4. Inoculum Conidial suspensions from 5–7-day-old cultures were adjusted spectrophotometrically at 80–82% transmittance according to Clinical and Laboratory Standards Institute (CLSI) guidelines [14] and were further diluted in RPMI 1640 medium containing 0.2 mg/mL 3-(4,5-dimethyl2-thiazyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) (Sigma Chemical, St Louis, MO). The final inoculum size ranged from 0.4 × 104 colony-forming units (CFU)/mL to 5 × 104 CFU/mL.

2.5. Combination studies The interaction of AMB and ITC was tested with a twodimensional 12 × 12 checkerboard broth microdilution technique in 96-well flat-bottom microtitre plates (Costar, Corning, NY) as described elsewhere [15]. Briefly, drugs were two-fold serially diluted in the test medium according to the CLSI guidelines [14] to obtain four times the final concentrations. Fifty microlitres of each concentration of AMB and its drug-free control was combined with 50 ␮L of each concentration of ITC and its drug-free control. The plates were stored at −70 ◦ C and thawed on the day of the experiment when 100 ␮L of inoculum was added to each well. Thus, the final concentration of both drugs ranged from 16 mg/L to 0.016 mg/L, with the last column and the last row containing only ITC and AMB, respectively. 2.6. Susceptibility testing After inoculation, microtitre plates were incubated at 35 ◦ C for 48 h and growth in each well was quantified by a modified colorimetric method employing the dye MTT as described previously [16]. Briefly, the content of each well was removed and 200 ␮L of isopropanol containing 5% of 1 N HCl was added to each well. After 30 min of incubation at room temperature and gentle agitation for 10 s every 10 min, the absorbance at 550 nm (A550 ) of each well was measured with a microtitration plate reader (Anthos htIII; Anthos Labtec Instruments, Salzburg, Austria). The percentage of growth in each well was calculated based on the following equation: (A550 of a well – background A550 )/(A550 of the drug-free well – background A550 of the drug-free well) × 100%, where the background A550 values were measured from a plate inoculated with a conidia-free inoculum and handled in the same way as the inoculated plates with the conidia-containing inocula. The minimal inhibitory concentrations (MICs) for AMB and ITC were defined as the lowest drug concentrations showing <10% of growth. 2.7. Regression analysis The checkerboard data were analysed with a previously described non-weighted, non-linear regression analysis using GraphPad Prism software (San Diego, CA) [15]. The Emax model was fitted to the concentration–effect curves of each drug alone (last column and row of the checkerboard for ITC and AMB, respectively) and their combinations at the AMB:ITC fixed ratios of 1:16, 1:8, 1:4, 1:2, 1:1, 2:1, 4:1, 8:1 and 16:1 based on drug weights. For example, for the 1:1 fixed ratio, the combinations with equal amount of both drugs were chosen (i.e. the diagonal of the 12 × 12 checkerboard), whilst for the 1:16 ratio the combinations of 1 mg/L of AMB and 16 mg/L of ITC, 0.5 mg/L of AMB and 8 mg/L of ITC, 0.25 mg/L of AMB and 4 mg/L of ITC etc., were chosen. The Emax model is described by the following equation: E = Emax × (C/EC50 )m /[1 + (C/EC50 )m ], where E is the

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percentage of growth (dependent variable) at the drug concentration C (independent variable), Emax is the maximum percentage of growth observed in the drug-free control, EC50 is the drug concentration producing 50% of the Emax and m is the slope of the concentration–effect curves (Hill coefficient). The maximum and minimum of the Emax model were kept constant at 100% and 0%, respectively. The goodness of fit of the model was interpreted using the runs test, residuals and R2 values, and poor fits (e.g. r2 < 0.9, 95% confidence interval (CI) > 1 log2 , statistically significant deviation of residuals from a normal distribution with mean 0 and statistically significant deviation based on runs test) were excluded from the analysis. 2.8. Pharmacodynamic drug interaction models

441

Bliss independence was concluded. When E of all combinations (11 × 11) for a particular isolate was plotted in a three-dimensional plot, an interaction surface plot can be obtained, with volumes above and below the 0 plane indicating synergistic and antagonistic combinations, respectively, whilst the 0 plane itself indicates no statistically significant interactions. To summarise the whole interaction surface for each isolate, the mean, sum and number of all statistically significant positive (synergistic interactions) and negative (antagonistic interactions) E values were calculated [15]. Finally, the median and range of drug concentrations of AMB and ITC at synergistic and antagonistic interactions were determined and the differences were assessed statistically with the Mann–Whitney U-test.

