https://orcid.org/0000-0001-5201-4090
Figures
Abstract
Ticagrelor, a commonly used antiplatelet medication, has been found to exhibit considerable inter-individual pharmacodynamic variability. Recent studies have revealed a close relationship between pharmacokinetics and pharmacodynamics, both of which can be influenced by gut microbiota. In this study, we explored whether the pharmacokinetics of ticagrelor is mediated by intestinal flora. We enrolled 22 healthy participants to assess the clinical pharmacokinetic profiles of ticagrelor and its metabolite AR-C124910XX after a single oral dose of ticagrelor. The fecal microbial compositions of individuals who exhibited distinct pharmacokinetic parameters were analyzed using 16S rRNA gene sequencing. Additionally, we conducted experiments involving the co-incubation of ticagrelor with fecal bacteria and a systematic exploration of the pharmacokinetics of ticagrelor in pseudo-germ-free (PGF) rats to illustrate the role of gut microbiota in ticagrelor metabolism, both in vitro and in vivo. Our findings revealed a three-fold difference in the bioavailability of ticagrelor among individuals. However, no difference was found in the composition of gut microbiota among individuals with different pharmacokinetic parameters. Quantitative analysis showed that gut microbiota cannot directly metabolize ticagrelor. Furthermore, there were no significant differences in AUC(0–48), AUC(0-∞), and Cmax between ticagrelor and AR-C124910XX in PGF rats compared to normal control, either by single intragastric or intravenous administration. In conclusion, these findings suggest that gut microbiota has no impact on the pharmacokinetics of ticagrelor.
Citation: Qu P, Gao Y, Li X, Yang L, Tang J, Chen M, et al. (2026) Ticagrelor and gut microbiota: Absence of pharmacokinetic interaction in vitro and in vivo studies. PLoS One 21(10): e0359660. https://doi.org/10.1371/journal.pone.0359660
Editor: Hideo Kato, Mie University Hospital: Mie Daigaku Igakubu Fuzoku Byoin, JAPAN
Received: January 19, 2026; Accepted: September 16, 2026; Published: October 1, 2026
Copyright: © 2026 Qu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The 16S sequencing microbiota data reported in this paper have been deposited in the Genome Sequence Archive for Human (GSA-Human) at the National Genomics Data Center, China National Center for Bioinformation (GSA Accession Number: HRA019780). These data are publicly accessible via the GSA-Human browse page: https://ngdc.cncb.ac.cn/gsa-human/browse/. Any additional information required to reanalyze the data reported in this work is available from the institutional contact (fanlan_038038@163.com) upon reasonable request.
Funding: This study was partly supported by the National Key Research and Development Program of China (2021YFA1301200), the National Natural Science Foundation of China (82373961, 82073945), the scientific research project of Furong Laboratory of Central South University (2023SK2083), and the Natural Science Foundation of Hunan Province (2022JJ30949). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
Ticagrelor, a cyclopentyltriazole compound, is a selective adenosine diphosphate receptor antagonist with a dual pathway inhibitory effect on platelets [1,2]. The latest American College of Cardiology and American Heart Association guidelines recommend ticagrelor as a first-line agent for the treatment of acute ST-segment elevation myocardial infarction (STEMI) [3]. However, there are significant individual differences in the clinical efficacy of ticagrelor. The PLATO subgroup study found that approximately 3%−27% of patients had a low response to ticagrelor (platelet reactivity index > 50%) [4]. Gene polymorphisms have limited effects on ticagrelor: P2RY12, P2RY1, and ITGB3 polymorphisms do not affect the inhibition of platelet aggregation by ticagrelor [5], and CYP2C19 and ABCB1 polymorphisms do not affect the clinical efficacy of ticagrelor [6]. Therefore, the factors that contribute to the individual differences in ticagrelor efficacy need to be further explored.
