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Abstract

Objectives:

Theophylline is used in the treatment of chronic obstructive pulmonary disease but readily causes symptoms of intoxication and exhibits high risks in elderly patients. However, there have only been a few recent reports on the significance of therapeutic drug monitoring (TDM) implementation, especially in elderly patients. To examine the usefulness of theophylline TDM, we evaluated the current status of prescriptions containing theophylline and its side effects and assessed the influence of aging, sex, drug formulation, and concurrent drugs use on theophylline exposure using data from various nationwide databases and a pharmacokinetic modeling approach.

Methods:

We utilized sampling data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan. Using the data of patients aged ≥80 years, we conducted an association analysis of theophylline and concurrent drugs. The transition in plasma theophylline concentration levels of elderly patients was estimated based on a previously reported physiological-based pharmacokinetic model.

Results:

Altogether, 3973 patients using theophylline were registered in our dataset, and about 50% were over 70 years old and used theophylline. Therapeutic drug monitoring implementation was confirmed in only 1.13% of patients. The association analysis confirmed a frequent co-occurrence with allopurinol and famotidine, which increase theophylline exposure, in elderly patients aged ≥80 years. The physiologically based pharmacokinetic model indicated that theophylline trough concentrations were 1.65-fold higher in elderly patients aged 80 years compared to those aged 30 years and 1.35-fold higher in females compared to males.

Conclusion:

This study effectively combined information on the nationwide health care database and modeling approach, indicating the importance of proactive TDM and dose justification for female and elderly patients.

Keywords

Theophylline therapeutic drug monitoring modeling and simulation database drug information

Introduction

Theophylline is a drug with anti-inflammatory and bronchodilator effects, used in treating respiratory diseases such as chronic obstructive pulmonary disease (COPD), asthma, and emphysema. Chronic obstructive pulmonary disease is a disease caused by long-term exposure to harmful substances such as smoking, and its incidence increases with age. Therefore, in severe cases of COPD, pharmacotherapy with theophylline is considered standard practice. However, the effective therapeutic range of theophylline is relatively narrow at 5–20 µg/mL.^1,2 Furthermore, exceeding a concentration of 25 µg/mL leads to intoxication symptoms such as nausea, vomiting, and arrhythmia.^3,4 Particularly, in elderly patients, physiological changes with age and concurrent drug use increase the risk of high drug exposure^5,6; indeed, a high incidence of theophylline intoxication among elderly patients aged ≥80 years was reported in Japan and in patients who developed theophylline intoxication, treatment was administered at a higher dose.⁷ Therefore, in actual clinical practice, it is recommended to perform therapeutic drug monitoring (TDM) using the plasma drug concentration as an indicator; however, few reports on the current situation regarding TDM of theophylline and the usefulness of TDM implementation in the elderly.

Recently, analyses using various databases and modeling and simulation (M&S) methods have drawn attention as research methods in the field of clinical pharmacology and have been applied in a wide range of fields, such as clinical development and safety evaluations.^8,9 Information from real-world databases enables access to a broader range of patient data than that typically acquired in clinical trials. In studies using M&S, the exposure levels can be quantitatively predicted in various circumstances, such as in elderly patients or patients under polypharmacy. Research using these methods is highly useful for identifying new issues that arise in the medical practice and has not been evident at the time of drug development.

Herein, we aimed to investigate the status of theophylline prescription and side-effect onset using information obtained from various databases available in Japan and evaluate the effect of aging, sex, drug formulation, and concurrent drug use on theophylline exposure based on a pharmacokinetic M&S.

Methods

Figure 1 shows the overall study flow. The present study was conducted according to the principles stipulated in the Declaration of Helsinki and the Ethical Guidelines for Medical and Biological Research Involving Human Subjects. Additionally, upon obtaining permission to use the NDB receipt data from the Ministry of Health, Labour, and Welfare, study approval was obtained from the ethical review board of Musashino University (Approval number: R5–3).

Figure 1.

