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Dilli Batcha JS, Gota V, Matcha S, Raju AP, Rao M, Udupa KS, Mallayasamy S. Predictive performance of population pharmacokinetic models of imatinib in chronic myeloid leukemia patients. Cancer Chemother Pharmacol 2024; 94:35-44. [PMID: 38441626 PMCID: PMC11258086 DOI: 10.1007/s00280-024-04644-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 01/25/2024] [Indexed: 07/19/2024]
Abstract
BACKGROUND AND AIM Chronic myeloid leukemia is a myeloproliferative neoplasm associated with the specific chromosomal translocation known as the Philadelphia chromosome. Imatinib is a potent BCR-ABL tyrosine kinase inhibitor, which is approved as the first line therapy for CML patients. There are various population pharmacokinetic studies available in the literature for this population. However, their use in other populations outside of their cohort for the model development has not been evaluated. This study was aimed to perform the predictive performance of the published population pharmacokinetic models for imatinib in CML population and propose a dosing nomogram. METHODS A systematic review was conducted through PubMed, and WoS databases to identify PopPK models. Clinical data collected in adult CML patients treated with imatinib was used for evaluation of these models. Various prediction-based metrics were used for assessing the bias and precision of PopPK models using individual predictions. RESULTS Eight imatinib PopPK model were selected for evaluating the model performance. A total of 145 plasma imatinib samples were collected from 43 adult patients diagnosed with CML and treated with imatinib. The PopPK model reported by Menon et al. had better performance than all other PopPK models. CONCLUSION Menon et al. model was able to predict well for our clinical data where it had the relative mean prediction error percentage ≤ 20%, relative median absolute prediction error ≤ 30% and relative root mean square error close to zero. Based on this final model, we proposed a dosing nomogram for various weight groups, which could potentially help to maintain the trough concentrations in the therapeutic range.
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Affiliation(s)
- Jaya Shree Dilli Batcha
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India
- Center for Pharmacometrics, Manipal Academy of Higher Education, Manipal, India
| | - Vikram Gota
- Department of Clinical Pharmacology, ACTREC, Tata Memorial Centre, Mumbai, India
| | - Saikumar Matcha
- Titus Family Department of Clinical Pharmacy, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, USA
| | - Arun Prasath Raju
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India
- Center for Pharmacometrics, Manipal Academy of Higher Education, Manipal, India
| | - Mahadev Rao
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India
| | - Karthik S Udupa
- Department of Medical Oncology, Manipal Academy of Higher Education, Kasturba Medical College, Manipal, India
| | - Surulivelrajan Mallayasamy
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.
- Center for Pharmacometrics, Manipal Academy of Higher Education, Manipal, India.
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Gagno S, Fratte CD, Posocco B, Buonadonna A, Fumagalli A, Guardascione M, Toffoli G, Cecchin E. Therapeutic drug monitoring and pharmacogenetics to tune imatinib exposure in gastrointestinal stromal tumor patients: hurdles and perspectives for clinical implementation. Pharmacogenomics 2023; 24:895-900. [PMID: 37955064 DOI: 10.2217/pgs-2023-0198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2023] Open
Abstract
Tweetable abstract Present evidence supports the use of intensified pharmacologic monitoring of #imatinib including #TherapeuticDrugMonitoring and #PGx to improve outcomes in patients with GI stromal tumor. Future studies need to address emerging questions to facilitate implementation in clinics.
