Biology subjects

Savic, R. M.

Publications and source records attributed to Savic, R. M..

8 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2026

Predicting early bactericidal activity of tuberculosis drug combinations using a translational pharmacokinetic-pharmacodynamic modeling approach

Phase IIa pulmonary tuberculosis (TB) trials typically assess the early bactericidal activity (EBA) of monotherapy for over 14 days. However, few studies have evaluated drug combinations, even though optimal monotherapy doses may not directly translate to combinations. Translational pharmacokinetic-pharmacodynamic (PK-PD) modeling has shown promise in predicting human treatment responses based on preclinical monotherapy data; however, its application in drug combinations remains limited. This study aimed to extend and validate our previously developed translational monotherapy PK-PD modeling platform to predict the EBA of two-drug combinations. Interactions between bedaquiline, pretomanid, linezolid, and pyrazinamide were characterized using two modeling approaches: the empirical SUPER method and the mechanistic General Pharmacodynamic Interaction model. Both approaches were independently linked to our translational platform and validated using mouse data and Phase IIa clinical results from the NC-001 study. Both modeling methods identified consistent interaction patterns, including antagonistic interactions when bedaquiline was combined with either pretomanid or linezolid. Pyrazinamide has emerged as the most effective companion for both bedaquiline and pretomanid. Our platform reasonably predicted 14-day clinical sputum colony-forming unit counts for multiple two-drug combinations, with most observations falling within the 95% prediction intervals, supporting its use in accelerating regimen development. Our study demonstrated that the translational PK-PD platform reliably predicts both short- and long-term outcomes for combinations, regardless of the interaction model. This supports its application across drug development stages to inform dose selection and effective companion drugs for anti-TB therapies.

pharmacology and toxicology↗

bioRxiv2024

Contribution of front-line, standard of care drugs to bactericidal responses, resistance emergence, and cure in murine models of easy- or hard-to-treat tuberculosis disease

By assessing the standard of care regimen for tuberculosis (TB) in BALB/c and C3HeB/FeJ mice, we demonstrate that rifampin, with or without pyrazinamide, is essential to effective bactericidal response and resistance suppression. Potency measurements in an in vitro lipid-rich model and rabbit caseum assay recapitulate the significance of rifampin as a sterilizing agent. These outcomes align with clinical performance, thus emphasizing the value of in vitro predictive tools and murine TB models with human-like pathology.

microbiology↗

bioRxiv2024

The kinetics of bedaquiline diffusion in tuberculous cavities opens a window for emergence of resistance.

Cavitary tuberculosis (TB) is difficult to cure and a site of relapse. Bedaquiline has been a wonder drug in the treatment of multidrug resistant TB, but emergence of resistance threatens its sustained success. To investigate the role of drug distribution in resistance development, we designed a novel laser-capture microdissection scheme to spatially resolve the penetration of bedaquiline in the necrotic center (caseum) of cavities, a recalcitrant site of disease. Working with preclinical models that form large necrotic lesions, we profiled bedaquiline and two next generation diarylquinolines TBAJ-587 and TBAJ-876. Drug concentrations were measured in laser-captured areas of cavity caseum as a function of time and distance from blood supply. To simulate drug coverage in patient cavities, the data were modeled, and drug penetration parameter estimates were linked to clinical plasma pharmacokinetics for bedaquiline and the new diarylquinolines. Pharmacokinetic-pharmacodynamic (PK-PD) simulations revealed that bedaquiline reaches efficacious concentrations in outer and deep caseum after several weeks to months and lingers at subtherapeutic concentrations up to 3 years after therapy ends. TBAJ-587 and TBAJ-876, currently in clinical development, achieve bactericidal concentrations in caseum more rapidly and shorten the window of suboptimal concentrations post treatment compared to bedaquiline. Simulations of clinically plausible dosing schemes were conducted to guide the design of clinical trials for cavitary TB and help mitigate resistance development. In summary, the slow kinetics of diffusion of bedaquiline into and out of cavity caseum creates spatio-temporal windows of subtherapeutic concentrations. Site-of-disease simulations of TBAJ-587 and TBAJ-876 predict reduced opportunities for resistance development. SIGNIFICANCEClinical resistance to bedaquiline has emerged faster than anticipated. Understanding potential contributing factors could help curb further resistance development, not only for bedaquiline but also for the next generation diarylquinolines currently in phase 2, TBAJ-587 and TBAJ-876. Here we hypothesized and confirmed that the extended time to reach steady state and slow clearance of bedaquiline leads to extremely slow diffusion into and out of cavity caseum, a recalcitrant site of TB disease and relapse. Through modeling of experimental data in a preclinical model of cavitary TB and clinical simulations, we show that the next generation diarylquinolines may reduce spatio-temporal windows of resistance development compared to bedaquiline. Our results can inform dosing schemes of diarylquinoline-based therapies that limit resistance development.

pharmacology and toxicology↗

bioRxiv2023

Prospectively predicting BPaMZ Phase IIb outcomes using a translational preclinical mouse to human platform