Studies have shown that changes in pharmacokinetics can alter drug efficacy and side effects [7]. Gut microbiota has been identified as an important factor in the regulation of drug pharmacokinetics and pharmacodynamics, as well as individual variability in drug response [8]. Recent studies have demonstrated that gut microbiota may affect drug biotransformation including absorption, distribution, metabolism, and excretion, which in turn affects pharmacodynamics, such as the ability of intestinal bacteria to convert drugs into biologically active substances (Sulfasalazine, lovastatin, and ginsenoside Rb1), inactive substances (Ranitidine and metronidazole), and toxic metabolites, etc [8–12]. Currently, the mechanisms of drug pharmacokinetics influenced by gut microbiota can be divided into three main categories: (1) Direct metabolism [13]; (2) Bioaccumulation [14]; (3) Gut microbiota metabolites alter drug pharmacokinetics by affecting metabolic enzymes, transporters [15]. Previous research has tentatively established a potential relationship between the plasma concentration of ticagrelor and its metabolite AR-C124910XX and gut microbiota [16]. However, the effects of gut microbiota on the pharmacokinetics of ticagrelor are not well explored.
Herein, with genetic polymorphism almost ruled out, we intended to explore whether the gut microbiota affects the pharmacokinetics of ticagrelor. By enrolling healthy subjects, we found significant individual differences in the pharmacokinetic profiles of ticagrelor and its metabolite AR-C124910XX, but no differences in the composition of gut microbiota among individuals with distinct pharmacokinetic parameters. Ticagrelor couldn’t be metabolized by gut microbiota in vitro. By comparing the plasma concentration of ticagrelor and AR-C124910XX in pseudo-germ-free (PGF) rats with control rats, we confirmed that gut microbiota had no influence on the pharmacokinetics of ticagrelor in vivo. Our results implied that gut microbiota may not be responsible for the pharmacokinetic differences in ticagrelor.
2. Materials and methods
2.1. Materials and reagents
Ticagrelor tablets (AstraZeneca Co., Ltd.), ticagrelor (98% purity, Aladdin Co., Ltd.), and AR-C124910XX (Push Bio-technology Co., Ltd.). Carbamazepine (98% purity) was provided by the National Institutes for Food and Drug Control (Beijing, China) and was selected as the internal standard (IS) for the pharmacokinetics experiment. Ampicillin, metronidazole, vancomycin hydrochloride, and neomycin sulphate were purchased from Sangon Biotech Co., Ltd (Shanghai, China). Gifu Anaerobic Medium, modified (mGAM) was purchased from Nissui Co., Ltd (Tokyo, Japan). QIAamp® PowerFecal® Pro DNA Kit was purchased from QIAGEN (Hilden, Germany).
Methanol was purchased from Merck & Co., Inc. (Kenilworth, NJ, USA). Formic acid was purchased from ANPEL Laboratory Technologies Inc.(Shanghai, China). Unless otherwise stated, all reagents were of analytical grade.
2.2. Human studies
The recruitment period for this study was conducted from June 1, 2020, to August 31, 2020. All participants in this study have signed the informed consent form, and the study protocol has been approved by the Institutional Review Board of the First Affiliated Hospital of Shantou University Medical College (ethical number: 2019005). All subjects were 19–36 years old and in good health. The health status of subjects was judged based on medical history, physical examination, and routine laboratory tests. These subjects had not taken any medications (prescription or nonprescription) for 2 weeks before the study and did not anticipate any need for medication during the study. The clinical details of the included cases are listed in S1 Table.
Twenty-two subjects received oral 90 mg ticagrelor with 240 mL water, which was to be swallowed whole, not swallowed or chewed. Plasma samples were collected at designated times for pharmacokinetic analysis. For the subjects, blood samples were collected before drug administration (0 h), and at 20, 40 min, 1, 1.5, 2, 2.5, 3, 4, 6, 8, 12, 24, 36, and 48 h after dosing. 4 mL of blood was collected into a labeled K2-EDTA anticoagulation tube, which was centrifuged at 2,000 × g at 4 °C for 10 min. The plasma supernatants were stored below −80 °C until assay. Hierarchical clustering analysis was applied to identify subject clusters with different pharmacokinetic parameters.
