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Amaeze OU, Isoherranen N. Application of a physiologically based pharmacokinetic model to predict isoniazid disposition during pregnancy. Clin Transl Sci 2023; 16:2163-2176. [PMID: 37712488 PMCID: PMC10651660 DOI: 10.1111/cts.13614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/08/2023] [Accepted: 08/02/2023] [Indexed: 09/16/2023] Open
Abstract
Pregnancy can increase the risk of latent tuberculosis infection (LTBI) progression to tuberculosis (TB) disease. Isoniazid (INH) is the preferred preventative treatment for LTBI in pregnancy. INH is mainly cleared by N-acetyltransferase 2 (NAT2) but the pharmacokinetics (PK) of INH in different NAT2 phenotypes during pregnancy is not well characterized. To address this knowledge gap, we used physiologically based pharmacokinetic (PBPK) modeling to evaluate NAT2 phenotype-specific effects of pregnancy on INH disposition. A whole-body PBPK model for INH was developed and verified for non-pregnant NAT2 fast (FA), intermediate (IA), and slow (SA) acetylators. Model predictive performance was assessed using a drug-specific model acceptance criterion for mean plasma area under the curve (AUC) and peak plasma concentration (Cmax ), and the absolute average fold error (AAFE) for individual plasma concentrations. The verified model was extended to simulate INH disposition during pregnancy in NAT2 SA, IA, and FA populations. A sensitivity analysis was conducted using the verified PBPK model and known changes in INH disposition during pregnancy to determine whether NAT2 activity changes during pregnancy or other INH clearance pathways are altered. This analysis suggested that NAT2 activity is unchanged while other INH clearance pathways increase by ~80% during pregnancy. The model was applied to explore the effect of pregnancy on INH disposition in two ethnic populations with different NAT2 phenotype distributions and with high TB burden. Our PBPK model can be used to predict INH disposition during pregnancy in diverse populations and expanded to other drugs cleared by NAT2 during pregnancy.
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Affiliation(s)
- Ogochukwu U. Amaeze
- Department of PharmaceuticsUniversity of Washington, School of PharmacySeattleWashingtonUSA
| | - Nina Isoherranen
- Department of PharmaceuticsUniversity of Washington, School of PharmacySeattleWashingtonUSA
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Miao YD, Quan WX, Dong X, Gan J, Ji CF, Wang JT, Zhang F. Prognosis-related metabolic genes in the development of colorectal cancer progress and perspective. Gene 2023; 862:147263. [PMID: 36758843 DOI: 10.1016/j.gene.2023.147263] [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: 12/01/2022] [Revised: 01/30/2023] [Accepted: 02/06/2023] [Indexed: 02/10/2023]
Abstract
Colorectal cancer (CRC) is one of the most commonplace malignant tumors in the world. The occurrence and development of CRC are involved in numerous events. Metabolic reprogramming is one of the hallmarks of cancer and is convoluted and associated with carcinogenesis. Lots of metabolic genes are involved in the occurrence and progression of CRC. Study methods combining tumor genomics and metabolomics are more likely to explore this field in depth. In this mini-review, we make the latest progress and future prospects into the different molecular mechanisms of seven prognosis-related metabolic genes, we screened out in previous research, involved in the occurrence and development of CRC.
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Affiliation(s)
- Yan-Dong Miao
- The Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai 264100, China
| | - Wu-Xia Quan
- Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai 264100, China
| | - Xin Dong
- The Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai 264100, China
| | - Jian Gan
- Department of Gastroenterology, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai 264100, China
| | - Cui-Feng Ji
- Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai 264100, China
| | - Jiang-Tao Wang
- Department of Thyroid and Breast Surgery, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai 264100, China
| | - Fang Zhang
- The Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai 264100, China.
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Influence of N-acetyltransferase 2 (NAT2) genotype/single nucleotide polymorphisms on clearance of isoniazid in tuberculosis patients: a systematic review of population pharmacokinetic models. Eur J Clin Pharmacol 2022; 78:1535-1553. [PMID: 35852584 PMCID: PMC9482569 DOI: 10.1007/s00228-022-03362-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 06/29/2022] [Indexed: 11/19/2022]
Abstract
Purpose Significant pharmacokinetic variabilities have been reported for isoniazid across various populations. We aimed to summarize population pharmacokinetic studies of isoniazid in tuberculosis (TB) patients with a specific focus on the influence of N-acetyltransferase 2 (NAT2) genotype/single-nucleotide polymorphism (SNP) on clearance of isoniazid. Methods A systematic search was conducted in PubMed and Embase for articles published in the English language from inception till February 2022 to identify population pharmacokinetic (PopPK) studies of isoniazid. Studies were included if patient population had TB and received isoniazid therapy, non-linear mixed effects modelling, and parametric approach was used for building isoniazid PopPK model and NAT2 genotype/SNP was tested as a covariate for model development. Results A total of 12 articles were identified from PubMed, Embase, and hand searching of articles. Isoniazid disposition was described using a two-compartment model with first-order absorption and linear elimination in most of the studies. Significant covariates influencing the pharmacokinetics of isoniazid were NAT2 genotype, body weight, lean body weight, body mass index, fat-free mass, efavirenz, formulation, CD4 cell count, and gender. Majority of studies conducted in adult TB population have reported a twofold or threefold increase in isoniazid clearance for NAT2 rapid acetylators compared to slow acetylators. Conclusion The variability in disposition of isoniazid can be majorly attributed to NAT2 genotype. This results in a trimodal clearance pattern with a multi-fold increase in clearance of NAT2 rapid acetylators compared to slow acetylators. Further studies exploring the generalizability/adaptability of developed PopPK models in different clinical settings are required.
