Target regimen profiles for treatment of tuberculosis: a WHO document

Lienhardt, Christian; Nahid, Payam; Rich, Michael; Bansbach, Cathy; Kendall, Emily A.; Churchyard, Gavin J.; González-Angulo, Licé; D’Ambrosio, Lia; Migliori, Giovanni Battista; Raviglione, Mario

doi:10.1183/13993003.02352-2016

Cited by 29 publications

(18 citation statements)

References 32 publications

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“…Địa chỉ email: bui.nhat1@gmail.com https://doi.org/10.25073/2588-1132/vnumps.4168 dụng diệt khuẩn và kìm khuẩn đồng thời trong một thời gian hợp lí để đảm bảo khỏi bệnh và tránh tình trạng kháng thuốc. Tuy vậy, các phác đồ điều trị hiện hành có thể có hiệu quả còn chưa cao như mong đợi, trong khi độc tính cao, kéo dài và tổn hao chi phí [1] -một nguyên nhân là sự khác biệt cá thể giữa các bệnh nhân về các quá trình hấp thu, phân bố, chuyển hóa, thải trừ, nhân dẫn tới khác biệt về các thông số dược động học và hiệu quả điều trị tương ứng [2,3]. Phác đồ điều trị lao thường quy đã không hề thay đổi suốt hơn 40 năm qua; dựa chủ yếu vào kinh nghiệm lâm sàng chứ không được dựa trên các thông số dược động học -dược lực học được tối ưu hóa.…”

Section: đặT Vấn đề unclassified

Population Pharmacokinetics of Rifampicin on Pulmonary Tuberculosis Patients

Nhat¹,

Hòa²,

Tuấn³

et al. 2019

MPS

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This study aimed to establish a reasonable population pharmacokinetic model for rifampicin taken orally by patients with pulmonary tuberculosis, estimate pharmacokinetic parameters as well as influencing covariates. Blood samples of patients were collected at day 10 – 14 after commencing treatment. Time – concentration data were handled using non-linear mixed-effect model with Monolix 2018. An one-compartment, linear elimination, absorption with transit compartments model was found to be the most suitable for rifampicin. Volume of distribution (33,5 L) and clearance (9,62 L) were found to be influenced by fat-free mass (calculated using Janmahasatian’s method). Absorption-related parameters (Ktr, mean transit time and Ka) were found to have high inter-individual variability. Keywords Rifampicin, population pharmacokinetics, pulmonary tuberculosis. References [1] Christian Lienhardt et al, Target regimen profiles for treatment of tuberculosis: a WHO document (2017).[2] J.G. Pasipanodya et al, Serum drug concentrations predictive of pulmonary tuberculosis outcomes, The Journal of infectious diseases 208(9) (2013) 1464-1473. https://doi.org/10.1093/infdis/jit352[3] Jonathan Reynolds, Scott K Heysell (2014), Understanding pharmacokinetics to improve tuberculosis treatment outcome, Expert opinion on drug metabolism & toxicology 10(6) (2014) 813-823. https://doi.org/10.1517/17425255.2014.895813[4] E.F. Egelund, A.B. Barth, C.A. Peloquin (2011), Population pharmacokinetics and its role in anti-tuberculosis drug development and optimization of treatment, Current pharmaceutical design 17(27) (2017) 2889-2899. https://doi.org/10.2174/138161211797470246.[5] J.F. Murray, D.E. Schraufnagel, P.C. Hopewell, Treatment of tuberculosis. A historical perspective, Annals of the American Thoracic Society 12(12) (2015) 1749-1759. https://doi.org/10.1513/AnnalsATS.201509-632PS[6] K.E. Stott, et al, Pharmacokinetics of rifampicin in adult TB patients and healthy volunteers: a systematic review and meta-analysis, Journal of Antimicrobial Chemotherapy 73(9) (2018) 2305-2313. https://doi.org/10.1093/jac/dky152.[7] Le Thi Luyen, Ta Manh Hung et al, Simultaneous Determination of Pyrazinamide, Rifampicin, Ethambutol, Isoniazid and Acetyl Isoniazid in Human Plasma by LC-MS/MS Method, Journal of Applied Pharmaceutical Science 8(09) (2018) 061-073. https://doi.org/ 10.7324/JAPS.2018.8910.[8] M.T. Chirehwa et al, Model-based evaluation of higher doses of rifampin using a semimechanistic model incorporating autoinduction and saturation of hepatic extraction, Antimicrobial agents and chemotherapy 60(1) (2016) 487-494. https://doi.org/10.1128/AAC.01830-15.[9] Paolo Denti et al, A population pharmacokinetic model for rifampicin auto-induction, The 3rd international workshop on clinical pharmacology of TB drugs (2010).[10] Y. Jing et al, Population pharmacokinetics of rifampicin in Chinese patients with pulmonary tuberculosis, The Journal of Clinical Pharmacology 56(5) (2016) 622-627. https://doi.org/10.1002/jcph.643.[11] S.R.C. Milán et al, Population pharmacokinetics of rifampicin in Mexican patients with tuberculosis, Journal of clinical pharmacy and therapeutics 38(1) (2013) 56-61. https://doi.org/10.1111/jcpt.12016.[12] Anushka Naidoo et al, Effects of genetic variability on rifampicin and isoniazid pharmacokinetics in South African patients with recurrent tuberculosis, Pharmacogenomics(00) (2013). https://doi.org/10.2217/pgs-2018-0166.[13] Neesha Rockwood et al, HIV-1 coinfection does not reduce exposure to rifampin, isoniazid, and pyrazinamide in South African tuberculosis outpatients, Antimicrobial agents and chemotherapy 60(10) (2016) 6050-6059. https://doi.org/10.1128/AAC.00480-16.[14] Alessandro Schipani et al, A simultaneous population pharmacokinetic analysis of rifampicin in Malawian adults and children, British Journal of Clinical Pharmacology 81(4) (2016) 679-687. https://doi.org/10.1111/bcp.12848.[15] Kok-Yong Seng et al, Population pharmacokinetics of rifampicin and 25-deacetyl-rifampicin in healthy Asian adults, Journal of Antimicrobial Chemotherapy 70(12) (2015) 3298-3306. https://doi.org/10.1093/jac/dkv268.[16] J.J. Wilkins et al, Population pharmacokinetics of rifampin in pulmonary tuberculosis patients, including a semimechanistic model to describe variable absorption, Antimicrobial agents and chemotherapy 52(6) (2008)2138-2148. https://dx.doi.org/10.1128%2FAAC.00461-07.[17] Sylvain Goutelle et al, Population modeling and Monte Carlo simulation study of the pharmacokinetics and antituberculosis pharmacodynamics of rifampin in lungs, Antimicrobial agents and chemotherapy 53(7) (2009) 2974-2981. https://doi.org/10.1128/AAC.01520-08.[18] R.M. Savic et al, Implementation of a transit compartment model for describing drug absorption in pharmacokinetic studies, Journal of pharmacokinetics and pharmacodynamics 34(5) (2007) 711-726. https://doi.org/10.1007/s10928-007-9066-0.[19] B.J. Anderson, N.H.G. Holford, Mechanism-based concepts of size and maturity in pharmacokinetics, Annu. Rev. Pharmacol. Toxicol 48 (2008) 303-332. https://doi.org/10.1146/annurev.pharmtox.48.113006.094708.[20] Kok-Yong Seng et al, Population pharmacokinetic analysis of isoniazid, acetyl-isoniazid and isonicotinic acid in healthy volunteers, Antimicrobial agents and chemotherapy, pp. AAC. (2015) 01244-15. https://doi.org/10.1128/AAC.01244-15.[21] Sarayut Janmahasatian et al, Quantification of lean bodyweight, Clinical pharmacokinetics 44(10), (2005) 1051-1065. https://doi.org/10.2165/00003088-200544100-00004.[22] Kidola Jeremiah et al, Nutritional supplementation increases rifampin exposure among tuberculosis patients coinfected with HIV, Antimicrobial agents and chemotherapy 58(6) (2014) 3468-3474. https://doi.org/10.1128/AAC.02307-13