2.3. 16S rRNA sequencing for human gut microbiota
The compositions of the intestinal flora of fecal samples from 22 volunteers were examined by 16S rRNA sequencing analysis. The total DNA was isolated from stool samples. After extracting the total DNA of the samples, PCR amplification was performed and the products were purified, quantified, and homogenized to form sequencing libraries. The constructed libraries were first subjected to quality control, and the libraries that passed the quality control were sequenced by Illumina NovaSeq. The results are stored in FASTQ (fq) file format, which contains the sequence information and sequencing quality information. High-quality clean tags were obtained by splicing and filtering the original Reads, followed by subsequent analysis using the EasyAmplicon [17] pipeline. Then the data were subjected to basic analysis and the processed tags were denoised with “unoise3” to obtain single-base precision ASVs, which were dechimerized, deplasmidized, and non-bacterialized. Species annotation, diversity analysis, and species composition analysis of ASV representative sequences were performed using the Silva database. The α-diversity was computed by the R package ‘vegan’, and the β-diversity was calculated by principal coordinate analysis (PCoA) at the ASV level. The linear discriminant analysis (LDA) effect size (LEfSe) method was applied to explore biomarker features.
2.4. Gut microbiota preparation
An appropriate amount of human or rat fresh fecal sample was suspended well in cold physiological saline (w/v, 1:20) before vortexing for adequate mixing and then centrifuged at 500 rpm for 5 min at 4 °C. The resultant fecal supernatant was decanted and centrifuged at 4,000 rpm for 30 min at 4 °C, then the precipitate was re-suspended with 2.5 mL of mGAM to produce gut microbiota suspension. Stocks were generated by adding glycerol to the gut microbiota suspension (final concentration of glycerol, 20%) and were anaerobically stored in −80 °C freezer [18].
2.5. Ticagrelor preparation and co-incubation with fecal samples
Gut microbiota stock was activated with mGAM broth (1:20). After incubation for 24 h, the medium was centrifuged at 4,000 rpm for 30 min at 4 °C. The supernatant was discarded and the precipitate was re-suspended in mGAM broth as the gut microbiota work solution. The biotransformation of the ticagrelor by the gut microbiota was performed in an incubation system containing 500 μL of the gut microbiota work solution and 5 μL of ticagrelor solution (1.07 μg/mL, solution in dimethyl sulphoxide). Negative control was performed in an incubation system containing 500 μL of the mGAM broth and 5 μL of ticagrelor solution. The incubation system was anaerobically incubated at 37 °C for 24 h and stopped with the addition of 600 μL cold methanol including IS (carbamazepine) in a 200 μL incubation system. The samples were centrifuged at 14,000 rpm for 10 min and detected by UPLC-MS/MS.
2.6. Animals
SD rats (specific pathogen-free (SPF), Certificate No. SCXK2019–0004), 250 ± 20 g, were purchased from Hunan SJA Laboratory Animal Co., Ltd (Changsha, China). The animals were maintained in the SPF animal facilities of the Animal Experimental Center of Central South University and natural light-dark cycle conditions with controlled temperature (22 ± 2°C), food and drinking water supplied unrestricted. All animal work was done in accordance with the National Institutes of Health’s Guide for the Use and Care of Laboratory Animals and was approved by the Institutional Review Board of Central South University (Hunan, China. permission numbers: CSU-2022-0001-0017).
Rats were acclimated to the laboratory for 1 week before the experiment and randomized into two treatment groups: control group and PGF group (pseudo-germ-free) (n = 8). Rats in the PGF group were gavage with an antibiotic cocktail (100 mg/kg ampicillin, 100 mg/kg neomycin sulfate, 100 mg/kg metronidazole, and 50 mg/kg vancomycin), and provided with an antibiotic cocktail (0.25 g/L ampicillin, 0.25 g/L neomycin sulfate, 0.25 g/L metronidazole and 0.125 g/L vancomycin) in drinking water for 2 weeks to deplete the intestinal flora. To validate the pseudo-sterile rat model, rat feces were collected and fecal DNA was extracted using a QIAamp® PowerFecal® Pro DNA kit. The amount of intestinal microbiota DNA was measured using a BioSpec-nano spectrophotometer to assess the stability and validity of the pseudo-sterility model [19].
