Rifapentine Population Pharmacokinetics and Dosing Recommendations for Latent Tuberculosis Infection.

RATIONALE: Rifapentine has been investigated at various doses, frequencies, and dosing algorithms but clarity on the optimal dosing approach is lacking. OBJECTIVES: In this individual participant data meta-analysis of rifapentine pharmacokinetics, we characterize rifapentine population pharmacokinetics, including autoinduction, and determine optimal dosing strategies for short-course rifapentine-based regimens for latent tuberculosis infection. METHODS: Rifapentine pharmacokinetic studies were identified though a systematic review of literature. Individual plasma concentrations were pooled, and non-linear mixed effects modeling was performed. A subset of data was reserved for external validation. Simulations were performed under various dosing conditions including current weight-based methods and alternative methods driven by identified covariates. MEASUREMENTS AND MAIN RESULTS: We identified 9 clinical studies with a total of 863 participants with pharmacokinetic data (n=4301 plasma samples). Rifapentine population pharmacokinetics were described successfully with a one-compartment distribution model. Autoinduction of clearance was driven by rifapentine plasma concentration. The maximum effect was a 72% increase in clearance and was reached after 21 days. Drug bioavailability decreased by 27% with HIV infection, decreased by 28% with fasting, and increased by 49% with a high-fat meal. Body weight was not a clinically relevant predictor of clearance. Pharmacokinetic simulations showed that current weight-based dosing leads to lower exposures in low weight individuals, which can be overcome with flat dosing. In HIV-positive patients, 30% higher doses are required to match drug exposure in HIV-negative patients. CONCLUSIONS: Weight-based dosing of rifapentine should be removed from clinical guidelines and higher doses for HIV-positive patients should be considered to provide equivalent efficacy

Coronavirus disease 2019 (COVID-19) pharmacologic treatments for children : research priorities and approach to pediatric studies

CITATION: Garcia-Prats, A. J. et al. 2021. Coronavirus Disease 2019 (COVID-19) Pharmacologic Treatments for Children: Research Priorities and Approach to Pediatric Studies. Clinical infectious diseases, 72(6):1067–1073. doi:10.1093/cid/ciaa885The original publication is available at https://academic.oup.com/cid/Clinical trials of pharmacologic treatments of coronavirus disease 2019 (COVID-19) are being rapidly designed and implemented in adults. Children are often not considered during development of novel treatments for infectious diseases until very late. Although children appear to have a lower risk compared with adults of severe COVID-19 disease, a substantial number of children globally will benefit from pharmacologic treatments. It will be reasonable to extrapolate efficacy of most treatments from adult trials to children. Pediatric trials should focus on characterizing a treatment’s pharmacokinetics, optimal dose, and safety across the age spectrum. These trials should use an adaptive design to efficiently add or remove arms in what will be a rapidly evolving treatment landscape, and should involve a large number of sites across the globe in a collaborative effort to facilitate efficient implementation. All stakeholders must commit to equitable access to any effective, safe treatment for children everywhere.https://academic.oup.com/cid/article/72/6/1067/5864500?login=truePublishers versio

Optimization of anti-tuberculosis treatment in children

Childhood tuberculosis (TB) affects one million children annually, and in 2019, 194,000 children under 15 years of age died from TB. Malnourished, HIV-positive, and young children have an increased risk of TB disease progression, severe forms of TB, and poor treatment outcomes. Historically, children with TB have been treated as small adults. This may contribute to poorer outcomes due to pharmacokinetic differences between adults and children that result in suboptimal drug exposure. The aims of this work were to apply modeling and simulation to optimize pediatric dosing of important drugs/regimens for drug-susceptible TB, drug-resistant TB, and latent TB infection. Current treatment guidelines for drug-susceptible TB endorsed by the World Health Organization (WHO) recommend dosing children by body weight alone, which may lead to systematic underdosing and worse treatment outcomes in underweight children. A systematic review and meta-analysis was performed to assess rifampicin pharmacokinetics in children. At the current WHO recommendations, rifampicin exposures were much lower in children compared to adults. Younger and HIV-positive children trended toward lower exposures compared to older and HIV-negative children, respectively, but data reporting by these groups were too sparse to draw definitive conclusions. In a separate study, an integrated pharmacologic-epidemiologic model was developed to predict childhood TB outcomes in a real-world population of children under 5 years of age from high burden TB countries. An alternative dosing method, which dosed children by ideal body weight instead of actual body weight, was predicted to reduce unfavorable child outcomes by at least 33%, with major improvements in the youngest children and those who were malnourished. The findings from both analyses support higher doses of rifampicin than currently recommended. Moxifloxacin is a high-priority drug for drug-resistant TB treatment per WHO guidelines. However, doses are not optimized for children due to a lack of pharmacokinetic and safety data, especially in young children. To address this need, the population pharmacokinetics and relationship with QT-interval prolongation were characterized in a cohort of 85 children with TB (median age 4.6 years). Optimal moxifloxacin doses were found to be 10-50% higher than current WHO recommendations, depending on child weight. The risk of QT-interval prolongation was low during the study, but requires further assessment at higher doses, especially with coadministration of other QT-prolonging anti-TB agents such as clofazimine and bedaquiline. Tuberculosis disease can be prevented in those with latent infection with anti-tuberculosis therapy. Novel short-course rifapentine-based therapies are an appealing, non-inferior alternative to the standard 9-months of isoniazid. However, rifapentine pharmacokinetic data in children are lacking. To inform on optimal rifapentine dosing in children, the pharmacokinetics and autoinduction profile were first characterized in adults. The adult model informed the model structure for pediatric simulations as well as pharmacokinetic targets for different regimens. Then, optimized and pragmatic weight band dosing was proposed for the 3-month once weekly regimen (3HP) for labelled use and for the experimental regimens being evaluated in pediatric clinical trials. Lastly, prior knowledge of rifapentine (and rifamycins, in general) pharmacokinetics were leveraged to inform the design of a pediatric PK study evaluating daily rifapentine for TB prevention. Collectively, this dissertation research contributes to the prevention and treatment of TB in children by applying model-based approaches to optimize the dosing of key drugs in current and novel regimens. There is a focus on vulnerable child populations that are typically underrepresented in clinical trials and underserved by standard weight-based dosing practices but represent a large burden of the mortality (e.g., malnourished, HIV-coinfected, young)