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Section: đặT Vấn đề unclassified

Population Pharmacokinetics of Rifampicin on Pulmonary Tuberculosis Patients

Nhat¹,

Hòa²,

Tuấn³

et al. 2019

MPS

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“…It is important, therefore, to recognise that a strategic approach to development pathways for different drugs may need to reflect these differences while identifying and preserving the core elements of a successful critical path to registration. At the same time, it is generally accepted that drug developers in TB need to focus more on codevelopment of regimens rather than drawing only on the lessons learned from development of individual drugs, which poses additional challenges in evaluation of both safety and efficacy [1]. Policymakers are increasingly seeking to integrate innovative clinical trial approaches into their decision-making to facilitate early and effective deployment of the best regimens [2], as emphasised by this collection.…”

Section: Introductionmentioning

confidence: 99%

Accelerating the transition of new tuberculosis drug combinations from Phase II to Phase III trials: New technologies and innovative designs

et al. 2019

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“…The emergency of Mycobacterium tuberculosis resistant to the first line drug [6] [7] [8] limited access to second line drugs for appropriate treatment and called for urgent action [9] [10]. Drug resistant TB patients require prolonged treatment using second line medication that are less effective and more toxic [5] [11] [12] [13] [14] [15]. The acquisition of Mycobacterium tuberculosis resistance may be occurring from using of inferior regimens, poor adherence to anti-TB drug, chronic malnutrition and co-infection to HIV/TB.…”

Section: Introductionmentioning

confidence: 99%

Multidrug-Resistant Tuberculosis Disease in North-Kivu Province, Democratic Republic of Congo

Robert¹,

Many²

2019

JTR

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Introduction: The emergency of Mycobacterium tuberculosis resistant to the first line drug reduced access possibility to second line drugs for appropriate treatment and required for urgent action especially in le Democratic Republic of Congo (DRC), which counts among the highest tuberculosis (TB) burden countries in Africa. Objective: To present prevalence and describe multidrugresistant tuberculosis cases in North-Kivu Province identified by using Genexpert technology. Methods: We conducted an observational prospective study on multidrug-resistant tuberculosis (MDR-TB) cases in North-Kivu Province, DRC from 2017 to 2018. All cases of MDR-TB identified by Genexpert MTB/ RIB were included in this series. Result: Of 15,544 tuberculosis cases registered during the study period, 19 cases of MDR-TB were identified. 57.9% was male, 89.5% was retreatment cases and 5.3% was coinfection HIV/TB cases. Conclusion: This new molecular technology diagnostic facilitates multidrug-resistance tuberculosis detection and improves the reporting of data lack.

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Target regimen profiles for treatment of tuberculosis: a WHO document

Cited by 29 publications

References 32 publications

Population Pharmacokinetics of Rifampicin on Pulmonary Tuberculosis Patients

Population Pharmacokinetics of Rifampicin on Pulmonary Tuberculosis Patients

Accelerating the transition of new tuberculosis drug combinations from Phase II to Phase III trials: New technologies and innovative designs

Multidrug-Resistant Tuberculosis Disease in North-Kivu Province, Democratic Republic of Congo

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