All surgeries were performed under anesthesia (isoflurane). Animals were euthanized when humane endpoints were reached, which included abnormal posture, failure to groom, lethargy, impaired ambulation or paralysis, weight loss exceeding 20% normal body weight, and the inability to voluntarily access food and water. Rats reaching these endpoints were euthanized immediately via CO2 inhalation followed by cervical dislocation to minimize suffering and distress. Animals were monitored daily for health and behaviour, and no animals died before meeting euthanasia criteria. All research staff received training in animal anaesthesia, animal surgery, experimental procedures, and monitoring/nursing. All animal welfare considerations were taken to minimize suffering and distress, including frequent monitoring and immediate euthanasia at endpoint.
2.7. Pharmacokinetic experiments
Rats were fasted 12 hours before the pharmacokinetic experiments. 18 mg/kg of ticagrelor (0.5% CMC-Na solution as solvent) was administered to the rats by intragastric gavage. Blood samples were collected from the tail vein at 0, 0.25, 0.5, 1, 2, 3, 4, 6, 7.5 and 24 h. Additionally, 3 mg/kg of ticagrelor (2% Tween 80 solution as solvent) was intravenously administered to the rats. The blood samples were collected from the tail vein at 0, 0.25, 0.5, 1, 2, 3, 4, 5, 6, and 24 h. The blood sample was centrifuged at 4,000 rpm at 4 °C for 15 min and supernatant plasma was collected and stored at −80 °C for further analysis.
2.8. Quantification of plasma ticagrelor and AR-C124910XX
Compounds were extracted from plasma by albumen precipitation method. The concentration of the ticagrelor and AR-C124910XX was determined on the AB Sciex Qtrap 6500 UPLC-MS/MS system (AB Sciex, Massachusetts, USA). Targeted analytes were separated using an ACE Excel 5 Super C18 column (150 mm x 2.1 mm, Radnor, PA, USA); the flow rate was maintained at 0.4 mL/min. The mobile phase consisted of solvent A (deionized water with 0.1% formic acid) and solvent B (methanol). A gradient program was used for the HPLC separation: 0–0.5 min (30% A); 0.5–1.5 min (30%−5% A); 1.5–2.0 min (5% A); 2.0–2.5 min (5%−30% A); 2.5–4.0 min (30% A). The oven temperature was maintained at 40℃ and the injection volume was set at 2 μL. The mass spectrometer was operated in positive ion mode through multiple-reaction monitoring. The precursor-product ion pairs monitored were m/z 523.4 → 152.9 for ticagrelor (DP 185 V, CE 46 eV), m/z 479.3 → 153.2 for AR-C124910XX (DP 155 V, CE 44 eV), and m/z 237.1 → 194.1 for carbamazepine (DP 130 V, CE 15 eV). Data were collected and processed using AB Sciex Analyst 1.4.2 data collection and integration software.
2.9. Statistical analysis
Pharmacokinetic parameters were analyzed by DAS 2.0 software (Chinese Pharmacological Association, China) using non-compartmental analysis. All data were represented as mean ± standard deviation (SD). The significance between the two groups was performed by using the unpaired two-tailed t-test or Mann-Whitney test, and p < 0.05 indicated that the difference was statistically significant.
