The importance of pharmacokinetics/pharmacodynamics assessment in Phase IIB/III trials for MDR-TB treatment

Märtson, Anne-Grete; Hy, Kim; Marais, Ben J; Alffenaar, J-W C

doi:10.5588/ijtld.21.0072

Cited by 3 publications

(3 citation statements)

References 28 publications

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“… 66 Including such analysis in Phase III studies, where there are remaining knowledge gaps, can have important implications for dosing strategies to improve patient outcomes. 67 , 68 For example, finding the best tolerable dose of linezolid 69 , 70 is an important subject of debate as cessation of linezolid (because of toxicity) may result in a less efficacious regimen. Including a pharmacokinetic assessment in the study protocol 67 , 70 , 71 allows for a detailed secondary dose optimisation analysis.…”

Section: Standardmentioning

confidence: 99%

“… 67 , 68 For example, finding the best tolerable dose of linezolid 69 , 70 is an important subject of debate as cessation of linezolid (because of toxicity) may result in a less efficacious regimen. Including a pharmacokinetic assessment in the study protocol 67 , 70 , 71 allows for a detailed secondary dose optimisation analysis. Exploring drug–drug interactions in trials is also important for component drugs of the TB regimen, or for drugs given for host-directed therapy or other indications (e.g., antiretroviral drugs).…”

Section: Standardmentioning

confidence: 99%

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Standards for clinical trials for treating TB

du Cros,

Greig,

Alffenaar

et al. 2023

int j tuberc lung dis

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BACKGROUND: The value, speed of completion and robustness of the evidence generated by TB treatment trials could be improved by implementing standards for best practice.METHODS: A global panel of experts participated in a Delphi process, using a 7-point Likert scale to score and revise draft standards until consensus was reached.RESULTS: Eleven standards were defined: Standard 1, high quality data on TB regimens are essential to inform clinical and programmatic management; Standard 2, the research questions addressed by TB trials should be relevant to affected communities, who should be included in all trial stages; Standard 3, trials should make every effort to be as inclusive as possible; Standard 4, the most efficient trial designs should be considered to improve the evidence base as quickly and cost effectively as possible, without compromising quality; Standard 5, trial governance should be in line with accepted good clinical practice; Standard 6, trials should investigate and report strategies that promote optimal engagement in care; Standard 7, where possible, TB trials should include pharmacokinetic and pharmacodynamic components; Standard 8, outcomes should include frequency of disease recurrence and post-treatment sequelae; Standard 9, TB trials should aim to harmonise key outcomes and data structures across studies; Standard 10, TB trials should include biobanking; Standard 11, treatment trials should invest in capacity strengthening of local trial and TB programme staff.CONCLUSION: These standards should improve the efficiency and effectiveness of evidence generation, as well as the translation of research into policy and practice.

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Section: Standardmentioning

confidence: 99%

Section: Standardmentioning

confidence: 99%

Standards for clinical trials for treating TB

du Cros,

Greig,

Alffenaar

et al. 2023

int j tuberc lung dis

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“…In vivo studies able to reflect the pathophysiological conditions of the TB infections study the effect of different drug dosages-exposure on treatment outcome including relapse and drug resistance. Human PKPD is characterized in phase 2a early bactericidal activity (EBA) studies and should be part of Phase 2b-3 studies to further refine the understanding of the exposure-response relationship (Martson et al, 2021). In addition to clinical trials, studies under operational research conditions are relevant to capture drug dosing, exposure, and treatment response under programmatic care (Alffenaar et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Pharmacokinetics and pharmacodynamics of anti-tuberculosis drugs: An evaluation of in vitro, in vivo methodologies and human studies

et al. 2022

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There has been an increased interest in pharmacokinetics and pharmacodynamics (PKPD) of anti-tuberculosis drugs. A better understanding of the relationship between drug exposure, antimicrobial kill and acquired drug resistance is essential not only to optimize current treatment regimens but also to design appropriately dosed regimens with new anti-tuberculosis drugs. Although the interest in PKPD has resulted in an increased number of studies, the actual bench-to-bedside translation is somewhat limited. One of the reasons could be differences in methodologies and outcome assessments that makes it difficult to compare the studies. In this paper we summarize most relevant in vitro, in vivo, in silico and human PKPD studies performed to optimize the drug dose and regimens for treatment of tuberculosis. The in vitro assessment focuses on MIC determination, static time-kill kinetics, and dynamic hollow fibre infection models to investigate acquisition of resistance and killing of Mycobacterium tuberculosis populations in various metabolic states. The in vivo assessment focuses on the various animal models, routes of infection, PK at the site of infection, PD read-outs, biomarkers and differences in treatment outcome evaluation (relapse and death). For human PKPD we focus on early bactericidal activity studies and inclusion of PK and therapeutic drug monitoring in clinical trials. Modelling and simulation approaches that are used to evaluate and link the different data types will be discussed. We also describe the concept of different studies, study design, importance of uniform reporting including microbiological and clinical outcome assessments, and modelling approaches. We aim to encourage researchers to consider methods of assessing and reporting PKPD of anti-tuberculosis drugs when designing studies. This will improve appropriate comparison between studies and accelerate the progress in the field.

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