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Affiliation(s)
- Sara Gagno
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS-Aviano, Aviano, 33081, Italy
| | - Chiara Dalle Fratte
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS-Aviano, Aviano, 33081, Italy
| | - Bianca Posocco
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS-Aviano, Aviano, 33081, Italy
| | - Angela Buonadonna
- Department of Medical Oncology, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS-Aviano, Aviano, 33081, Italy
| | - Arianna Fumagalli
- Department of Medical Oncology, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS-Aviano, Aviano, 33081, Italy
| | - Michela Guardascione
- Department of Medical Oncology, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS-Aviano, Aviano, 33081, Italy
| | - Giuseppe Toffoli
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS-Aviano, Aviano, 33081, Italy
| | - Erika Cecchin
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS-Aviano, Aviano, 33081, Italy
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He S, Shao Q, Zhao J, Bian J, Zhao Y, Hao X, Li Y, Hu L, Liu B, He H, Huang L, Jiang Q. Population pharmacokinetics and pharmacogenetics analyses of imatinib in Chinese patients with chronic myeloid leukemia in a real-world situation. Cancer Chemother Pharmacol 2023; 92:399-410. [PMID: 37624393 DOI: 10.1007/s00280-023-04581-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 08/09/2023] [Indexed: 08/26/2023]
Abstract
BACKGROUND Imatinib is presently the first-line choice for the treatment of chronic myeloid leukemia. However, there are limited real-world data on Chinese patients to support individualized medicine. This work aims to characterize population pharmacokinetics in Chinese patients with chronic myeloid leukemia, investigate the effects of several covariates on imatinib exposure, and provide support for personalized medicine and dose reduction. METHODS A total of 230 patients with chronic myeloid leukemia were enrolled, and 424 steady-state concentration measurements were taken to perform the population pharmacokinetic analysis and Monte Carlo simulations with Phoenix NLME software. The effects of the demographic, biological, and pharmacogenetic (ten SNP corresponding to CYP3A4, CYP3A5, ABCB1, ABCG2, SCL22A1 and POR) covariates on clearance were evaluated. RESULTS A one-compartmental model best-described imatinib pharmacokinetics. The hemoglobin and the estimated glomerular filtration rate (< 85 mL⋅min-1⋅1.73 m2) were associated with imatinib clearance. The genetic polymorphisms related to pharmacokinetics were not found to have a significant effect on the clearance of imatinib. The final model estimates of parameters are: ka (h-1) = 0.329; Vd/F (L) = 270; CL/F (L⋅h-1) = 7.60. CONCLUSIONS Key covariates in the study population accounting for variability in imatinib exposure are hemoglobin and the estimated glomerular filtration rate. There is some need for caution when treating patients with moderate-to-severe renal impairment and significant hemoglobin changes.
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Affiliation(s)
- Shiyu He
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Qianhang Shao
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
| | - Jinxia Zhao
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Jialu Bian
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Yinyu Zhao
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Xu Hao
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
| | - Yuanyuan Li
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
| | - Lei Hu
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
| | - Boyu Liu
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
| | - Huan He
- Department of Pharmacy, Beijing Children's Hospital of Capital Medical University, Beijing, China
| | - Lin Huang
- Department of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China.
| | - Qian Jiang
- Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, Peking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China.
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Shriyan B, Mehta P, Patil A, Jadhav S, Kumar S, Puri AS, Govalkar R, Krishnamurthy MN, Punatar S, Gokarn A, Khattry N, Gota V. Role of ADME gene polymorphisms on imatinib disposition: results from a population pharmacokinetic study in chronic myeloid leukaemia. Eur J Clin Pharmacol 2022; 78:1321-1330. [PMID: 35652931 DOI: 10.1007/s00228-022-03345-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 05/24/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE Imatinib is a substrate of CYP3A4, ABCB1 and ABCG2, and is known to have wide variability in pharmacokinetics (PK). At the same time, a clear relationship between drug levels and response also exists for imatinib in chronic myeloid leukaemia (CML). Therefore, pharmacogenetic-based dosing of imatinib is an attractive proposition. This study aims to characterize the population pharmacokinetics of imatinib in order to identify significant covariates including pharmacogenetic variants. METHODS Forty-nine patients with CML were enrolled in the study after being on imatinib for at least 4 consecutive weeks. Steady-state pharmacokinetic sampling was performed either in a sparse (4 samples each, n = 44) or intensive manner (9 samples each, n = 5). An additional pharmacogenetic sample was also collected from all patients. Plasma imatinib levels were estimated using a validated HPLC method. Pharmacogenetic variants were identified using the PharmacoScan array platform. Population pharmacokinetic analysis was carried out using NONMEM v7.2. Seven SNPs within CYP3A4, ABCB1 and ABCG2 genes were evaluated for covariate effect on the clearance of imatinib. RESULTS Imatinib PK was well characterized using a one-compartment model with zero-order absorption. The clearance and volume of distribution were found to be 10.2 L/h and 389 L respectively. Only SNP rs1128503 of the ABCB1 gene had a small but insignificant effect on imatinib clearance, with a 25% reduction in clearance observed in patients carrying the polymorphism. Twenty-three out of forty-nine patients (47%) carried the polymorphic allele, of whom 17 were heterozygous and six were homozygous. CONCLUSION Our study conclusively proves that genetic polymorphisms in the CYP3A4 and ABC family of transporters do not have any role in the personalized dosing of imatinib in CML.