The workflow of the present study.

Data sources

This cross-sectional study of the number of theophylline prescriptions, concurrent drug use, and TDM implementation utilized anonymized medical insurance claim information. We used a sampling dataset (2020, January) of the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), provided by the Japanese Ministry of Health, Labour and Welfare. The NDB encompasses ˃98% of Japan's medical insurance receipt data. Our analysis was based on a sample dataset extracted from the NDB, including outside hospitals and community pharmacy receipt data. We selected 1% of patient records with identifiable patient IDs from medical outpatient and pharmacy receipts, ensuring that population and composition ratios remained consistent across sex and age groups with five-year intervals.¹⁰ DPC receipts without patient IDs were excluded from the dataset as they could not be linked to pharmacy receipts. Therefore, no selection or exclusion criteria are established, and we cannot specify the sample size. This selection process included the exclusion of costly receipts to safeguard patient identities. As a result of these anonymization procedures, obtaining informed consent was unnecessary. Based on the medical service fee and in-hospital drug dispensing data, patients with specific drug management charges calculated on the drug dispensing receipt and medical service fees calculated on the medical department inpatient/outpatient receipt were categorized as the TDM implementation group, and the remaining patients were categorized as the TDM implementation unknown group. Clinical drug–drug interaction information for theophylline was collected from the Drug Interaction Database (DIDB, Certara, St Louis, MO, https://www.druginteractionsolutions.org), which is a database containing information on drug–drug interactions obtained from peer-reviewed publications and recent NDA/BLA reviews. Using the area under the concentration–time curve ratio (AUCR) (the ratio of AUC in the presence of an interacting drug to that in the absence) as a metric, drugs that exerted an impact on theophylline exposure with an AUCR ˃1.25 were extracted, as classified by the US Food and Drug Administration as weak inhibitors (AUCR = 1.25–2.0).¹¹

Association analysis of drugs affecting theophylline exposure

Drugs that affect theophylline exposure and the state of their concurrent usage were evaluated via an association analysis, a data mining method to extract statistical patterns and significant relationships from a considerable amount of data.¹² Herein, using data of patients aged ≥80 years who were registered in the NDB, we examined the confidence value between theophylline and precipitant drugs affecting theophylline exposure (the rate of including theophylline at the same time in a prescription including the target drug), support value (the rate including theophylline and target drug in all prescriptions), and lift value (an indicator showing the relationship of concurrent use of the target drug and theophylline, whereby ≥1 indicates a positive correlation).

Physiologically based pharmacokinetic M&S

We used Phoenix^® NLME™ version 8.1 (Certara, St Luis, MO) for model construction and each simulation. The changes in plasma theophylline concentration were estimated based on the physiologically based pharmacokinetic (PBPK) model reported by Navid et al.¹³ The absorption rate constant was 0.14/h for long-acting tablets (once daily).¹⁴ For the data on distribution volume between various tissues and flow rates, we used the parameters of Asian males and females (Supplemental Figure 1 and Table 1). Compared with drug metabolism in young patients (aged 30 years), it was reported that the liver and kidney functions in elderly patients (aged 80 years) declined by 0.66- and 0.27-fold, respectively. We incorporated these data in our PBPK model.¹³

Table 1.

Association analysis of drugs influencing theophylline exposure (over 80 years old).

Precipitant drug	AUCR	Confidence (%)	Support (%)	Lift
Fluvoxamine¹⁶	2.38	0.31	<0.001	0.36
Mexiletine¹⁷	1.95	1.52	0.0040	1.77
Cimetidine¹⁸	1.82	1.30	0.0023	1.52
Famotidine¹⁹	1.56	1.58	0.0687	1.84
Ciprofloxacin²⁰	1.52	1.67	<0.001	1.95
Acyclovir²¹	1.45	0.97	<0.001	1.13
Allopurinol²²	1.34	2.60	0.0505	3.03
Verapamil²³	1.28	1.49	0.0119	1.75

AUCR: ratio of area under the curve (AUC) in the presence of an interacting drug to that in the absent; AUCR: theophylline AUC with precipitant / theophylline AUC without precipitant.