The interaction of AMB and ITC was assessed for each isolate with two different models based on two different zero interaction theories: the response surface analysis of Bliss independence zero interaction theory and the isobolographic analysis of Loewe additivity zero interaction theory [17]. Both models can detect synergy and antagonism within a data set enabling the investigation of concentration-dependent interactions.

2.8.2. Isobolographic analysis of Loewe additivity The interaction of AMB and ITC at each fixed-ratio combination was assessed for each isolate and replicate with the isobolographic analysis of Loewe additivity zero interaction theory [17]. Loewe additivity is described by the following equation:

2.8.1. Response surface analysis of Bliss independence Bliss independence is described by the equation

where cA and cB are the concentrations of the drugs A and B in the combination that elicit a certain effect, and ECA and ECB are the isoeffective concentrations of the drugs A and B acting alone. Isobolographic analysis is based on comparison of the concentration–effect curves of the drugs in combination with the theoretical concentration–effect curve if the drugs were acting additively (Fig. 1). Based on isobolographic analysis [18], for each fixed-ratio combination of AMB and ITC, the total concentration ECmix is compared with the isoeffective theoretical additive total concentration ECadd . The Emax model provides for each fixed-ratio combination an estimate of the total concentration ECmix = cAMB + cITC (cAMB and cITC are the concentrations of AMB and ITC in the combination, respectively) together with its standard error SE(ECmix ) for a specified growth level (e.g. 20%, 50% or 80% of Emax ). The theoretical additive concentration ECadd for the same growth level is calculated from Eq. (2) by substituting cA = cAMB = PAMB * ECadd , cB = cITC = PITC * ECadd , ECA = ECAMB and ECB = ECITC where PAMB and PITC are the proportions of AMB and ITC in the total concentration ECmix (e.g. for the fixed ratio 1:2 of AMB:ITC the corresponding proportions PAMB of AMB and PITC of ITC are 1/3 and 2/3, respectively), and ECAMB and ECITC are the isoeffective concentrations of AMB and ITC alone, respectively, obtained from the Emax model of the concentration–effect curves of the drugs alone [18]. After rearrangement, the equation

Iind = IA + IB − IA × IB

(1)

for a certain combination of x mg/L of drug A and y mg/L of drug B. IA is the percentage growth inhibition at x mg/L of drug A acting alone, IB is the percentage growth inhibition at y mg/L of drug B acting alone and Iind is the expected percentage growth inhibition of a non-interactive (independent) theoretical combination of x mg/L of drug A with y mg/L of drug B [10]. Eq. (1) is equivalent to Eind = EA × EB (since E = 1 − I), where Eind is the expected theoretical percentage of growth that describes the effect of a combination where the drugs are acting independently and EA and EB are the experimental percentage of growth of each drug acting alone, respectively. The difference E between the predicted percentage of growth Eind and the experimentally observed percentage of growth Eobs describes the interaction at each combination of drug concentrations. For each combination of AMB with ITC in each of the independent replicate experiments, Eobs was subtracted from Eind . When the mean E was positive and its 95% CI did not include 0, statistically significant synergy was claimed for that specific combination of x mg/L of AMB with y mg/L of ITC since the combination resulted in less growth than that expected if the drugs were acting independently. When the mean difference was negative without its 95% CI overlapping 0, statistically significant antagonism was claimed since the combination resulted in more growth than that expected if the drugs were acting independently. In any other case,

1=

cB cA + , ECA ECB

ECadd =

ECAMB (PAMB + PITC × ECAMB /ECITC )

(2)

(3)

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Fig. 1. Schematic representation of the isobolographic analysis. The concentration–effect curves of drug A, drug B and the mixture of drug A–drug B at the fixed-ratio combinations 1:4 were obtained with nonlinear regression analysis of the experimental data. The theoretical additive concentration–effect curve for the fixed-ratio combination 1:4 of the two drugs was obtained by Eq. (3) (see text). At 80% of growth (low drug concentrations), the concentration–effect curve of the mixture is on the left of the additive one (ECmix < ECadd ) resulting in an interaction index < 1, which indicates synergy because less drug is required to obtain the same effect as if the two drugs were acting additively (A). At 50% of growth (intermediate drug concentrations), the concentration–effect curve of the mixture is superimposed on the additive one (ECmix = ECadd ) resulting in an interaction index of 1, which indicates additivity since the same amount of drug is required to obtain the same effect as if the two drugs were acting additively (B). At 20% of growth (high drug concentrations), the concentration–effect curve of the mixture is on the right of the additive one (ECmix > ECadd ) resulting in an interaction index > 1, which indicates antagonism because more drug is required to obtain the same effect as if the two drugs were acting additively (C). Black and grey circles correspond to the ECmix and ECadd , respectively.