3. Results
3.1. Individual variability in clinical pharmacokinetics of ticagrelor
To evaluate the population pharmacokinetic profile of ticagrelor in Chinese healthy individuals, 22 healthy individuals were recruited and received a single oral dose of ticagrelor (90 mg), then measured by UPLC-MS/MS. The plasma concentration-time curves of ticagrelor and AR-C124910XX within 48 h in healthy subjects are shown in Fig 1, and the mean pharmacokinetic parameters are summarized in Table 1. For ticagrelor, there was a 3-fold difference between individuals in AUC(0–48) (1,429 ng·h/mL −5,582 ng·h/mL) and AUC(0-∞) (1,568 ng·h/mL −5,746 ng·h/mL). At the same time, we found a 7-fold difference in the Cmax of ticagrelor (137 ng/mL −953 ng/mL). The AUC(0–48), AUC(0-∞), and Cmax of AR-C124910XX also showed significant individual differences. Altogether, these results indicated that large individual differences in the population pharmacokinetics of ticagrelor.
Data are represented as mean ± SD. n = 22.
3.2. Characteristics of gut microbiome of individuals with different pharmacokinetic parameters of ticagrelor
To explore whether individual differences in pharmacokinetic parameters of ticagrelor were related to gut microbiota. Subjects were divided into two groups based on ticagrelor pharmacokinetic parameters by using hierarchical clustering, Group H (with higher AUC, n = 12) versus Group L (with lower AUC, n = 10) (S1 Fig). Compared to Group L, the AUC(0–48), AUC(0-∞), Cmax, and t1/2 of ticagrelor were significantly higher than in Group H, with AUC(0–48) increased by 79.51%, AUC(0-∞) increased by 80.77%, Cmax increased by 62.43% and t1/2 increased by 30.34%. However, CL was significantly reduced by 45.51%. In addition, the AUC(0–48), AUC(0-∞), and Cmax of AR-C124910XX in Group H showed an increasing trend, but there was no statistical significance compared to Group L (S2 Fig, Table 2). These results suggested a significant increase in the bioavailability of ticagrelor for individuals in Group H.
Microbial DNA was isolated from fecal samples collected before ticagrelor administration and ed by 16S rRNA amplicon sequencing was performed to investigate the differences in gut microbiota between Group H and Group L. The results revealed no notable differences in α- (ACE, Chao, Simpson, and Shannon index) and β-diversities between Group H and Group L (Figs 2A and 2B). Additionally, we compared the abundance of bacteria taxa between Group H and Group L at phylum and genus levels. Compared with Group L, Firmicutes were significantly decreased in Group H on phylum level, while Proteobacteria were enriched (Figs 2C, E and F). At the genus level, only Faecalibacterium was found significantly enriched in Group L (P < 0.05, LDA scores > 4) (Figs 2D, E and F).
(A) The alpha diversity boxplot (ACE, Chao, Simpson, and Shannon) in the Group H and Group L. Principal coordinates analysis (PCoA) (B) using unweighted unifrac distance, weighted unifrac distance, and bray-curtis metric distance of the Group H and Group L. Composition of the gut microbiome at phylum (C) and genus (D) taxonomic levels. (E) LEsSe analysis for gut microbiota between Group H and Group L (P < 0.05, LDA scores > 4). (F) Cladogram based on LDA scores. n = 12 for the Group H, n = 10 for the Group L. ns, no significance.
3.3. Absence of biotransformation of ticagrelor by gut microbiota in vitro
To investigate the bioconversion of ticagrelor mediated by gut microbiota, fecal bacteria from humans or rats were co-incubated with ticagrelor in vitro for 24 h, and ticagrelor was detected in the co-incubation system before (0 h) and after incubation (24 h). Compared to 0 h, there was no significant change in the amount of ticagrelor after 24 h of co-incubation with either human or rat gut microbiota (Fig 3). It indicated the absence of biotransformation of ticagrelor by gut microbiota.
Mean concentration of ticagrelor in mGAM medium (A), in the co-incubation system with human fecal suspensions (B), and rat fecal suspensions (C) at 0 h and 24 h. Data are represented as mean ± SD (n = 10).