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Pharmacometrics in tuberculosis: progress and opportunities. Int J Antimicrob Agents 2022; 60:106620. [PMID: 35724859 DOI: 10.1016/j.ijantimicag.2022.106620] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 05/23/2022] [Accepted: 06/12/2022] [Indexed: 11/22/2022]
Abstract
Tuberculosis remains one of the leading causes of death by a communicable agent, infecting up to one-quarter of the world's population, predominantly in disadvantaged communities. Pharmacometrics employs quantitative mathematical models to describe the relationships between pharmacokinetics and pharmacodynamics, and to predict drug doses, exposures, and responses. Pharmacometric approaches have provided a scientific basis for improved dosing of antituberculosis drugs and concomitantly administered antiretrovirals at the population level. The development of modelling frameworks including physiologically-based pharmacokinetics, quantitative systems pharmacology and machine learning provides an opportunity to extend the role of pharmacometrics to in silico quantification of drug-drug interactions, prediction of doses for special populations, dose optimization and individualization, and understanding the complex exposure-response relationships of multidrug regimens in terms of both efficacy and safety, informing regimen design for future study. In this short clinically-focused review, we explore what has been done, and what opportunities exist for pharmacometrics to impact tuberculosis pharmacotherapy.
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Ladumor MK, Paudel A, Modhave D, Sharma S, Balhara A, Singh DK, Ramalingam M, Shah R, Pavankumarraju S, Kurmi M, Mariappan TT, Bhutani H, Prasad B. A Tribute to Professor Saranjit Singh - A Critical Thinker, Innovator, Mentor, and Educator. J Pharm Sci 2021; 111:1224-1231. [PMID: 34699842 DOI: 10.1016/j.xphs.2021.10.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 10/21/2021] [Accepted: 10/21/2021] [Indexed: 11/26/2022]
Abstract
This commentary presents contributions and accomplishments of Professor Saranjit Singh, National Institute of Pharmaceutical Education and Research (NIPER), SAS Nagar, India, to pharmaceutical research and education. Prof. Singh completed his successful tenure in October 2021. Over his 40+ years of illustrious academic career, he trained 147 Masters and 15 PhD students in the fields of drug stability testing, degradation chemistry, impurity and metabolite characterization, and advanced analytical technologies. He has published ∼250 research articles, reviews, editorials, patent, book, and book chapters, and received numerous awards, including the Professor M.L. Khorana Memorial Lecture Award from the Indian Pharmaceutical Association (IPA) and the Outstanding Analyst and Eminent Analyst awards from the Indian Drug Manufacturers' Association (IDMA). This commentary highlights Prof. Singh's inspiring personal and renowned professional journey, including early life, education, career, accomplishments, as well as his services to academia, industry, and regulatory. By sharing the contributions and accomplishments of Prof. Singh, we strongly believe that his story will inspire the next generation of scientists to continue his legacy to advance the field.
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Affiliation(s)
- Mayur K Ladumor
- Department of Pharmaceutics, University of Washington, Seattle, WA
| | - Amrit Paudel
- Institute of Process and Particle Engineering, Graz University of Technology, Inffeldgasse 13, 8010 Graz, Austria
| | | | - Sheena Sharma
- Department of Pharmaceutical Sciences, Washington State University, Spokane, WA
| | - Ankit Balhara
- Department of Pharmaceutics, University of Washington, Seattle, WA
| | - Dilip K Singh
- Sandoz Development Center, Hyderabad, Telangana, India
| | | | - Ravi Shah
- National Institute of Pharmaceutical Education and Research, Ahmedabad, Gujarat, India
| | | | - Moolchand Kurmi
- Biocon Bristol Myers Squibb R&D Centre (BBRC), Synegene International Limited, Bangalore 560099, India
| | - T Thanga Mariappan
- Biocon Bristol Myers Squibb R&D Centre (BBRC), Synegene International Limited, Bangalore 560099, India; Bristol Myers Squibb (BMS), Bangalore, India.
| | - Hemant Bhutani
- Novartis Healthcare Private Limited, Hyderabad, Telangana, India.
| | - Bhagwat Prasad
- Department of Pharmaceutical Sciences, Washington State University, Spokane, WA.
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