Physiologically Based Pharmacokinetic Modeling To Guide Management of Drug Interactions between Elexacaftor-Tezacaftor-Ivacaftor and Antibiotics for the Treatment of Nontuberculous Mycobacteria

ABSTRACT

Nontuberculous mycobacteria (NTM) are the pathogens of concern in people with cystic fibrosis (pwCF) due to their association with deterioration of lung function. Treatment requires the use of a multidrug combination regimen, creating the potential for drug-drug interactions (DDIs) with cystic fibrosis transmembrane conductance regulator (CFTR)-modulating therapies, including elexacaftor, tezacaftor, and ivacaftor (ETI), which are eliminated mainly through cytochrome P450 (CYP) 3A-mediated metabolism. An assessment of the DDI risk for ETI coadministered with NTM treatments, including rifabutin, clofazimine, and clarithromycin, is needed to provide appropriate guidance on dosing. The CYP3A-mediated DDIs between ETI and the NTM therapies rifabutin, clarithromycin, and clofazimine were evaluated using physiologically based pharmacokinetic (PBPK) modeling by incorporating demographic and physiological “system” data with drug physicochemical and in vitro parameters. Models were verified and then applied to predict untested scenarios to guide continuation of ETI during antibiotic treatment, using ivacaftor as the most sensitive CYP3A4 substrate. The predicted area under the concentration-time curve (AUC) ratios of ivacaftor when coadministered with rifabutin, clofazimine, or clarithromycin were 0.31, 2.98, and 9.64, respectively, suggesting moderate and strong interactions. The simulation predicted adjusted dosing regimens of ETI administered concomitantly with NTM treatments, which required delayed resumption of the standard dose of ETI once the NTM treatments were completed. The dosing transitions were determined based on the characteristics of the perpetrator drugs, including the mechanism of CYP3A modulation and their elimination half-lives. This study suggests increased doses of elexacaftor/tezacaftor/ivacaftor 200/100/450 mg in the morning and 100/50/375 mg in the evening when ETI is coadministered with rifabutin and reduced doses of elexacaftor/tezacaftor 200/100 mg every 48 h (q48h) and ivacaftor 150 mg daily or a dose of elexacaftor/tezacaftor/ivacaftor 200/100/150 mg q72h when coadministered with clofazimine or clarithromycin, respectively. Importantly, the PBPK simulations provide evidence in support of the use of treatments for NTM in pwCF receiving concomitant dose-adjusted ETI therapy.

INTRODUCTION

Nontuberculous mycobacteria (NTM) are increasingly being isolated from the sputum of people with CF (pwCF), with estimates of prevalence increasing from 1.3% in 1984 to 12% in 2012 (1). The prevalence of NTM increases with age, from 10% in children aged 10 years to over 30% in adults over the age of 40 years (1). NTM are pathogens of concern in CF due to their association with deterioration of lung function due to progressive inflammatory lung damage. A significant barrier to effective treatment is the limited number of safe and effective antibiotics for the treatment of NTM. Further, NTM require the use of a multidrug combination regimen over a prolonged period of up to 18 months, creating the potential for drug-drug interactions (DDIs) with other chronic medications for CF, including the cystic fibrosis transmembrane conductance regular (CFTR) modulators (2). A triple combination of elexacaftor, tezacaftor, and ivacaftor (ETI) (Trikafta; Vertex Pharmaceuticals) has resulted in significant improvements in lung function and nutritional status in pwCF and is indicated in 90% of patients age 6 or greater (3). However, all three components of ETI are eliminated primarily through cytochrome P450 (CYP) 3A-mediated hepatic metabolism (4) and therefore present a therapeutic challenge to the treatment of NTM in pwCF. The exclusion of antibiotics due to drug-drug interactions further reduces the available treatment options for NTM in patients that already exhibit relatively poor outcomes with available treatments.