3.4. Pharmacokinetics of ticagrelor and AR-C124910XX in pseudo-germ-free rats
To further evaluate whether the pharmacokinetics of ticagrelor were changed after the gut microbiota was eliminated in vivo, a pseudo-germ-free (PGF) rat model was constructed. Compared to the control group, the number of fecal microorganisms in PGF rats decreased by 86.61% in the PGF group, suggesting that the gut microbiota was extremely disrupted after the treatment of antibiotic cocktails (S3 Fig). The pharmacokinetic profiles of ticagrelor and its metabolite AR-C1249XX are shown in Fig 4, and the corresponding mean pharmacokinetic parameters are listed in Table 3 and Table 4. In oral study, no obvious changes were identified in the main pharmacokinetic parameters of ticagrelor and AR-C124910XX between control and PGF group, except for slight increases in MRT(0–24), MRT(0-∞) of ticagrelor and MRT(0–24), MRT(0-∞), and t1/2 of AR-C124910XX after microbiota depletion (Figs 4A and B, Table 3). Moreover, no significantly different pharmacokinetic parameters of ticagrelor were found after single intravenous administration (Fig 4C, Table 4), only minor increases in MRT(0–24), MRT(0-∞), and t1/2 of AR-C124910XX were identified in PGF rats (Fig 4C, Table 4). Combined with the above finding that the gut microbiota cannot directly metabolize ticagrelor, these results suggest that the gut flora has less influence on the pharmacokinetics of ticagrelor.
Data are represented as mean ± SD (n = 8).
4. Discussion
Compared with traditional antiplatelet drugs, ticagrelor is recommended as a first-line drug for the treatment of STEMI due to its rapid and stable onset of action. However, 20% of STEMI patients have no obvious response to ticagrelor, showing a delayed response. Individual differences in pharmacokinetic parameters have been proven to be one of the important factors affecting drug efficacy. In our present study, plasma concentrations of ticagrelor and its active metabolite AR-C124910XX were detected by recruiting healthy volunteers and found that the AUC(0–24) and AUC(0-∞) of ticagrelor and AR-C124910XX were 3-fold different between individuals, suggesting that there are large individual differences in the population pharmacokinetics of ticagrelor, which may affect drug efficacy.
Accumulating studies have focused on the influence of gut microbiota on drug pharmacokinetics and pharmacodynamics, which can alter drug bioavailability and efficacy either directly by producing active enzymes or indirectly by affecting host transporters or metabolizing enzymes through their metabolites [8]. However, most of the previous studies on the pharmacokinetics of ticagrelor only focused on the host gene polymorphisms but failed to well explain the individual pharmacokinetic differences, while ignoring the important role of the gut microbiota. In this study, we hypothesized that the pharmacokinetic differences in ticagrelor were likely due to the changes in the gut microbiota of different individuals.
By 16S rRNA sequencing, we analyzed the compositions of gut microbiota of individuals with different ticagrelor bioavailability. However, no significant correlation was found between gut microbiota and the pharmacokinetics of ticagrelor, suggesting that the gut microbiota may not be the main cause of individual differences in the pharmacokinetics of ticagrelor. At the same time, fecal samples were employed from humans and rats to primarily explore the bioconversion effects of intestinal bacteria on ticagrelor, and no direct metabolism was found. However, the existence of bioaccumulation of ticagrelor by bacteria remains to be further investigated.
To further study the effect of gut microbes on the pharmacokinetic parameters of ticagrelor in vivo, a microbiota-depleted PGF model was constructed using antibiotics, which has been widely used to investigate the role of gut microbiota in specific conditions [19], and subsequently evaluated the pharmacokinetic profiles of ticagrelor under oral and intravenous administration. As the results showed, apparently increased MRT(0–24) and MRT(0-∞) of ticagrelor were observed in PGF rats under oral administration compared to intravenous administration, indicating that the effects of microbiota-depletion on ticagrelor were mainly in the intestine. This may be related to decreased expression of the intestinal efflux transporter P-glycoprotein (P-gp), which leads to reduced transport of ticagrelor from the blood to the intestine, thereby prolonging the retention time of ticagrelor in the body [20]. A Previous study reported that the expression of Cyp3a11 (CYP3A4 homologous enzyme) was reduced by 60% and 86% in the duodenum and ileum of mice after microbiota depletion [21], resulting in decreased metabolism of ticagrelor in the intestine and increase blood absorption.