is obtained, based on which ECadd can be calculated.The 95% CI of ECadd is calculated based on its standard error (SE), which is given by the following equation: SE(ECadd ) = {f 2 × [SE(ECAMB )]2 + 1/2

(1 − f )2 × [SE(ECITC )]2 }

where

f = PAMB /(PITC + PAMB × ECAMB /ECITC )

(4)

and the SE(ECAMB ) and SE(ECITC ) can be obtained from the Emax model of the concentration–effect curve of the drugs alone [18]. Eq. (4) relates the proportion P of the actual drug concentrations in a mixture to the fraction f of the respective unitary potencies ECAMB and ECITC , thus allowing for different potency ratios ECAMB /ECITC at different growth levels (for more details see [18]). For each replicate synergy was concluded when the ECmix is significantly less than ECadd , whereas antagonism was claimed when ECmix is significantly more than ECadd . In any other case, Loewe additivity is deemed for a particular fixed ratio at a specified growth level (Fig. 1). Because the drug concentrations are logarithmically distributed, the statistical significance of the differences was calculated based on the logarithms with a Student’s t-test. Log ECmix and SE(ECmix ) were obtained directly from the Emax model since regression analysis was performed using the loga-

rithms of the drug concentrations, log ECadd is the logarithm of Eq. (3) and its SE is given by the following equation: SE(log ECadd ) = SE(ECadd )/[ln(10) * ECadd )]. An interaction index I for each fixed ratio at a specified growth level was then calculated as the ratio ECmix /ECadd for each replicate [9]. If the I values for all three replicates of an isolate were statistically significantly smaller or greater than 1, synergy or antagonism, respectively, was concluded for that particular isolate. The isobolographic analysis was performed for 20%, 50% and 80% of growth to assess the interactions at high (close to the MIC), intermediate and low drug concentrations, respectively (Fig. 1). Finally, the AMB and ITC concentrations in the mixtures with the strongest synergy (smallest interaction index) and the strongest antagonism (greatest interaction index) were determined for each growth level and their differences were assessed statistically with the Kruskal–Wallis test followed by Dunn’s multiple comparison test using GraphPad Prism software.

3. Results 3.1. Drug susceptibility The MICs of the quality control isolates were within the reference ranges. The MICs of AMB for all isolates ranged from 0.5 mg/L to 2 mg/L with a median MIC of 1 mg/L. The MICs of ITC for ITC-S isolates ranged from 0.25 mg/L to 2 mg/L with a median MIC of 0.25 mg/L, whilst for ITC-R isolates the MICs of ITC were >16 mg/L. 3.2. Response surface analysis of Bliss independence The results of this analysis are summarised in Table 1 where the sum, mean and number of E of all statistically significant synergistic and antagonistic combinations are presented for the ITC-S and ITC-R isolates together with the median AMB and ITC concentrations where these interactions occurred. For all the isolates except one, both synergistic and antagonistic interactions occurred at different concentrations of AMB and ITC resulting in a mosaic of interactions as depicted in Fig. 2. For ITC-S isolates, more antagonistic interactions (sum E −230%, n = 14) were found than synergistic ones (sum E 24%, n = 3). For ITC-R isolates, the synergistic interactions (sum E 718%, n = 26) were stronger than the antagonistic ones (sum E −165%, n = 14) (Table 1). Antagonistic interactions were observed at median AMB concentrations ranging from 0.25 mg/L to 2 mg/L and were statistically significantly (P < 0.001) higher than the AMB concentration where synergistic interactions were found (0.02–0.06 mg/L) both for the ITC-S and ITC-R isolates (Table 1). For ITC, synergy and antagonism was found at similar concentrations for ITC-S isolates (0.03–0.5 mg/L), whereas for ITC-R isolates ITC concentrations of antagonistic combinations (median 0.13 mg/L, range 0.09–0.50 mg/L)

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Table 1 Results of Bliss independence response surface analysis: the sum, mean and number of statistically significant interactions (median and range among isolates) are presented together with the median (range) amphotericin B (AMB) and itraconazole (ITC) concentrations in combinations where these interactions occurred Isolates (n)