Despite known treatments, tuberculosis (TB) remains the worlds top infectious killer, highlighting the pressing need for new drug regimens. To prioritize the most efficacious drugs for clinical testing, we previously developed a PK-PD translational platform with bacterial dynamics that reliably predicted short-term monotherapy outcomes in Phase IIa trials from preclinical mouse studies. In this study, we extended our platform to include PK-PD models that account for drug-drug interactions in combination regimens and bacterial regrowth in our bacterial dynamics model to predict cure at end of treatment and relapse 6 months post-treatment. The Phase III trial STAND, testing new regimen pretomanid (Pa), moxifloxacin (M), and pyrazinamide (Z) (PaMZ), predicted to shorten treatment duration by 2 months was put on hold after a separate ongoing trial showed adding bedaquiline (B) to the PaMZ regimen (SimpliciTB) suggested superior efficacy. To forecast if the addition of B would indeed benefit the PaMZ regimen, we applied an extended translational platform to both regimens. We predicted currently available short- and long-term clinical data well for drug combinations related to BPaMZ. We predict the addition of B to PaMZ will shorten treatment duration by 2 months and be non-inferior compared to control HRZE, both at the end of treatment for treatment efficacy and 6 months after treatment has ended in relapse prevention. Using BPaMZ as a case study, we have demonstrated our translational platform can predict Phase II and III outcomes prior to actual trials, allowing us to better prioritize the regimens most likely to succeed.

pharmacology and toxicology↗

bioRxiv2023

Lung microenvironments harbor Mycobacterium tuberculosis phenotypes with distinct treatment responses

Tuberculosis lung lesions are complex and harbor heterogeneous microenvironments that influence antibiotic effectiveness. Major strides have been made recently in understanding drug pharmacokinetics in pulmonary lesions, but the bacterial phenotypes that arise under these conditions and their contribution to drug tolerance is poorly understood. A pharmacodynamic marker called the RS ratio quantifies ongoing rRNA synthesis based on the abundance of newly-synthesized precursor rRNA relative to mature structural rRNA. Application of the RS ratio in the C3HeB/FeJ mouse model demonstrated that Mycobacterium tuberculosis populations residing in different tissue microenvironments are phenotypically distinct and respond differently to drug treatment with rifampin, isoniazid or bedaquiline. This work provides a foundational basis required to address how anatomic and pathologic microenvironmental niches may contribute to the long treatment duration and drug tolerance during treatment of human tuberculosis.

microbiology↗

bioRxiv2023

Translational predictions of phase 2a first-in patient efficacy studies for antituberculosis drugs

BackgroundPhase 2a trials in tuberculosis typically use early bactericidal activity (EBA), the decline in sputum colony forming units (CFU) over 14 days, as the primary outcome for testing the efficacy of drugs as monotherapy. However, the cost of phase 2a trials can range from 7 to 19.6 million dollars on average, while more than 30% of drugs fail to progress to phase 3. Better utilizing preclinical data to predict and prioritize the most likely drugs to succeed will thus help accelerate drug development and reduce costs. We aim to predict clinical EBA using preclinical in vivo pharmacokinetic-pharmacodynamic (PKPD) data and a model-based translational pharmacology approach. Methods and FindingsFirst, mouse PK, PD and clinical PK models were compiled. Second, mouse PKPD models were built to derive an exposure response relationship. Third, translational prediction of clinical EBA studies was performed using mouse PKPD relationships and informed by clinical PK models and species-specific protein binding. Presence or absence of clinical efficacy was accurately predicted from the mouse model. Predicted daily decreases of CFU in the first 2 days of treatment and between day 2 and day 14 were consistent with clinical observations. ConclusionThis platform provides an innovative solution to inform or even replace phase 2a EBA trials, to bridge the gap between mouse efficacy studies and phase 2b and phase 3 trials, and to substantially accelerate drug development.

pharmacology and toxicology↗

bioRxiv2021

Combination of Mycobacterium tuberculosis RS ratio and CFU improves the ability of murine efficacy experiments to distinguish between drug treatments

Murine tuberculosis drug efficacy studies have historically monitored bacterial burden based on colony forming units of M. tuberculosis in lung homogenate. In an alternative approach, a recently described molecular pharmacodynamic marker called the RS ratio quantifies drug effect on a fundamental cellular process: ongoing ribosomal RNA synthesis. Here we evaluated the ability of different pharmacodynamic markers to distinguish between treatments in three BALB/c mouse experiments at two institutions. We confirmed that different pharmacodynamic markers measure distinct biological responses. We found that a combination of pharmacodynamic markers distinguishes between treatments better than any single marker. The combination of the RS ratio with colony forming units showed the greatest ability to recapitulate the rank order of regimen treatment-shortening activity, providing proof of concept that simultaneous assessment of pharmacodynamic markers measuring different properties will enhance insight gained from animal models and accelerate development of new combination regimens. These results suggest potential for a new era in which antimicrobial therapies are evaluated not only on culture-based measures of bacterial burden but also on molecular assays that indicate how drugs impact the physiological state of the pathogen.

microbiology↗