Rifamycins are the first-line treatment for Mycobacterium avium complex (MAC), the most commonly identified NTM species (2, 5). Rifamycins are a key component of the treatment regimen since they reduce the emergence of macrolide resistance, which is associated with poor clinical outcomes (6, 7). However, the concomitant use of strong inducers, including the rifamycins (e.g., rifampin and rifabutin), is not recommended with ETI, since a pharmacokinetic (PK) study has shown that the coadministration of rifampin decreased the area under the concentration-time curve (AUC) of ivacaftor by 89% (AUC ratio of 0.11) (8). This DDI potentially compromises the treatment efficacy for NTM in pwCF by precluding the first-line antibiotics for patients receiving ETI therapy. While rifabutin induces CYP3A activity, its effect appears to be moderate in comparison with that of rifampin. For example, a study with lersivirine (a CYP3A substrate) demonstrated an 85% reduction in the lersivirine AUC with rifampin but only a 34% reduction with rifabutin (9). Thus, we hypothesized that the use of rifabutin with an adjusted dosing regimen of ETI might offer a key alternative to rifampin in patients receiving ETI.

Additional potential drug interactions include those with clofazimine and clarithromycin. Clofazimine is a guideline-recommended therapy for Mycobacterium abscessus complex (MABSC), which is difficult to treat due to its intrinsic resistance to antibiotics and is associated with more rapid decline in lung function in pwCF (2, 10). There is conflicting information regarding the CYP3A-modulating activity of clofazimine (e.g., inhibitor or inducer), leaving a question about whether concomitant use with ETI without dose adjustment is appropriate. Clarithromycin is also a guideline-recommended treatment for NTM (2). Clarithromycin acts as both a competitive and a mechanism-based CYP3A inhibitor (11), thereby potentially exerting a significant and prolonged inhibitory effect requiring dose adjustment of ETI. Currently, there are no clinical trial data available regarding the interactions of ETI with rifabutin, clofazimine, or clarithromycin. Therefore, there is an urgent need for DDI predictions and development of dosing guidelines for these NTM treatments for pwCF.

In the present study, we evaluated the CYP3A modulation-mediated drug interactions of ETI with selected NTM therapies by using a physiologically based pharmacokinetic (PBPK) simulation-based approach, with the goal of enabling the use of additional NTM therapies with appropriate dosage adjustment. The predictive performance of PBPK simulations for CYP enzyme-based DDIs has been well established (12, 13), and this strategy is increasingly included during regulatory review by the FDA as an alternative for exploring DDI potential to provide dosing recommendations in product labeling (14). We applied the verified physiologically based pharmacokinetic–drug-drug interaction (PBPK-DDI) models of ETI that we constructed in a recent investigation to determine appropriate dosing of ETI when coadministered with nirmatrelvir-ritonavir (Paxlovid; Pfizer, Inc.) (15). In the current study, we extended our PBPK model to evaluate the interaction of ETI with selected guideline-recommended NTM therapies and to determine appropriate dosage adjustments for coadministration.

RESULTS

DDI simulation of ETI with rifabutin.

(i) Simulated DDI suggests that rifabutin can be coadministered with dose-adjusted ETI. To mimic the clinical setting where rifabutin is initiated in patients receiving chronic ETI therapy, we simulated steady-state PK of ETI, with the addition of rifabutin 300 mg daily for 20 days while continuing ETI standard dosing during and after rifabutin administration (Fig. 1a to c). The results of the simulated effect of rifabutin on the PK of ETI at steady state are summarized in Table 1. The simulated geometric mean AUC ratio was lowest for ivacaftor (0.31; 90% confidence interval [CI], 0.29, 0.34), followed by tezacaftor (0.60; 90% CI, 0.58, 0.62) and elexacaftor (0.67; 90% CI, 0.66, 0.69). This result corresponds to the magnitude of the drug fraction metabolized by CYP3A (fmCYP3A), with ivacaftor being the most sensitive CYP3A substrate among ETI components with an fmCYP3A of 98%. Importantly, the predicted magnitude of the interaction for rifabutin-ivacaftor was lower than that observed when ivacaftor was coadministered with lumacaftor (AUC ratio of 0.22), which is combined with an increased dose of ivacaftor (16).

FIG 1.

Predicted plasma concentration profiles of standard-dose ETI without NTM treatment (green) and with NTM treatment (red). (a to c) Rifabutin 300 mg daily administered day 1 through day 20; (d to f) clofazimine 100 mg daily administered day 1 through day 130; (g to i) clarithromycin 500 mg q12h administered day 1 through day 50.