Optimization of anti-tuberculosis treatment in children

Childhood tuberculosis (TB) affects one million children annually, and in 2019, 194,000 children under 15 years of age died from TB. Malnourished, HIV-positive, and young children have an increased risk of TB disease progression, severe forms of TB, and poor treatment outcomes. Historically, children with TB have been treated as small adults. This may contribute to poorer outcomes due to pharmacokinetic differences between adults and children that result in suboptimal drug exposure. The aims of this work were to apply modeling and simulation to optimize pediatric dosing of important drugs/regimens for drug-susceptible TB, drug-resistant TB, and latent TB infection. Current treatment guidelines for drug-susceptible TB endorsed by the World Health Organization (WHO) recommend dosing children by body weight alone, which may lead to systematic underdosing and worse treatment outcomes in underweight children. A systematic review and meta-analysis was performed to assess rifampicin pharmacokinetics in children. At the current WHO recommendations, rifampicin exposures were much lower in children compared to adults. Younger and HIV-positive children trended toward lower exposures compared to older and HIV-negative children, respectively, but data reporting by these groups were too sparse to draw definitive conclusions. In a separate study, an integrated pharmacologic-epidemiologic model was developed to predict childhood TB outcomes in a real-world population of children under 5 years of age from high burden TB countries. An alternative dosing method, which dosed children by ideal body weight instead of actual body weight, was predicted to reduce unfavorable child outcomes by at least 33%, with major improvements in the youngest children and those who were malnourished. The findings from both analyses support higher doses of rifampicin than currently recommended. Moxifloxacin is a high-priority drug for drug-resistant TB treatment per WHO guidelines. However, doses are not optimized for children due to a lack of pharmacokinetic and safety data, especially in young children. To address this need, the population pharmacokinetics and relationship with QT-interval prolongation were characterized in a cohort of 85 children with TB (median age 4.6 years). Optimal moxifloxacin doses were found to be 10-50% higher than current WHO recommendations, depending on child weight. The risk of QT-interval prolongation was low during the study, but requires further assessment at higher doses, especially with coadministration of other QT-prolonging anti-TB agents such as clofazimine and bedaquiline. Tuberculosis disease can be prevented in those with latent infection with anti-tuberculosis therapy. Novel short-course rifapentine-based therapies are an appealing, non-inferior alternative to the standard 9-months of isoniazid. However, rifapentine pharmacokinetic data in children are lacking. To inform on optimal rifapentine dosing in children, the pharmacokinetics and autoinduction profile were first characterized in adults. The adult model informed the model structure for pediatric simulations as well as pharmacokinetic targets for different regimens. Then, optimized and pragmatic weight band dosing was proposed for the 3-month once weekly regimen (3HP) for labelled use and for the experimental regimens being evaluated in pediatric clinical trials. Lastly, prior knowledge of rifapentine (and rifamycins, in general) pharmacokinetics were leveraged to inform the design of a pediatric PK study evaluating daily rifapentine for TB prevention. Collectively, this dissertation research contributes to the prevention and treatment of TB in children by applying model-based approaches to optimize the dosing of key drugs in current and novel regimens. There is a focus on vulnerable child populations that are typically underrepresented in clinical trials and underserved by standard weight-based dosing practices but represent a large burden of the mortality (e.g., malnourished, HIV-coinfected, young)

Advancing evidence-based treatment of infectious diseases in children with real-world data: Opportunities and challenges

There is an increased interest in utilizing real-world data (RWD) for pharmaceutical research and regulatory decision-making. The development and use of pediatric medicines could benefit greatly from real-world data studies given nearly half of drugs prescribed to children are "off-label", meaning there is a lack of pediatric-specific evidence from controlled trials, while there is an abundance of data from routine clinical practice. Currently, the use of real-world data, such as data from electronic health records, is lacking in pediatric research, especially within infectious diseases. Here, we discuss opportunities and challenges for real-world data to generate evidence on the optimal treatment and management of infectious diseases in children