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Chaba, L.

Publications and source records attributed to Chaba, L..

2 recordsLinked to original sources

Comprehensive preclinical reevaluation of PaBQU and DBQU regimens identifies lesional liability in hard-to-treat forms of tuberculosis

Murine efficacy models inform advancement of preclinical tuberculosis treatment regimens to human clinical testing. A recent human Phase 2 trial was terminated early because investigational regimens (4-months of PaBQU or DBQU) did not meet the treatment shortening criteria outlined in the Target Regimen Profile ([≤] 3 months). We queried whether a factor leading to this early termination may have been lesional liability, meaning slow or diminished onset of effect in the caseum of complex lung lesions. We conducted a translational study, comparing the easy-to-treat BALB/c mouse, lacking complex lesions, to the hard-to-treat C3HeB/FeJ mouse that develops complex human-like lesions. We evaluated traditional and novel pharmacodynamic markers (colony forming units and RS ratio), relapse outcomes and ex vivo caseum pharmacokinetics. PaBQU and DBQU were slower to elicit bactericidal activity, RS ratio activity and prevent relapse in the C3HeB/FeJ mouse than the BALB/c mouse. A reference regimen (BPaMZ) had less lesional liability than PaBQU and DBQU. Fewer drugs in PaBQU were projected to achieve target attainment in caseum compared to BPaMZ, particularly early in treatment due to slow accumulation of bedaquiline in caseum. Here, we demonstrated application of a multi-modality pharmacokinetic-pharmacodynamic analysis that compared regimen activity in the hard-to-treat C3HeB/FeJ and easy-to-treat BALB/c mouse models, identifying lesional liability of PaBQU and DBQU. Systematic interrogation of additional diverse regimens is needed to determine the value of preclinical lesional liability as a means of predicting clinical treatment shortening activity.

microbiology↗

Predicting tuberculosis relapse based on 28-day CFU, RS ratio, and/or drug contribution for novel regimens in the relapsing mouse model

Treatment shortening in tuberculosis therapy is needed, but testing all novel antibiotic combinations is unfeasible. Especially the tuberculosis relapsing mouse model is time- and resource demanding. Therefore, our objective is to develop a computational model predictive of long-term relapse prevention in mice based on short-term biomarkers, increasing the number of regimens that can be tested and prioritize regimens for further development. The innovative ribosomal RNA synthesis (RS) ratio is utilized to characterize drug effect on Mycobacterium tuberculosis health and activity, together with colony forming units (CFU) in murine lungs. Nine datasets of 58 unique regimens with 843 short-term biomarker and 2,239 long-term relapse observations were leveraged for model development in 3 iterations with external validations. The final model included therapeutic predictors, such as CFU and RS ratio change from baseline, and corrected for experimental conditions, to enable unbiased ranking of regimens between experiments. Model performance was optimal without model structure change despite fully separate model development at each iteration. Final external validation had an area under the receiver operator curve of 0.90. Challenging the model by assessing removal of either biomarker showed that performance of CFU only was similar to CFU and RS ratio once the sterilizing contribution of individual drugs to the regimens was accounted for. New drugs without this contribution quantified could benefit from RS ratio determination to predict relapse. Our predictive model can successfully differentiate between 2-, 3-, and 4-month regimens in the relapsing mouse model based on 4-week data only, supporting acceleration of treatment-shortening regimen development. One Sentence SummaryOur predictive model ranks new drug regimens by tuberculosis relapse prevention based on 28-day CFU and RS ratio, or on CFU only for known drugs.

pharmacology and toxicology↗