TABLE 1.

Summary of the predicted steady-state C_max and AUC geometric mean ratios for standard-dose ETI in the presence and absence of NTM treatments

NTM treatment	ETI	Predicted GMR (90% CI) of ETI PK parameter in the presence and absence of NTM treatmenta
		C max	AUC
Rifabutin, 300 mg daily	Elexacaftor, 200 mg daily	0.74 (0.73, 0.76)	0.67 (0.66, 0.69)
	Tezacaftor, 100 mg daily	0.74 (0.72, 0.76)	0.60 (0.58, 0.62)
	Ivacaftor, 150 mg q12h	0.37 (0.34, 0.39)	0.31 (0.29, 0.34)
Clofazimine, 100 mg daily	Elexacaftor, 200 mg daily	1.60 (1.57, 1.64)	1.75 (1.71, 1.80)
	Tezacaftor, 100 mg daily	1.51 (1.48, 1.55)	1.87 (1.82, 1.91)
	Ivacaftor, 150 mg q12h	2.48 (2.39, 2.57)	2.98 (2.88, 3.08)
Clarithromycin, 500 mg q12h	Elexacaftor, 200 mg daily	2.14 (2.02, 2.27)	2.43 (2.27, 2.59)
	Tezacaftor, 100 mg daily	2.11 (1.99, 2.24)	2.92 (2.73, 3.12)
	Ivacaftor, 150 mg q12h	7.28 (6.31, 8.41)	9.64 (8.33, 11.16)

^aGMR, geometric mean ratio.

(ii) An altered dose of ETI when coadministered with rifabutin recapitulates the PK profile of standard-dose ETI alone. We next utilized the PBPK models to simulate steady-state ETI dose adjustments when these agents are coadministered with rifabutin and to determine dose transitions when initiating and discontinuing rifabutin. Based on the simulated effects of rifabutin, elexacaftor 200 mg, tezacaftor 100 mg, and ivacaftor 450 mg in the morning (2 orange and 2 blue tablets) and elexacaftor 100 mg, tezacaftor 50 mg, and ivacaftor 375 mg in the evening (1 orange and 2 blue tablets) provided maximum concentration of drug in serum (C_max) and AUC (80.6 to 102.2%) values approximately equivalent to those of the conventional regimen of ETI alone at steady state (Fig. 2a to c; Table 2). Since ivacaftor showed the most significant DDI among the three components, an additional dose adjustment step for ivacaftor was needed, by initiating an increased dose of ivacaftor (ivacaftor 300 mg every 12 h [q12h]) on day 2 of rifabutin. On day 5, the increased dose needed to be initiated for all components of ETI. The standard dose of ETI could be resumed 8 days after rifabutin discontinuation (Table 3). In addition, using the PBPK model of M1-tezacaftor (a metabolite of tezacaftor), we were able to determine that the adjusted dose of ETI in combination with rifabutin resulted in a steady-state M1-tezacaftor AUC of 101.9% of the standard regimen.

FIG 2.

Predicted plasma concentration profiles of standard-dose ETI without NTM treatment (green) and adjusted-dose ETI with NTM treatment (red). (a to c) Rifabutin 300 mg daily administered day 1 through day 20; (d to f) clofazimine 100 mg daily administered day 1 through day 130; (g to i) clarithromycin 500 mg q12h administered day 1 through 50.

TABLE 2.

Predicted steady-state mean C_max and AUC values of adjusted regimens of ETI when coadministered with NTM treatments

NTM treatment	ETI	ETI regimen	Cmax (mg/L)	% of value for standard-dose ETI alone	AUCa (mg · h/L)	% of value for standard-dose ETI alone
Rifabutin, 300 mg daily	Elexacaftor	200 mg in a.m., 100 mg in p.m.	8.1	100.0	161.4	102.2
	Tezacaftor	100 mg in a.m., 50 mg in p.m.	7.3	88.0	104.7	91.8
	Ivacaftor	450 mg in a.m., 375 mg in p.m.	1.6	100.0	21.6	80.6
Clofazimine, 100 mg daily	Elexacaftor	200 mg q48h	7.5	92.6	274.8	87.0
	Tezacaftor	100 mg q48h	8.1	97.6	213.3	93.6
	Ivacaftor	150 mg daily	2.3	143.8	74.0	138.1
Clarithromycin, 500 mg q12h	Elexacaftor	200 mg q72h	7.3	90.1	392.6	82.8
	Tezacaftor	100 mg q72h	9.1	109.6	348.8	102.0
	Ivacaftor	150 mg q72h	3.1	193.8	147.7	183.7

^aAUC from 0 to 24 h for coadministration with rifabutin, AUC from 0 to 48 h for coadministration with clofazimine, and AUC from 0 to 72 h for coadministration with clarithromycin.