Interactions

Sum of Ea

Mean E

No. of E

AMB

ITC

ITC-S (9)

Antagonistic Synergisticb

−230 (−34 to −353) 24 (0 to 153)

−7 (−3 to −25) 7 (0 to 12)

14 (4–27) 3 (0–12)

1.00 (0.25–1.00)c 0.02 (0.02–0.03)c

0.13 (0.05–0.38) 0.13 (0.03–0.50)

ITC-R (5)

Antagonistic Synergistic

−165 (−93 to −375) 718 (651 to 777)

−8 (−7 to −13) 23 (16 to 27)

14 (11–40) 26 (25–47)

2.00 (0.25–2.00)d 0.03 (0.03–0.06)d

0.13 (0.09–0.50)e 1.00 (0.50–1.50)e

Concentration (mg/L)

a E is the difference between the expected theoretical (under the Bliss independence no interaction theory) percentage of growth minus the experimentally observed percentage of growth. Positive E indicates synergy since less growth was observed overall than was expected if the two drugs were acting independently; negative E indicates antagonism since more growth was found than if the two drugs were acting independently. b Synergistic interactions were not observed for one isolate. c,d AMB concentrations in combinations with synergistic interactions were statistically significantly lower (P < 0.001) than AMB concentrations in combination with antagonistic interactions. e ITC concentrations in combinations with synergistic interactions were statistically significantly lower (P < 0.05) than ITC concentrations in combination with antagonistic interactions.

were statistically significantly (P = 0.038) lower than ITC concentrations of synergistic combinations (median 1 mg/L, range 0.5–1.5 mg/L) (Table 1). 3.3. Isobolographic analysis of Loewe additivity The results of isobolographic analysis are summarised in Table 2 where the mean interaction indices with their 95% CIs for all ITC-S and ITC-R isolates are presented for each fixedratio combination and the three growth levels (20%, 50% and 80% of growth). Statistically significant (P < 0.05) deviations from additivity were found depending on growth level and fixed ratio, with interaction indices ranging from 0.04 up to 3.44 indicating the presence of both synergy and antagonism.

For example, in the isobolograms of Fig. 3, for a growth level of 50% of an ITC-S and ITC-R isolate statistically significant synergy and antagonism were found for different AMB:ITC fixed ratios. This resulted in isobols that concaved upwards at combinations of low AMB concentrations with high ITC concentrations and downwards at combinations of high AMB concentrations with low ITC concentrations. In general, the higher the AMB fraction in the mixtures, the higher interaction indices were obtained for all growth levels. Similarly, the lower the growth level (i.e. high drug concentrations), the higher the interaction indices (Table 2). The interaction indices were >1 indicating antagonism for combinations where AMB prevailed over ITC, and < 1 indicating synergy for combinations where ITC prevailed over

Fig. 2. Interaction surface plots obtained from the response surface analysis of Bliss independence for the combination of amphotericin B (AMB) with itraconazole (ITC) against (A) an ITC-susceptible (ITC-S) and (B) an ITC-resistant (ITC-R) Aspergillus fumigatus isolate. E was calculated as the expected theoretical % of growth (Eind ) calculated with Bliss independence equation minus the observed % of growth (Eobs ) for each combination of AMB and ITC concentrations. Volumes above (E > 0) and below (E < 0) the zero plane (E = 0) (independent interactions) represent synergistic and antagonistic interactions, respectively. Note the large antagonistic volumes for the ITC-S isolate and synergistic volumes for the ITC-R isolate.

