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Tuberculosis (TB) is a bacterial infection primarily affecting the lungs, caused by Mycobacterium tuberculosis. Despite available antibiotics, TB remains a significant public health issue, particularly in developing countries, largely due to the rise of drug-resistant strains. Drug resistance occurs when bacteria survive despite antibiotic treatment. Gaurav Srivastava's research focuses on modeling drug resistance in TB bacteria to uncover the mechanisms behind this issue. His approach employs mathematical, computational, and molecular modeling to explore the pharmacokinetics and pharmacodynamics of antibiotics and their interactions with the bacteria. One key method is computational simulation, which tests various drug combinations and dosages in silico before proceeding to laboratory tests. This helps identify optimal combinations for treating drug-resistant TB. Additionally, Srivastava studies the molecular biology of drug-target interactions and genetic mutations that contribute to resistance. Understanding these mechanisms can lead to the development of new drugs that effectively target resistant strains. His research also has implications for precision and personalized medicine, allowing treatments to be tailored based on individual genetic profiles. Overall, Srivastava's work significantly contributes to TB research and the advancement of effective treatment strategies, ultimately aiming to improve patient outcomes.