TABLE 3.

Suggested dosing schedules of ETI when coadministered with select NTM treatments

NTM treatment	ETI and time of dose		Suggested ETI dose adjustments and transitionsa
			DOT 2 to 4	DOT 5 to DPT 1	DPT 2 to 7	DPT 8
Rifabutin, 300 mg daily	a.m.	Elexacaftor/tezacaftor/ivacaftor	200/100/150 mg	200/100/150 mg	200/100/150 mg	Resumption of standard doseb
		ivacaftor	150 mg	300 mg	150 mg
	p.m.	Elexacaftor/tezacaftor/ivacaftor		100/50/75 mg
		Ivacaftor	300 mg	300 mg	300 mg
			DOT 3 to 23	DOT 24 to DPT 9	DPT 10 to 41	DPT 42
Clofazimine, 100 mg daily	Elexacaftor/tezacaftor/ivacaftor		200/100/150 mg daily	200/100/150 mg q48hc	200/100/150 mg daily	Resumption of standard doseb
	Ivacaftor			150 mg q48hc
			DOT 2 to DPT 3			DPT 4
Clarithromycin, 500 mg q12h	Elexacaftor/tezacaftor/ivacaftor		200/100/150 mg q72h			Resumption of standard doseb

^aDOT, day of treatment; DPT, day posttreatment.

^bStandard dose consists of elexacaftor 200 mg/tezacaftor 100 mg/ivacaftor 150 mg a.m. plus ivacaftor 150 mg p.m.

^cElexacaftor 200 mg/tezacaftor 100 mg/ivacaftor 150 mg alternating with ivacaftor 150 mg every other day.

DDI simulation of ETI with clofazimine.

(i) PBPK model of clofazimine recapitulates the observed drug interaction with bedaquiline. Based on the in vitro CYP3A induction experiments, the maximal fold induction (E_max) and the concentration resulting in half-maximal induction (EC₅₀) of clofazimine were 6.8 and 6.7 μM (95% CI, 5.4, 8.4), respectively (see Fig. S1 in the supplemental material). Rifampin exhibited significantly higher induction of CYP3A, with an E_max of 40.3 and an EC₅₀ of 1.4 μM (95% CI, 0.8, 2.4). The fraction of unbound drug in the in vitro hepatocyte incubation (fuinc) of clofazimine was predicted to be 0.05 based on the model established by Austin et al. (17) and was incorporated into the PBPK model. To verify its perpetrator property as defined in the model, we simulated the interaction between clofazimine and bedaquiline (a CYP3A substrate). A published clinical study evaluating the potential DDI between clofazimine and bedaquiline found no statistically significant DDI between the two drugs (18). In our PBPK simulation, clofazimine did not show a significant interaction with bedaquiline, with C_max and AUC ratios of 1.14 (1.13, 1.15) and 1.17 (1.15, 1.18), respectively, which agrees with the data from the published clinical trial.

(ii) Simulated clofazimine-ETI DDI suggests moderate accumulation as a net effect of concurrent moderate CYP3A4 inhibition and weak induction activities. The simulation of steady-state PK of ETI with or without clofazimine 100 mg administered daily resulted in AUC ratios of 1.75 (1.71, 1.80), 1.87 (1.82, 1.91), and 2.98 (2.88, 3.08) for elexacaftor, tezacaftor, and ivacaftor, respectively (Table 1). The AUC ratio of ivacaftor derived by clofazimine’s inhibition potential (3.11; 90% CI, 3.00, 3.23) was not significantly different from that derived by clofazimine’s inhibition and induction potential (2.98; 90% CI, 2.88, 3.08), suggesting that clofazimine’s induction effect is very mild and its inhibition activities outweigh the induction activities on CYP3A.