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Fig. 3. Two-dimensional isobolograms showing the interaction at a 50% growth level between amphotericin B (AMB) and itraconazole (ITC) against (A) an ITC-susceptible and (B) an ITC-resistant Aspergillus fumigatus isolate. All points on 50% isobolograms represent drug concentrations, alone and in combination, which resulted in 50% of growth. The isoboles of additivity are shown as solid lines drawn between the EC50 values of AMB on the x-axis and ITC on the y-axis (closed points), whilst the dashed lines represent the theoretically additive 95% confidence intervals (CIs). The open points represent the experimentally-derived EC50,mix values and the 95% CIs (error bars). (A) The experimental EC50,mix of the mixture AMB:ITC for the fixed-ratio combinations of 1:8 and 1:4 were found to be statistically significantly below the theoretical isobole of additivity, indicating synergistic interactions with interaction indices of 0.77 and 0.80, respectively, whilst the fixed-ratio combinations of 2:1, 4:1, 8:1, 16:1 and 32:1 were found to be statistically significantly above the theoretical isobole of additivity, indicating antagonistic interactions with interaction indices of 1.41, 1.92, 2.56, 2.95 and 2.11, respectively. (B) The experimental EC50,mix of the mixture AMB:ITC for the fixed-ratio combinations of 1:16 and 1:8 were found to be statistically significantly below the theoretical isobole of additivity, indicating synergistic interactions with interaction indices of 0.25 and 0.42, respectively, whilst the fixed-ratio combinations of 1:1, 2:1 and 4:1 were found to be statistically significantly above the theoretical isobole of additivity, indicating antagonistic interactions with interaction indices of 1.44, 1.90 and 2.52, respectively. The grey dotted lines starting from the origin of the axes represent the different AMB:ITC fixed ratios. * P < 0.1; ** P < 0.01; *** P < 0.001.

AMB. Although the exact pattern of interactions (i.e. curvature of isobols) varied depending on the growth level (Fig. 4) and on the isolate, the transition from antagonism to synergy occurred at mixtures with AMB fraction PAMB of 0.11 for ITC-S isolates and 0.5 for ITC-R isolates (Table 2). Most of the antagonistic interactions were found for the ITCS isolates at high PAMB , whereas most of the synergistic interactions were found for the ITC-R isolates at low PAMB (Table 2).

The concentrations of AMB and ITC at which the synergistic and antagonistic interactions were found are presented in Table 3 for growth levels of 20%, 50% and 80%, which are associated with high, intermediate and low drug concentrations, respectively. AMB concentrations that produced antagonistic interactions were statistically significant higher (P < 0.001) than those where synergy was found for all three growth levels both for the ITC-S and ITC-R isolates. For example, at 20% growth level, the median AMB

J. Meletiadis et al. / International Journal of Antimicrobial Agents 28 (2006) 439–449 Table 2 Results of isobolographic analysis: the mean (95% confidence interval) interaction indices for all ITC-susceptible (ITC-S) and ITC-resistant (ITC-R) isolates are presented for each AMB:ITC ratio and growth level (growth levels are inversely related to drug concentrations) Interaction indicesa

AMB:ITC ratio (PAMB )

% Growth

ITC-S isolates (n = 9)

ITC-R isolates (n = 5)

16:1 (0.94)

20 50 80

1.67 (2.03–1.37) 1.80 (2.06–1.57) 2.10 (2.63–1.67)

1.22 (1.53–0.97) 1.12 (1.32–0.94) 1.07 (1.26–0.91)

8:1 (0.89)

20 50 80

1.76 (2.05–1.51) 1.74 (2.02–1.50) 1.88 (2.26–1.56)

1.39 (1.86–1.04) 1.08 (1.22–0.95) 0.91 (1.04–0.79)

4:1 (0.80)

20 50 80

1.77 (1.99–1.56) 1.55 (1.79–1.33) 1.48 (1.84–1.18)

1.42 (1.77–1.13) 1.26 (1.59–1.00) 1.30 (1.69–1.00)

2:1 (0.67)

20 50 80

1.42 (1.58–1.29) 1.22 (1.33–1.13) 1.13 (1.37–0.93)

1.26 (1.68–0.95) 0.99 (1.48–0.66) 0.98 (1.69–0.57)

1:1 (0.50)

20 50 80

1.20 (1.28–1.12) 1.06 (1.14–0.98) 0.98 (1.15–0.84)

0.97 (1.43–0.65) 0.73 (1.15–0.47) 0.78 (1.35–0.45)

1:2 (0.33)

20 50 80

1.03 (1.09–0.98) 1.01 (1.10–0.94) 1.03 (1.17–0.91)

0.89 (1.38–0.58) 0.68 (0.99–0.47) 0.80 (1.21–0.53)

1:4 (0.20)

20 50 80

1.01 (1.15–0.89) 1.25 (1.47–1.06) 1.57 (2.05–1.21)

0.74 (1.19–0.47) 0.54 (0.69–0.43) 0.69 (0.84–0.56)

1:8 (0.11)

20 50 80

0.75 (0.93–0.61) 0.67 (1.32–0.34) 0.60 (1.97–0.19)

0.73 (1.11–0.48) 0.41 (0.49–0.34) 0.43 (0.70–0.27)

1:16 (0.06)

