In vivo Tuberculosis models
Tuberculosis (TB) remains a significant global health challenge, exacerbated by rising drug-resistance and the urgent need for shorter, more effective treatment regimens. Evotec has developed and refined a range of well-established and novel preclinical TB models that allows assessment of drug and/or vaccine efficacy and explorations of new treatment and prophylactic options. These models offer distinct advantages for evaluating the pharmacodynamics, bactericidal and sterilizing effects of TB drug candidates or immunogenicity and protection of vaccines.
We have developed both, acute and highly acute in vivo TB models to enable rapid screening of novel drug candidates, offering early insights into their potential efficacy. To assess long-term treatment outcomes, we also use a relapse mouse model (RMM), specifically designed to evaluate the bactericidal and sterilizing effects of individual drugs and combinations. This model helps identify regimens with the potential to shorten the duration of TB treatment. The RMM has been extensively applied in large-scale studies as part of the PAN-TB consortium (www.pan-tb.org), highlighting our ability to deliver high-quality, complex preclinical trials at scale.
Evotec has developed an advanced Kramnik mouse model, which forms necrotic granulomas that closely mimic the pathology seen in humans. This model enables a more accurate translation of the disease's progression and the corresponding treatment response. To address the growing threat of drug resistant TB, we have also established in vivo models using a bedaquiline-resistant Mycobacterium tuberculosis strain. This allows us to evaluate the efficacy of new compounds or drug regimens against resistant infections. Across all models, pharmacodynamic data are integrated with in vitro profiling, mechanistic assays, and pharmacokinetic evaluations using phase-appropriate translational modeling frameworks. This comprehensive approach enhances predictive accuracy and supports informed decision-making in TB drug development.
The integration of these diverse in vivo models allows us to rigorously evaluate drug combinations and novel therapeutic candidates, supporting the development of improved TB treatment strategies. Our platform highlights the importance of using multiple, complementary TB models in preclinical research to better predict clinical outcomes and accelerate the discovery of effective therapies against both TB.
Overall, we have built a comprehensive nonclinical pharmacology platform that generates critical data to guide decision-making - from early drug discovery through to late-stage development.