Since the CYP3A inhibition effect increases over time as clofazimine accumulates toward its steady state, the AUC ratio of ETI gradually increases until clofazimine reaches steady state (130 days). Similarly, reestablishment of steady-state ETI after discontinuation of clofazimine requires a prolonged period due to the long elimination half-life of clofazimine (Fig. 1d to f). Crucially, this indicates that dose reduction of ETI in the case of coadministration with clofazimine would require delayed initiation and would need to be extended beyond the period of coadministration after clofazimine discontinuation.

(iii) Reduced dose of ETI decreases the impact of the drug interaction with clofazimine. We simulated steady-state ETI dose adjustments when these agents are coadministered with clofazimine. Based on the simulated effects of clofazimine, elexacaftor/tezacaftor 200/100 mg every 2 days and ivacaftor 150 mg once a day (2 orange tablets and 1 blue tablet on alternate days) achieve AUC ratios between 87.0 and 138% relative to that of the standard regimen of ETI alone at steady state (Fig. 2d to f; Table 2). We could not meet the FDA bioequivalence limit (0.8 to 1.25), since ETI is provided as a fixed-dose combination tablet that limited the dosing regimens could be simulated. Since ivacaftor showed the most significant DDI among the three components, the reduced dose of ivacaftor (ivacaftor 150 mg daily) needed to be initiated earlier on day 3, followed by the reduced dose of all components of ETI on day 24. The standard dose of ETI could be resumed 42 days after clofazimine discontinuation (Table 3). The simulation of the active metabolite M1-tezacaftor showed that the reduced dose of tezacaftor when coadministered with clofazimine resulted in M1-tezacaftor AUC of 70.3% compared with that of tezacaftor alone.

DDI simulation of ETI with clarithromycin.

(i) Simulated clarithromycin-ETI DDI indicates significant drug accumulation. The simulated geometric mean AUC ratio at steady state was highest for ivacaftor (9.64; 90% CI, 8.33, 11.16), followed by tezacaftor (2.92; 90% CI, 2.73, 3.12) and elexacaftor (2.43; 90% CI, 2.27, 2.59) (Table 1). Plasma concentrations of ETI in the presence and absence of clarithromycin are shown in Fig. 1g to i. Although clarithromycin itself is eliminated the day after discontinuation, it is a mechanism-based CYP3A inhibitor, so the inhibition is prolonged and the baseline steady state of ETI is not predicted to be reestablished until 10 days after discontinuation of clarithromycin.

(ii) Reduced dose of ETI decreases the impact of the drug interaction with clarithromycin. We next utilized the models to simulate dose adjustments of ETI when coadministered with clarithromycin. Based on the simulations, elexacaftor 200 mg, tezacaftor 100 mg, and ivacaftor 150 mg in the morning (2 orange tablets) every 3 days provides a steady-state PK profile closest to that of the standard regimen of ETI, with the AUC ranging from 82.8 to 183.7% of that of the standard regimen (Fig. 2g to i; Table 2). The reduced dose of ETI was initiated on day 2 of coadministration, and the standard dose of ETI was resumed 4 days after clarithromycin discontinuation (Table 3). We could not meet the FDA bioequivalence limit (0.8 to 1.25) for ivacaftor, since targeting 1.25-fold of ivacaftor exposure would result in significant subtherapeutic levels of elexacaftor and tezacaftor due to the fixed-dose combination tablet. The simulation of M1-tezacaftor showed that with a reduced dose of ETI and clarithromycin, its AUC achieved 36.5% of that of the standard dose tezacaftor alone.

DISCUSSION

NTM pulmonary disease remains a significant therapeutic challenge in pwCF, requiring the use of multidrug combination regimens over a prolonged period, creating the potential for drug interactions with ETI. Our PBPK simulations indicate that coadministration of rifabutin, clofazimine, or clarithromycin leads to clinically significant DDIs with ETI, necessitating dose adjustment. In addition, we found that the altered concentrations of ETI were sustained after the discontinuation of NTM treatments, requiring delayed resumption of the standard dose of ETI. The optimal dosing transitions determined by simulations depend on the characteristics of the perpetrator drugs, including the mechanism of CYP3A4 modulation as well as the elimination half-lives. Rifabutin and clarithromycin require 8 and 4 additional days, respectively, of ETI dose adjustment after drug discontinuation due to their residual enzyme induction or inhibition effects. On the other hand, clofazimine requires 42 additional days of adjusted dose after drug discontinuation due to its prolonged elimination half-life.