20 50 80

0.44 (0.82–0.24) 0.33 (1.03–0.11) 0.25 (1.63–0.04)

1.07 (3.44–0.33) 0.31 (0.37–0.25) 0.18 (0.36–0.09)

445

ergistic combinations of 0.02 mg/L (0.001–0.15 mg/L) and 0.32 mg/L (0.24–0.48 mg/L) for the ITC-S and ITC-R isolates, respectively. For ITC, the concentrations that produced synergistic interactions were statistically significantly higher than the ITC concentrations where antagonism was found only for the ITC-R isolates at 20% and 50% growth level (P < 0.001). For example, at 20% growth level the median ITC concentrations in the synergistic combinations were 1.87 mg/L (0.97–3.18 mg/L) for the ITC-R isolates and 0.10 mg/L (0.01–0.33 mg/L) for ITC-S isolates, which are lower than the ITC concentrations in the antagonistic combinations only for the ITC-R isolates (0.39 mg/L; 0.16–1.91 mg/L), but not for the ITC-S isolates (0.15 mg/L; 0.09–0.25 mg/L).

4. Discussion

AMB, amphotericin B; ITC, itraconazole; PAMB , fraction of AMB in the mixture. a Interaction indices >1 indicate antagonism and <1 indicate synergy.

concentrations in the antagonistic combinations were 0.93 mg/L (range 0.15–1.87 mg/L) for ITC-S isolates and 2.70 mg/L (range 0.65–4.77 mg/L) for the ITC-R isolates, which are higher than the AMB concentrations in the syn-

AMB was found to interact with ITC in vitro against A. fumigatus in a concentration-dependent manner. Synergy was observed at combinations with low concentrations of AMB (<0.125 mg/L) whereas antagonism was found at combinations with higher concentrations of AMB. For ITC-R isolates, the synergistic interactions were observed at high concentrations of ITC (>0.5 mg/L). Synergy was more frequently observed for the ITC-R isolates than for the ITC-S isolates. These results were confirmed with independent analyses using two drug interaction pharmacodynamic models based on different zero interaction theories, the Loewe additivity and the Bliss independence theories. Previous in vitro combination studies with AMB and ITC against A. fumigatus resulted in conflicting data, with antagonism being the most commonly reported interaction [3]. In all these studies a complete growth inhibition endpoint was used, which inevitably assesses the interactions only at drug concentrations close to the optically clear MICs of the drugs. Furthermore, given the inherent variability of ±1 dilution of antifungal susceptibility testing using geometrically increased drug dilutions, the stringent cut-offs of 0.5 and 4 were used [3] to determine deviation from additivity instead

Table 3 Drug concentrations (median and range among isolates) at combinations with synergistic and antagonistic interactions based on the results of isobolographic analysis Isolates (n)

% Growth

AMB concentrations (mg/L) at: Antagonistic interactions –1.87)a

ITC concentrations (mg/L) at:

Synergistic interactions (0.001–0.15)a

Antagonistic interactions

Synergistic interactions

ITC-S (9)

20 50 80

0.93 (0.15 0.45 (0.01–0.91)a 0.14 (0.01–0.60)a

0.02 0.01 (0.001–0.05)a 0.002 (0.001–0.03)a

0.15 (0.09–0.25) 0.06 (0.03–0.17) 0.04 (0.01–0.16)

0.10 (0.01–0.33) 0.04 (0.001–0.17) 0.01 (0.001–0.08)

ITC-R (5)

20 50 80

2.70 (0.65–4.77)a 0.66 (0.41–1.06)a 0.36 (0.18–0.43)a

0.32 (0.24–0.48)a 0.05 (0.02–0.09)a 0.005 (0.001–0.02)a

0.39 (0.16–1.91)b 0.13 (0.07–0.26)b 0.15 (0.03–0.24)

1.87 (0.97–3.18)b 0.75 (0.26–1.40)b 0.03 (0.02–0.33)

AMB, amphotericin B; ITC, itraconazole; ITC-S, itraconazole susceptible; ITC-R, itraconazole resistant. a AMB concentrations at combinations with synergistic interactions were statistically significantly lower than the AMB concentrations at combinations with antagonistic interactions. b ITC concentrations at combinations with synergistic interactions were statistically significantly higher than the ITC concentrations at combinations with antagonistic interactions.