Assuming the following situations in Japanese clinical setting, PBPK M&S was performed for each age group, assuming the concurrent use of representative drugs shown in Table 1: (I) plasma concentration-time profiles when young (30 years) and older (65 and 80 years) male and female were administered theophylline at doses of 400 and 200 mg/day; and (II) changes in plasma concentration in the same subjects as in (1), assuming concurrent use of representative drugs that affect theophylline exposure and was extracted by the association analysis.

Statistical analysis

Statistical analyses were performed using the SPSS software package (version 26, SPSS Inc., Chicago, IL, USA) and the R Commander plug-in of the EZR package (version 4.0.2, RcmdrPlugin.EZR).¹⁵ Differences were considered significant for p < 0.05. Association analysis was performed using the Visual Mining Studio software package (version. 9.0, NTT DATA Mathematical Systems Inc., Tokyo, Japan).

Results

From the NDB sampling dataset, information on the number of patients, sex, dosage forms, and the number of concomitant medications by five years age group was obtained. In the NDB sampling dataset (January 2020), 3,776,358 drug prescriptions (patients aged ≥ 80 years: 899,747 drug prescriptions), 908,504 dispensing receipts (patients aged ≥ 80 years: 141,087), and 456,156 patients (patients aged ≥ 80 years: 59,627 patients) were registered. Altogether, 3973 patients used theophylline (male:female = 45.3%:54.7%); among whom, 97.6% used controlled-release tablets, 1.29% used controlled-release dry syrup, 0.56% used a syrup, and 0.52% used controlled-release granules. The prescription percentage per age group and sex is presented in Figure 2. The prescription percentage was the highest in patients aged 80–84 years at approximately 12%. The annual total usage percentage was 21.8% and 27.7% for those aged 70–79 years and ≥80 years, respectively. Furthermore, there was no difference in male and female drug prescriptions among the age groups (p = 0.37, F-test, Figure 2).

Figure 2.

Prescription rates for theophylline by age group (national database sampling dataset).

Among patients with calculations as specific drug management charges or as medical service fees calculated on the medical department inpatient/outpatient receipt, 1148 patients had confirmed theophylline prescriptions, among whom TDM was performed in only 13 patients. The theophylline dose distribution per day for the TDM implementation and TDM implementation unknown groups is presented in Figure 3. Theophylline is usually administered at a dose of 400 mg/day; however, in both the TDM implementation and TDM implementation unknown groups, a dose of 200 mg/day was most commonly administered in 53.8% and 59.1% patients, respectively, whereas a dose of 400 mg/day was administered in 30.8% and 24.3% patients, respectively (No significant difference in dosage between the TDM and Unknown groups.).

Figure 3.

Daily dose of theophylline in therapeutic drug monitoring and unknown group.

The results of the association analysis of theophylline and concurrent drugs in elderly patients aged ≥80 years are presented in Table 1. In all the receipts, 174,172 prescriptions were found for patients aged ≥80 years, including 1476 prescriptions for theophylline (0.85%). Fluvoxamine was reported to have the most increases in theophylline exposure (AUCR = 2.38), and it was confirmed that theophylline was used concurrently in 0.31% of the patients. The concurrent use of theophylline was found in 2.60% of patients taking allopurinol, with the highest lift value of 3.03 among the precipitant drugs examined in the association analysis. Famotidine was used concurrently with theophylline in 0.0687% of patients, exhibiting the highest support value among the precipitant drugs examined.