Rifamycins are first-line therapy for the treatment of MAC, the most frequently identified NTM species in pwCF; however, the CYP3A induction effect creates a therapeutic challenge to coadministration with ETI. Although both rifampin and lumacaftor reduce the exposure of ivacaftor significantly, the reduction in the AUC of ivacaftor was greater with rifampin than with lumacaftor (AUC ratios of 0.11 and 0.22, respectively) (16, 19). The concomitant use of ETI with rifampin is not recommended; however, lumacaftor, a first-generation CFTR corrector therapy, is combined with an higher dose of ivacaftor (250 mg q12h) than the standard dose (150 mg q12h) to partially compensate for the induction effect of lumacaftor. The clinical efficacy of lumacaftor/ivacaftor demonstrates the feasibility of dose adjustment of ETI to overcome the CYP3A induction effect of rifabutin. From the ETI-rifabutin DDI simulations, we found that rifabutin led to an ivacaftor AUC ratio of 0.31, indicating a smaller reduction than that seen when ivacaftor was coadministered with either rifampin or lumacaftor. A clinical trial to assess the impact of rifabutin on ETI is ongoing (registration no. NCT04840862). Once these data become available, we will reassess the model, giving us the opportunity to further learn and confirm; however, in the meantime, we believe the modeling is sufficiently verified to guide therapy options and dose adjustments for pwCF. Use of these modified dosing regimens will enable the use of first-line therapy for the treatment of MAC while maintaining the efficacy of highly active CFTR modulators.

While the adjusted dosing regimen of ETI for coadministration with rifabutin was designed to match the plasma exposure of ETI with that of a standard dose, we recognize that this would result in a substantial increase in cost. Alternatively, the reduced plasma exposure of ETI might still be effective if its exposure at the site of action (lung) is sufficient to achieve an effective concentration, thereby potentially avoiding the cost increase associated with the increased dose. We simulated lung concentrations of ETI derived from full PBPK models upon rifabutin coadministration (model data are not shown). The predicted lung trough concentrations of ETI at steady state (1.30 mg/L, 1.05 mg/L, and 0.58 mg/L for elexacaftor, tezacaftor, and ivacaftor, respectively) exceed the half-maximal effective concentration (EC₅₀) for chloride transport in phe508del human bronchial epithelial cells (0.05 mg/L, 0.31 mg/L, and 0.09 mg/L for elexacaftor, tezacaftor, and ivacaftor, respectively) (20, 21). This result suggests that the standard dose of ETI might maintain therapeutic efficacy despite its decreased plasma exposure upon rifabutin administration. These results require further clinical evaluation.

Lung infections with MABSC represent a significant therapeutic challenge in pwCF due to bacterial resistance and poor clinical outcomes with current therapies (22, 23). Clofazimine is a guideline-recommended therapy for the treatment of MABSC lung infections. There has been conflicting information regarding the CYP3A-modulating activity of clofazimine. Several in vitro studies have suggested that clofazimine is a CYP3A inhibitor (24, 25), but there is also a report of its potential CYP3A4 induction activity in vitro (26). Currently, specific guidance on dosing of ETI when coadministered with clofazimine is not provided due to the insufficient data available to classify the degree of CYP3A modulation by clofazimine (27). Our PBPK simulation results suggest that clofazimine moderately inhibits ivacaftor metabolism, leading to drug accumulation. These data are in contrast to those of a recent case report of a 16-year-old person with CF, which found no significant DDI between clofazimine and tezacaftor and ivacaftor (28). The observed data from this report show ivacaftor AUC ratios of 1.46 and 1.09 on days 8 and 115, respectively, demonstrating a weak interaction at day 8 (prior to steady state of clofazimine) but no DDI at day 115. We performed sensitivity analyses in an attempt to address the disparity between these data and our predictions and to explore the impact of variability in interaction parameters. By altering the parameters for the CYP3A-modulating potential (K_i, EC₅₀, and E_max) within our model, we were unable to recapitulate the observed data from this case report (see Table S2 in the supplemental material). To recapitulate no DDI at steady state, it would require potent induction activity such that it could offset the inhibition activity at steady state; however, potent CYP3A-induction activities are not consistent with the moderate inhibition observed on day 8 of coadministration in this case report. No data on medication adherence or plasma concentrations of clofazimine were provided, and as indicated in the case report, food intake was not controlled, although it is recommended that ivacaftor be taken with fat-containing food to maximize absorption, as described in the prescribing information (8). A limitation of the clofazimine PBPK model is that it was only partially validated with a single drug (bedaquiline) that is not classified as a sensitive index substrate. Therefore, a clinical DDI study of clofazimine with ETI or another sensitive CYP3A substrate is necessary to validate the model and to provide definite guidance on dose adjustment with ETI.