The association between ticagrelor and gut microbiota has been reported before, which enrolled 65 patients with high platelet reactivity (HPR) and 90 controls with normal platelet reactivity (NPR). Pharmacokinetic evaluation showed that plasma concentrations of ticagrelor and its metabolite AR-C124910XX were lower in HPR than in controls, while HPR patients had higher microbial abundance and diversity. This result is similar to our findings that the bioavailability of ticagrelor was relatively low in control rats (higher microbial abundance and diversity) [16]. However, the effects of antibiotics on drug-processing genes are complex and may induce other unrecognized drug transporter proteins or drug-metabolizing enzymes [22], resulting in inapparent changes in plasma ticagrelor concentrations. Therefore, our findings favor that antibiotics have no distinct effect on the pharmacokinetics of ticagrelor.
There are some limitations in the current study. Firstly, insufficient sample size may be an important factor affecting the effectiveness of explaining individual differences. Secondly, the inclusion of healthy subjects may not fully reflect the patients who will be using ticagrelor. Thirdly, drug pharmacokinetic alterations are only clinically relevant if platelet reactivity is also altered, but the platelet reactivity of ticagrelor in the presence or absence of gut microbiota was not evaluated in our study. Fourthly, we acknowledge that the single‑dose pharmacokinetic results cannot fully replicate steady‑state exposure; our findings serve as a basis for further multiple‑dose PK/PD investigations rather than a direct prediction of chronic dosing effects. Thus, further investigations are needed to disclose the effects of the gut microbiota in the clinical treatment of ticagrelor in larger sample sizes and different populations using ticagrelor, with extended dosing regimens and inclusion of pharmacodynamic assessments.
5. Conclusion
Overall, our investigation based on the pharmacokinetic assessment of ticagrelor in healthy volunteers and microbiota-depleted PGF rats suggested that gut microflora may not be the primary cause of individual differences in the pharmacokinetics of ticagrelor. Ticagrelor can’t be directly metabolized by intestinal bacteria in vitro. However, as the present study did not evaluate other potential mechanisms of drug–drug interactions between ticagrelor and antibiotics (e.g., effects on drug‑metabolizing enzymes or transporters), our findings do not completely exclude the possibility of indirect interactions. Therefore, we suggest that no dosage adjustment is specifically required based on microbiota‑mediated pathways; nevertheless, prudent safety monitoring is still warranted when ticagrelor is co‑administered with antibiotics.
Supporting information
S1 Table. Clinical characteristics of in healthy subjects enrolled in the study.
https://doi.org/10.1371/journal.pone.0359660.s001
(DOCX)
S1 Fig. Cluster analysis of subjects based on pharmacokinetic parameters of ticagrelor.
Group H included subjects with higher AUC(0–48) and AUC(0-∞). Group H included subjects with lower AUC(0–48) and AUC(0-∞). Group H: n = 12. Group L: n = 10.
https://doi.org/10.1371/journal.pone.0359660.s002
(TIF)
S2 Fig. The plasma concentration-time curve of ticagrelor and AR-C124910XX in healthy subjects.
Data are represented as mean ± SD. Group H: n = 12. Group L: n = 10.
https://doi.org/10.1371/journal.pone.0359660.s003
(TIF)
S3 Fig. Fecal DNA concentration of the normal rats (control) and pseudo germ free rats (PGF).
Data are represented as mean ± SD. **P < 0.01 vs. control group (n = 8).
https://doi.org/10.1371/journal.pone.0359660.s004
(TIF)
Acknowledgments
We thank all the volunteers for their participation in this study.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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