The changes in plasma concentrations in patients aged 30, 65, and 80 years, assuming the currently use of fluvoxamine, allopurinol, or famotidine with theophylline, are shown in Figure 4. Using the model, the theophylline trough concentration and AUCR were estimated to be 1.82- and 1.65-fold higher in elderly patients aged 80 years, 1.50- and 1.39-fold higher in elderly patients aged 65 years compared with that of healthy young patients (30 years of age, Supplemental Table 2). Females exhibited trough concentration and AUCR 1.35 times higher than males. In women, the plasma concentration levels were estimated to exceed 20 µg/mL in female patients aged 30 years administered at a dose of 400 mg/day with fluvoxamine and those aged 80 years at a dose of 200 mg/day (Figure 4C and D).

Figure 4.

Simulated plasma theophylline concentration–time profile in 30-, 65-, and 80-years patients.

Discussion

This research provided information on the appropriate use of theophylline using real-world data and the M&S method. Theophylline is designated as a TDM drug and has been available on the market for an extended period, and over time, a wealth of information has been accumulated regarding its efficacy and safety during the post-marketing processes compared to its new drug development and approval stages. For pharmaceutical products such as theophylline, an approach involving dose adjustment based on combining prescription data, adverse event reporting, and M&S is considered particularly valuable in terms of ensuring the appropriate use of the drug.

While TDM is recommended for theophylline, herein, the implementation of TDM was confirmed in 13 out of 1148 patients (1.13%) in the NDB sampling data, suggesting a low likelihood of TDM being conducted in actual clinical practice. When treatment becomes chronic, as in COPD, and long-term drug therapy is administered, dosing adjustments may be made while observing clinical symptoms, and if symptoms remain relatively stable, TDM with blood sampling may be avoided.²⁴ In particular, treatment with low doses (200 mg/day) of theophylline tends to be safer and may avoid the need for TDM.²⁵ Indeed, the TDM unknown group tended to have lower doses than the TDM group (Figure 2). However, the plasma concentration levels in elderly patients can potentially and easily increase under various clinical situations, resulting in adverse events. In fact, the odds ratio for theophylline-induced intoxication calculated from the Japanese Adverse Drug Event Report database (February 2023), provided by the Pharmaceuticals and Medical Devices Agency,²⁶ was 6.7, and reportedly, in patients aged ≥80 years, theophylline-induced intoxication can easily occur.⁷ The typical symptoms of theophylline intoxication include nausea, vomiting, and arrhythmia, which are nonspecific, rendering it more difficult to identify the onset of adverse events in long-term users. Therefore, performing regular TDM using plasma concentration as an indicator is indispensable.

Many elderly patients take multiple drugs to treat comorbidities. Theophylline is eliminated primarily by hepatic metabolism; thus, an aging-related decline in hepatic blood flow and a decrease in the activity of metabolizing enzyme P450 causes concern for reduced hepatic clearance.^5,13 CYP1A2 is the major metabolizing enzyme of theophylline²⁷; therefore, the concurrent use of drugs that inhibit CYP1A2 carries the risk of adverse events associated with high exposure to theophylline. In this study, all eight drugs identified as increasing theophylline exposure (Table 1) were inhibitors of CYP1A2. Therefore, we conducted an association analysis with extracted CYP1A2 inhibitors. In addition, we also analyzed the prescription trends of concurrent drugs in patients aged ≥80 years. The association analysis showed that the confidence value of fluvoxamine with theophylline was relatively low at 0.31, indicating the concurrent use of fluvoxamine tended to be avoided in medical practice. Contrarily, the other seven drugs had a lift value of ≥1, and a tendency of avoidance was not observed. In particular, numerous patients were administered famotidine or allopurinol concurrently. According to the results of the M&S analysis, it was suggested that in female patients, the change in plasma theophylline concentration levels under the concurrent use of fluvoxamine could reach toxic levels even when 400 mg/day was administered in patients aged 30 years and 200 mg/day was administered in patients aged 80 years. Furthermore, females weigh approximately 30% less than males, and when administering typical doses, ignoring gender-based differences in size may increase the risk of adverse events associated with high exposure.¹² Therefore, in elderly patients, even though a low dose is started, it is still possible that the plasma concentration level can reach toxicity owing to a combination of factors such as age, sex, and concurrent drug use. Hence, it is important to recognize factors that increase the risk of theophylline exposure (female, elderly, CYP1A2 inhibitors) and to have a good understanding of symptoms of intoxication. Regular monitoring of adverse effects and plasma concentrations is crucial for at-risk patients. In this study, the PBPK M&S presents the median change in plasma theophylline concentration levels, assuming a single concurrent drug. However, in real-world clinical scenarios, many elderly patients use multiple drugs simultaneously. Concurrent drug use with an AUCR < 1.25 was not factored in. The synergistic metabolism-inhibiting effects of these precipitant drugs underscore the necessity to vigilantly monitor patients, especially the female and elderly, at risk of heightened plasma concentrations for signs of intoxication and changes in plasma theophylline levels.