Clarithromycin is a guideline-recommended treatment for NTM, and it strongly inhibits CYP3A activity by an irreversible mechanism-based inhibition. While azithromycin is more widely used due to its once daily administration and fewer DDIs, there may be instances where clarithromycin is indicated, considering its higher potency against NTM species than that of azithromycin (29–31). The DDI between clarithromycin and ivacaftor in pwCF has been reported (32). Applying our PBPK model with the same dose and schedule of drugs (e.g., clarithromycin 500 mg q12h for 2.5 days with a single dose of ivacaftor) demonstrated a very close prediction of the observed DDI (3.75 and 3.20 for predicted and observed median AUC ratios of ivacaftor, respectively), which further verifies that the model was adequate for the assessment of this DDI. By following the sponsor-recommended dosing regimens of ETI when concomitantly used with a strong CYP3A inhibitor, elexacaftor 200 mg/tezacaftor 100 mg/ivacaftor 150 mg q72h provided PK profiles closest to those of standard dosing of ETI alone.

A limitation of this study is that no controlled clinical DDI study has been conducted for ETI with rifabutin or clofazimine or for elexacaftor/tezacaftor with clarithromycin. However, the predictions of drug interactions were preceded by thorough validation of the ETI DDI models with a range of CYP3A4 modulators described in a previous publication (15). The PBPK simulation is a practical tool for investigating drug interactions where clinical investigation is limited, especially in the case of clofazimine, which exhibits a prolonged half-life. In the absence of clinical data, we used the PBPK modeling approach to provide guidance for the treatment of NTM in pwCF, bridging the gap with the urgent need for proper dosing guidelines.

A possible future work may involve simulations of ETI coadministered with a combination of NTM antibiotics. In particular, when the inducer (rifabutin) and inhibitor (clofazimine or clarithromycin) are coadministered, the CYP3A-modulating activities may be balanced out, potentially leading to less DDI and thereby decreasing the burden of dose adjustment of ETI. One thing that should be considered is that rifabutin is also metabolized by CYP3A, so the exposure of rifabutin and 25-O-desacetyl rifabutin, its active metabolite, which exerts almost the same potency as that of rifabutin, can be affected by concomitant use with a CYP3A inhibitor, requiring further research to determine the optimal regimen of ETI, inhibitor, and rifabutin.

In conclusion, using a PBPK modeling approach, we determined adjusted dosing regimens of ETI when administered concomitantly with NTM therapies that will likely decrease the impact of DDIs. The outcome of this study provides preliminary guidance on dosing of NTM treatments in patients with CF while they continue to receive highly active CFTR modulators. In addition, this work provides tools to address new drug interactions and to suggest timely guidelines for dose adjustments where clinical trial data do not yet exist.

MATERIALS AND METHODS

PBPK population model and trial design.

The models were implemented within the Simcyp Simulator (version 21; Certara, Sheffield, UK). In the default adult healthy population library file (Sim-Healthy volunteers) provided in Simcyp, the distribution of ages and proportion of females were corrected to reflect the demographics of the CF population based on the “Patient Registry: 2020 Annual Report” published by the Cystic Fibrosis Foundation (15, 33). The corrected healthy population library file was used for all simulations, since PK parameters of ETI were not found to differ between healthy adults and pwCF (15, 19, 20, 34). It should be noted that the simulation results apply to adults with CF only, as the simulated population includes ages between 18 and 65 years. For the trial design, a total of 10 trials with 10 subjects per trial were simulated (10 × 10 design).