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Affiliation(s)
- Bharati Shriyan
- Department of Clinical Pharmacology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, 410210, India
| | - Parsshava Mehta
- Department of Clinical Pharmacology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, 410210, India
| | - Anand Patil
- Department of Clinical Pharmacology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, 410210, India
| | - Shraddha Jadhav
- Department of Clinical Pharmacology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, 410210, India
| | - Sharath Kumar
- Department of Clinical Pharmacology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, 410210, India
| | - Apeksha S Puri
- Department of Clinical Pharmacology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, 410210, India
| | - Ravina Govalkar
- Department of Clinical Pharmacology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, 410210, India.,Gahlot Institute of Pharmacy, Koparkhairane, Navi Mumbai, 400709, India
| | - Manjunath Nookala Krishnamurthy
- Department of Clinical Pharmacology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, 410210, India.,Homi Bhabha National Institute, Mumbai, 400094, India
| | - Sachin Punatar
- Department of Medical Oncology, Tata Memorial Hospital, Mumbai, 400012, India.,Homi Bhabha National Institute, Mumbai, 400094, India
| | - Anant Gokarn
- Department of Medical Oncology, Tata Memorial Hospital, Mumbai, 400012, India.,Homi Bhabha National Institute, Mumbai, 400094, India
| | - Navin Khattry
- Department of Medical Oncology, Tata Memorial Hospital, Mumbai, 400012, India.,Homi Bhabha National Institute, Mumbai, 400094, India
| | - Vikram Gota
- Department of Clinical Pharmacology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, 410210, India. .,Homi Bhabha National Institute, Mumbai, 400094, India.
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Corral Alaejos Á, Zarzuelo Castañeda A, Jiménez Cabrera S, Sánchez-Guijo F, Otero MJ, Pérez-Blanco JS. External evaluation of population pharmacokinetic models of imatinib in adults diagnosed with chronic myeloid leukaemia. Br J Clin Pharmacol 2021; 88:1913-1924. [PMID: 34705297 DOI: 10.1111/bcp.15122] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 09/29/2021] [Accepted: 10/21/2021] [Indexed: 12/30/2022] Open
Abstract
AIMS Imatinib is considered the standard first-line treatment in newly diagnosed patients with chronic-phase myeloid leukaemia (CML). Several imatinib population pharmacokinetic (popPK) models have been developed. However, their predictive performance has not been well established when extrapolated to different populations. Therefore, this study aimed to perform an external evaluation of available imatinib popPK models developed mainly in adult patients, and to evaluate the improvement in individual model-based predictions through Bayesian forecasting computed by each model at different treatment occasions. METHODS A literature review was conducted through PubMed and Scopus to identify popPK models. Therapeutic drug monitoring data collected in adult CML patients treated with imatinib was used for external evaluation, including prediction- and simulated-based diagnostics together with Bayesian forecasting analysis. RESULTS Fourteen imatinib popPK studies were included for model-performance evaluation. A total of 99 imatinib samples were collected from 48 adult CML patients undergoing imatinib treatment with a minimum of one plasma concentration measured at steady-state between January 2016 and December 2020. The model proposed by Petain et al showed the best performance concerning prediction-based diagnostics in the studied population. Bayesian forecasting demonstrated a significant improvement in predictive performance at the second visit. Inter-occasion variability contributed to reducing bias and improving individual model-based predictions. CONCLUSIONS Imatinib popPK studies developed in Caucasian subjects including α1-acid glycoprotein showed the best model performance in terms of overall bias and precision. Moreover, two imatinib samples from different visits appear sufficient to reach an adequate model-based individual prediction performance trough Bayesian forecasting.