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Fig. 4. Interaction surface plots obtained with the isobolographic analysis for the combination of amphotericin B (AMB) with itraconazole (ITC) against an (A) ITC-susceptible and (B) and ITC-resistant Aspergillus fumigatus isolate. Interaction indices for each fixed-ratio combination are plotted against the AMB proportion of the mixtures and growth level. Surface areas lower or higher than the plane with interaction index 1 indicate synergy or antagonism, respectively.

of 1, which is the correct cut-off based on the Loewe additivity theory [12]. However, most of the fractional inhibitory concentration (FIC) indices of previously published studies were between 0.5 and 4, resulting in no interaction [8,19,20]. Thus, much of the information regarding drug interactions is lost within this range. Determination of FIC indices using different MIC endpoints could help to detect interactions at different drug concentrations, as we found previously [21], whereas arithmetically increased drug dilutions and replications can help to detect deviations from additivity [22]. In the present study, a regression analysis was used to determine precisely and accurately the effective concentrations of AMB and ITC minimising experimental errors as it was found previously when the Emax model was used to describe the concentration–effect relationships of antifungal drugs [15,23]. This approach, in combination with the isobolographic analysis, enabled us to obtain a detailed picture of AMB–ITC interactions at a broad range of concentrations with statistical confidence. To our knowledge, this is the first time that isobolography has been used to determine antifungal drug interactions. Isobolography is an analytical method applicable for determining pharmacological interactions among drugs and can document and give shape to unusual phenomena [24] with many applications in assessing interactions between antiepileptic [9], analgesic [25] and anti-inflammatory drugs [26]. Unlike other fully parametric drug interaction models of Loewe additivity [27], the isobolographic model is flexible and can describe any type of response surfaces detecting local areas of synergy and antagonism, as long as the concentration–effect curves of the drugs alone and in combination at fixed ratios are well defined, and not necessarily the same e.g. in Fig. 1 the concentration–effect curves have different shapes. Finally, small departures from additivity can be detected without replication. The results of isobolographic analysis were confirmed with a response

surface analysis based on another zero interaction theory, the Bliss independence theory [15]. The latter model provides local measures of pharmacodynamic interactions and the drug concentrations where these occurred. Although the underlying molecular mechanisms of AMB–ITC interaction are unknown, the findings of the present study fit with a model for AMB action proposed initially by Cohen and others [28–31]. AMB at low concentrations (0.2–0.8 ␮M) forms non-aqueous pre-pore structures (ionic channels) without the direct participation of ergosterol molecules, making the membranes more permeable to urea and glucose [28]. At higher concentrations (>1.2 ␮M) the initially formed structures subsequently interact with ergosterol in the membrane and form aqueous pores with enlarged diameter. Thus, the synergistic interactions between AMB and ITC at low AMB concentrations could be explained by increased influx and/or inefficient efflux of ITC as a result of permeability changes in the fungal cell membrane caused by AMB. Increased penetration of a drug as a result of cell membrane impairment by another drug was suggested for interactions between AMB and antibacterials such as rifampicin [32] and flucytosine [33]. Surprisingly, the non-aqueous pre-pore structures of AMB molecules were observed at AMB concentrations <0.1 ␮M (i.e. 0.09 mg/L) [34], which matched with the AMB concentrations showing synergy in the present study (<0.125 mg/L). Since ergosterol is not necessary at this stage [28], inhibition of ergosterol biosynthesis by ITC does not antagonise the AMB action. At high AMB concentrations, AMB exerts its antifungal activity by forming aqueous pores, a process in which ergosterol is required. Thus, at this stage inhibition of ergosterol biosynthesis by ITC may antagonise the action of AMB. The concentration-dependent nature of AMB–ITC interaction against A. fumigatus was suspected in a recent study where a head-to-head comparison of different drug interac-