To predict the effect of CYP3A modulators on ETI pharmacokinetics, published PBPK models of ETI that we previously verified using known DDI liability data were employed (15). Briefly, the ETI models were developed based on available physicochemical properties and clinical data from published PK studies (15). Since ETI is predominantly eliminated through CYP3A-mediated hepatic metabolism, the excretion was set to enzyme kinetics to quantify the metabolism by CYP3A. The fraction of ETI being metabolized by CYP3A (fmCYP3A) was set to 98%, 73.2%, and 67% for ivacaftor, tezacaftor, and elexacaftor, respectively, with ivacaftor being the most sensitive CYP3A substrate among the ETI components. The models were validated against PK profiles of ETI after single and multiple administrations of clinically relevant doses. Upon accurate recapitulation of the PK of ETI, the models were further assessed against the clinical DDI data with strong CYP3A modulators, which indicated that the models were adequate for the assessment of DDI.

For clofazimine, we incorporated the induction potential acquired from an in vitro induction assay (described below) into a published model that contains the inhibition potential (24). For rifabutin and clarithromycin, the validated compound files provided in Simcyp (version 21) were used.

(i) Clofazimine induction assay. While clofazimine’s inhibition potential (K_i) for CYP3A is known and has been incorporated into a published PBPK model (24), no quantitative measurement of its induction potential has been performed. Therefore, for completeness of the model, we quantified its induction potential by assessing the changes in CYP3A4 mRNA upon treatment of cryopreserved primary human hepatocytes with clofazimine. Cells were obtained from GIBCO/Life Technologies and were cultured according to the manufacturer’s instructions (35). After the cell attachment period, cells were treated daily for two consecutive days with fresh culture medium containing either vehicle control (0.1% dimethyl sulfoxide [DMSO]), clofazimine, or rifampin at concentrations ranging from 0.01 to 50 μM. Quantification of CYP3A4 mRNA induction was performed using SYBR green-based quantitative PCR. The maximal fold induction (E_max) and the concentration resulting in half-maximal induction (EC₅₀) of CYP3A4 for each compound were determined after curve fitting using GraphPad Prism (version 5).

(ii) Clofazimine PBPK model development. The clofazimine model was constructed based on a published PBPK model, with the addition of the induction potential (EC₅₀, E_max) determined by the induction assay. The in vitro EC₅₀ and E_max data for clofazimine were calibrated against in vitro data for rifampin, for which the CYP3A induction potential is well characterized. The fraction of unbound drug in the in vitro hepatocyte incubation (fuinc) was predicted using a quantitative model previously established by Austin et al. (17, 36). The developed model of clofazimine was further assessed against the observed DDI data with bedaquiline (CYP3A substrate with fmCYP3A of 16%) (37) to verify that the model was adequate for the assessment of DDIs. The published model of bedaquiline that has been verified against its interacting drugs was used (38).

DDI predictions with selected NTM antibiotics.

We first simulated the steady-state PK of standard-dose ETI alone and when coadministered with rifabutin 300 mg daily, clofazimine 100 mg daily, and clarithromycin 500 mg every 12 h in accordance with the guideline for treatment of NTM in CF (2). The durations of coadministration with rifabutin, clarithromycin, and clofazimine were set to 20, 50, and 130 days, based on the timelines required to reach steady state. Additional simulations were run to evaluate the transitions after the discontinuation of the antibiotics due to the time-dependent CYP3A-modulating activities of rifabutin, the prolonged elimination half-life of clofazimine (25 days) (24), and the prolonged mechanism-based CYP3A inhibition effects of clarithromycin. To quantify the DDIs, the geometric mean ratios of AUC or C_max with or without the presence of CYP3A modulators were calculated. We further simulated adjusted dosing regimens of ETI when coadministered with the NTM antibiotics to determine the optimal dosing regimen targeting an AUC of ETI within the bioequivalence limit (0.80 to 1.25) relative to that of the standard regimen.