Although we provide an important safety outcome of theophylline therapy, the present study utilized information from a sampling dataset of the NDB and thus has several limitations. First, despite theophylline being used for treating COPD and other diseases, such as bronchial asthma, we have not conducted an examination according to different underlying diseases. Therefore, it is possible that the present study included several confounding factors (e.g. body weight, organ function, and concomitant drugs) in addition to age, sex, dose, and concurrent drug use, and there was an unavoidable selection bias. Second, since the NDB sampling dataset used in this study consists of data limited to a single month, evaluating monthly changes was not feasible, and identifying changes not included in the dataset proved challenging. However, the NDB comprehensively collects insurance claims data, including comprehensive data on elderly care, making it one of the most reliable datasets for accurately capturing the current state of clinical institutions in Japan. This allows for generalization and rapid insights into the real-world situation.

Conclusion

Theophylline is frequently prescribed to elderly patients, and even at a low dose (200 mg/day), there is a risk of reaching toxic levels depending on age, sex, and concurrent medications. This underscores the importance and necessity of TDM in the female and elderly patients. Numerous pharmaceuticals have long been commercially available and with whose usage healthcare providers have extensive experience; however, TDM implementation for pharmaceuticals with a risk of intoxication is limited. The present study is highly significant, employing a large-scale database and pharmacometrics that provides evidence to administer theophylline therapy more effectively and safely for female and elderly patients; thus, our findings should be widely communicated to healthcare professionals.

Supplemental Material

sj-docx-1-sci-10.1177_00368504241285122 - Supplemental material for Current status and usefulness of therapeutic drug monitoring implementation of theophylline in elderly patients based on a nationwide database study and modeling approach

Supplemental material, sj-docx-1-sci-10.1177_00368504241285122 for Current status and usefulness of therapeutic drug monitoring implementation of theophylline in elderly patients based on a nationwide database study and modeling approach by Akira Okada, Shoji Sera, Maho Taguchi, Hiroaki Yamada and Naomi Nagai in Science Progress

Footnotes

Author contributions

AO,SS,MT,HY,and NN contributed equally to the conception,design of the research,and acquisition of the data;AO,SS,and MT contributed to the analysis of the data. All authors critically revised the manuscript,read and approved the final manuscript,and agreed to be fully accountable for ensuring the integrity and accuracy of the work.

Acknowledgements

The authors thank Ms. Moe Ishigaki from Musashino University for assisting in collecting some data for this study and Enago (

) for the English language review.

Availability of data and materials:

All data and materials included in this study are available upon request by contact with the corresponding author. Drug Interaction Database files can be downloaded from [

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Ethics approval and consent to participate:

Upon obtaining permission to use the NDB receipt data from the Ministry of Health,Labour,and Welfare,study approval was obtained from the ethical review board of Musashino University (Approval number: R5–3). As a result of these anonymization procedures,obtaining informed consent was unnecessary.

Funding

The authors disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: This study was supported by a grant from the Japan Agency for Medical Research and Development (AMED) under grant number JP21mk0101159h0003.

ORCID iDs

Akira Okada

Shoji Sera

Supplemental material

Supplemental material for this article is available online.

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