Systematic and quantitative analyses of pre-clinical Mycobacterium avium Lung Disease Tools for Drug Development and Transition from Animal Models to New Approach Methodologies

Abstract

Animal and new approach methodologies such as the hollow fiber system model [HFS] are used for Mycobacterium avium-complex [MAC] lung disease [LD] preclinical drug development. Our objective was to perform a systematic review to benchmark these pre-clinical tools. We performed a literature search to identify preclinical pharmacokinetics/pharmacodynamics [PK/PD] studies for MAC-LD. Preferred Reporting Items for Systematic Reviews and Meta-analyses was used for bias minimization. Twenty HFS-MAC and 3 mouse studies met PK/PD inclusion criteria. We created a novel quality score tool based on predictors of clinical response, design optimization, and information theory. The quality score was judged high in 10%, good in 50%, adequate in 30%, and poor in 10% of studies. Monte Carlo experiments for PK/PD target attainment were reported in 61% of studies. On repetitive sampling, the PK/PD target exposure estimate varied significantly between sampling days in 76% of studies. The solution was ordinary differential equations with parameter outputs such as {gamma} [nonlinear kill-slope] and time-to-extinction applied to both HFS-MAC and patients sputa CFU/mL output. Next, we ranked the antibiotics by extent of microbial kill as fold-improvement over guideline-based therapy. The three top ranked drugs for microbial kill were omadacycline [69-fold], tedizolid [19-fold], and ceftriaxone [8-fold]. We recommend the HFS-MAC as tractable for exposure-effect and dose-fractionation studies, ranking antibiotics effect, and for translation to clinical doses. The analyses inform us of HFS-MAC recommendations for regulatory authorities and drug developers, including quality scores for optimal PK/PD design for target identification, resistance suppression, and choice of the best novel regimen.