Pharmacokinetic analysis across studies to drive knowledge-integration: optimal dose finding of rifampicin for the treatment of drug-susceptible tuberculosis in children
Belén P. Solans (1), Rob C van Wijk (1), Ryo Miyakawa (1), Rada Savic (1)
(1) University of California San Francisco, UCSF
Introduction: Answering challenging questions in drug development sometimes requires pharmacokinetic (PK) data analysis across different studies. Given the growing interest in data sharing and advanced computational methods, knowledge integration from multiple data sources is increasingly applied in model informed drug discovery and development. A potent analysis method is the individual patient data meta-analysis (IPDMA), leveraging systematic review of databases and literature, with the most detailed data type of the individual patient, and quantitative modelling of the PK processes while accounting for heterogeneity of variance between studies. An especially relevant field to apply IPDMA to is the paediatric population and PK therein, which is challenged by smaller sample sizes. Specifically, optimal doses in children and young adolescents of first-line drugs for treatment of drug-susceptible tuberculosis (DS-TB) such as rifampicin, remain uncertain.
Objectives: We performed a systematic review and meta-analysis (MA), both with aggregate and individual patient data, with the objective to 1) evaluate current evidence on clinical outcomes and exposure to rifampicin among children, 2) synthesize knowledge on PK and other risk factors for unfavourable clinical outcomes, and 3) assess underexposure of children receiving rifampicin for the treatment of DS-TB.
Methods: Two systematic reviews and MA were performed in children treated with rifampicin for DS-TB, one on aggregate data on exposure to rifampicin and outcome data, and the other one looking for studies including individual children’s data. We systematically searched PubMed, Embase, and Cochrane Library databases for observational, descriptive studies and randomized controlled trials from 2010 to August 2021. For the aggregate data meta-analysis, summary estimates for AUC were obtained by meta-analysis with the ‘metafor’ package (v.2.4.0) in R. A restricted maximum likelihood mixed-effects model was used to perform a meta-analysis of drug exposure estimates. DerSimonian–Laird estimator was applied for residual heterogeneity, which was assessed by the I2 statistic and visual inspection of forest plots. Meta-regression was performed with key covariates to assess their impact on inter-study heterogeneity. For the IPDMA, a mixed-effects model in NONMEM v7.5 was developed, using the $LEVEL functionality to model hierarchical levels of variability [1] and therefore including inter-study variability. Clinical simulations based on WHO dosing [2] and alternative dosing strategies were performed to assess the drug exposure in children with DS-TB.
Results: An aggregate-data analysis from 12 studies and 1,862 children revealed that, at WHO doses [2], the proportion of favourable outcomes in children with DS-TB is suboptimal (82%). In addition, observed exposure to rifampicin was systematically lower in children than in adults, with younger children and children living with HIV potentially requiring higher doses to reach similar exposures than in adults [2]. A follow-up IPDMA with PK data from 11 studies and 965 children (0 to 14 years old) was performed. Using individual outcome data in a subset of 493 children from 6 different studies, rifampicin exposure was the only relevant predictor of unfavourable outcome (p<0.05). A robust PK model was built with the individual concentrations from the complete set of children. Relevant covariates identified included age (maturation function with a hill coefficient of 4.9 and reaching half of the maturation at 10.1 months post-menstrual age), allometric scaling with weight, malnutrition (weight-for-age zscore, 5% decrease in bioavailability), and co-infection with HIV (26% decrease in bioavailability). The evaluation of simulated drug exposure under WHO-recommended doses confirmed that children are underexposed to rifampicin. Using a dosing algorithm based on the developed PK model, increasing rifampicin dose in smaller children are recommended to reach similar exposure than in adults.
Conclusion: An IPD-MA is a powerful tool to analyse PK data across studies with clear advantages in special populations. We successfully applied IPDMA to reveal that rifampicin exposure in children remains low with WHO-recommended doses, with younger and smaller children at a higher risk of being underexposed and therefore, at a higher risk of unfavourable outcome.
References: [1] Bauer RJ. CPT Pharmacomet Syst Pharmacol (2019) 8(8):538–56 [2] Implementing the end TB strategy: the essentials. Geneva: World Health Organization; 2015 (https://apps.who.int/iris/handle/10665/206499) [3] P. Solans B et al. Clin Infect Dis (2023) Jan 4:ciac973. doi: 10.1093/cid/ciac973