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Affiliation(s)
| | | | | | - Fermín Sánchez-Guijo
- Institute for Biomedical Research of Salamanca, Salamanca, Spain.,Haematology Department, University Hospital of Salamanca, Salamanca, Spain.,Department of Medicine, University of Salamanca, Salamanca, Spain
| | - María José Otero
- Pharmacy Service, University Hospital of Salamanca, Salamanca, Spain.,Institute for Biomedical Research of Salamanca, Salamanca, Spain
| | - Jonás Samuel Pérez-Blanco
- Department of Pharmaceutical Sciences, Pharmacy Faculty, University of Salamanca, Salamanca, Spain.,Institute for Biomedical Research of Salamanca, Salamanca, Spain
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Adiwidjaja J, Gross AS, Boddy AV, McLachlan AJ. Physiologically-based pharmacokinetic model predictions of inter-ethnic differences in imatinib pharmacokinetics and dosing regimens. Br J Clin Pharmacol 2021; 88:1735-1750. [PMID: 34535920 DOI: 10.1111/bcp.15084] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 07/28/2021] [Accepted: 09/04/2021] [Indexed: 01/06/2023] Open
Abstract
AIMS This study implements a physiologically-based pharmacokinetic (PBPK) modelling approach to investigate inter-ethnic differences in imatinib pharmacokinetics and dosing regimens. METHODS A PBPK model of imatinib was built in the Simcyp Simulator (version 17) integrating in vitro drug metabolism and clinical pharmacokinetic data. The model accounts for ethnic differences in body size and abundance of drug-metabolising enzymes and proteins involved in imatinib disposition. Utility of this model for prediction of imatinib pharmacokinetics was evaluated across different dosing regimens and ethnic groups. The impact of ethnicity on imatinib dosing was then assessed based on the established range of trough concentrations (Css,min ). RESULTS The PBPK model of imatinib demonstrated excellent predictive performance in describing pharmacokinetics and the attained Css,min in patients from different ethnic groups, shown by prediction differences that were within 1.25-fold of the clinically-reported values in published studies. PBPK simulation suggested a similar dose of imatinib (400-600 mg/d) to achieve the desirable range of Css,min (1000-3200 ng/mL) in populations of European, Japanese and Chinese ancestry. The simulation indicated that patients of African ancestry may benefit from a higher initial dose (600-800 mg/d) to achieve imatinib target concentrations, due to a higher apparent clearance (CL/F) of imatinib compared to other ethnic groups; however, the clinical data to support this are currently limited. CONCLUSION PBPK simulations highlighted a potential ethnic difference in the recommended initial dose of imatinib between populations of European and African ancestry, but not populations of Chinese and Japanese ancestry.
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Affiliation(s)
- Jeffry Adiwidjaja
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,Faculty of Pharmacy, Gadjah Mada University, Yogyakarta, Special Region of Yogyakarta, Indonesia
| | - Annette S Gross
- Clinical Pharmacology Modelling & Simulation, GlaxoSmithKline R&D, Sydney, NSW, Australia
| | - Alan V Boddy
- UniSA Cancer Research Institute and UniSA Clinical & Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Andrew J McLachlan
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
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Mohammadi F, Rostami G, Assad D, Shafiei M, Hamid M, Jalaeikhoo H. Association of SLC22A1,SLCO1B3 Drug Transporter Polymorphisms and Smoking with Disease Risk and Cytogenetic Response to Imatinib in Patients with Chronic Myeloid Leukemia. Lab Med 2021; 52:584-596. [PMID: 34128532 DOI: 10.1093/labmed/lmab023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE To determine whether polymorphisms of SLC22A1 and SLCO1B3 genes could predict imatinib (IM) response and chronic myeloid leukemia (CML) risk. METHODS We genotyped SLC22A1 (c.480G > C, c.1222A > G) and SLCO1B3 (c.334T > G, c.699G > A) polymorphisms in 132 patients with CML and 109 sex- and age-matched healthy subjects. The patients were evaluated for cytogenetic response by standard chromosome banding analysis (CBA). RESULTS Polymorphism analysis showed significant increased risk of IM resistance for SLC22A1c.1222AG (P = .03; OR = 2.2), SLCO1B3c.334TT/TG genotypes (P = .007; OR = 4.37) and 334T allele (P = .03; OR = 2.86). The double combinations of SLC22A1c.480CC and c.1222AG polymorphisms with SLCO1B3c.334TT/TG were significantly associated with complete cytogenetic response (CCyR) (P <.05; OR> 7). The interaction between all polymorphisms and smoking were associated with CML development and IM resistance (P ≤.04; OR> 3). CONCLUSIONS Our study results suggest the influence of SLC22A1 and SLCO1B3 polymorphisms and the interaction of smoking on CML development and IM response.
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Affiliation(s)
- Fatemeh Mohammadi
- Department of Biology, School of Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Golale Rostami
- Department of Molecular Medicine, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Dlnya Assad
- Department of Biology, College of Science, Sulaimani University, Sulaymanyah, Iraq
| | - Mohammad Shafiei
- Department of Biology, School of Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran.,Biotechnology and Biological Science Research Center, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Mohammad Hamid
- Department of Molecular Medicine, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Hasan Jalaeikhoo
- AJA Cancer Epidemiology Research and Treatment Center (AJA-CERTC), AJA University of Medical Sciences, Tehran, Iran
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