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tion models was performed to explore their advantages and disadvantages for analysing antifungal combinations [21]. Different FIC indices were obtained for the AMB–ITC interaction, ranging from 0.08 to 2 when different MIC endpoints (50%, 75% and 90% growth inhibition) were used [21]. Although sequential drug exposure results in a different pattern of interaction, evidence of concentration-dependent AMB–ITC interactions was found using the Etest methodology where AMB MICs increased after pre-exposure to non-inhibitory concentrations of ITC, whereas ITC MICs decreased after pre-exposure to subinhibitory concentrations of AMB [35]. Concentration-dependent interactions might be a common phenomenon for antifungal combinations since different FIC indices were obtained for different levels of growth inhibition (i.e. different drug concentrations) for combinations of AMB, 5-flucytosine, ITC, caspofungin, voriconazole and fluconazole against A. fumigatus, Aspergillus flavus, Aspergillus terreus and Candida albicans [19–21]. Most of the in vivo studies of AMB–azole combination therapy for experimental aspergillosis were performed using single dose levels of AMB, which prohibits drawing conclusions regarding the dose-dependent nature of this interaction in vivo [1,3,36]. Furthermore, in most of these studies AMB was administered at highly effective doses (>0.8 mg/kg) [2,37–39], which may have resulted in high drug levels. In a murine model of acute invasive pulmonary aspergillosis, pre-exposure to ITC resulted in a statistically significant increase in CFU counts in lung tissue following AMB treatment with doses of 3, 1 and 0.5 mg/kg intraperitoneally but not at a dose of 0.25 mg/kg [40]. Unfortunately, lower doses, which may have resulted in synergistic effects, were not tested. Of note, plasma levels of AMB for doses of 3, 1 and 0.5 mg/kg were >0.2 mg/L for most of the 24 h post-dosing period, a concentration that based on the in vitro results of the present study is much higher than the AMB concentrations that showed synergistic effects. In experimental murine central nervous system aspergillosis, combination of 40 mg/kg of voriconazole (<40% survival) with a subtherapeutic dose of liposomal AMB (1 mg/kg, 20% survival) increased efficacy (100% survival and significant reduction of fungal burden in kidney and brain) compared to monotherapies; whereas combination of the same voriconazole dose with a higher therapeutic dose of liposomal AMB (10 mg/kg, 70% survival) did not affect outcome (60% survival in combination group) [47]. Unfortunately, the only studies where low AMB doses were used in combination with azoles can be found for non-aspergillosis experimental models. In a study of experimental murine candidiasis, combination of AMB at a dose of 0.1 mg/kg but not at a dose of 1 mg/kg prolonged the survival of mice significantly compared with monotherapy when it was combined with the triazole SCH 39304 [41]. Furthermore, in a model of murine cryptococcal meningitis, worse survival was observed when higher doses of AMB–ITC (0.5 mg/kg–25 mg/kg) were used in combination compared with lower doses (0.12 mg/kg–6.25 mg/kg) where combi-

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nation therapy prolonged survival [37]. Finally, although AMB–azole interaction may be different than AMB interaction with other drugs, doses of AMB lower than 0.125 mg/kg appeared more efficacious when they were combined with caspofungin than either drug alone in murine candidiasis and aspergillosis [42]. In clinical settings, there are few cases of the simultaneous use of AMB and ITC [3]. A retrospective clinical case series of 21 patients examining concurrent therapy with AMB (1 mg/kg/day) plus ITC (400 mg/kg) demonstrated no clinical antagonism, with a cure or improvement rate of 82% in the combination arm and 50% with AMB monotherapy [43]. Although other factors (e.g. neutropenia, ability to take oral medication, concomitant medications) may also contribute to this difference, the interesting observation of this study is that 10 of 11 patients who received combination therapy for a mean period of 34 days completed therapy with ITC alone. Based on the pharmacokinetic profile of AMB, subtherapeutic AMB levels can be detected 3–6 weeks after the last dose [44]. Therefore, the improved outcome of AMB–ITC combination therapy may be due to interactions at subtherapeutic low concentrations of AMB, as was found in the present study. Such interactions may also occur when AMB therapy is followed by azole therapy and may explain why these combination regimens result in better outcomes [45] than regimens where azole therapy is followed by AMB therapy [1,3]. In conclusion, the AMB–ITC interaction is concentrationdependent in vitro against A. fumigatus isolates, with synergistic interactions at low concentrations of AMB and antagonistic interactions at high concentrations of AMB. These findings need in vivo evaluation to be useful for optimising antifungal therapy. However, a pharmacodynamic synergy or antagonism is not necessarily correlated with therapeutic benefit or failure, respectively [46]. Synergy and antagonism are defined relative to the effects of the drugs alone, e.g. a synergistic combination of low doses of two drugs can result in an effect that may be much smaller in absolute values than the effect of high doses of each drug alone. Thus, monotherapy with high doses of AMB or ITC alone may well result in better outcome than any combination of these two drugs. Therefore, the therapeutic superiority of combination therapy with low AMB doses and high azole doses over monotherapy should be considered in relation to other factors such as toxicity or tissue penetration. For example, high doses of AMB could be followed by combination therapy of low doses of AMB with high doses of ITC, thus minimising the risk of toxicity without compromising efficacy.

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