Pavan Asalapuram

I am a researcher in the Health Systems and Policy group led by Professor Cecilia Stålsby Lundborg, developing diagnostic decision infrastructure for drug-resistant infections. Tuberculosis is my primary model system, and the same approach applies to other bacterial and zoonotic infections where detection, resistance interpretation and antibiotic choice are linked.

Detecting resistance is only the first step. Its value depends on whether the result is interpreted and translated into better decisions: the right treatment for the individual patient, and more appropriate antibiotic use across health systems and in population-level AMR control. My work follows this chain: detect, interpret, decide, implement and monitor.

I bring about two decades of experience in infectious-disease diagnostics, spanning assay development, clinical evaluation across Europe, Asia and Africa, regulatory approval and quality-certified manufacturing. I led the development of a molecular test for multidrug-resistant tuberculosis included in the Treatment Action Group's 2024 TB Diagnostics Pipeline and referenced in the WHO Global Tuberculosis Report 2024.

My research connects four areas:

• Detection: rapid multiplex molecular and immuno diagnostics for drug-resistant infections, including tuberculosis, respiratory and zoonotic pathogens.
• Interpretation: machine-learning models that predict which resistance-associated mutations are clinically relevant, beginning with bedaquiline and the BPaLM regimen, where genotype–phenotype relationships remain poorly defined.
• Decisions: how diagnostic results translate into equitable treatment decisions and more appropriate antibiotic use, and the lifetime burden of disease that makes those decisions consequential.
• Implementation and surveillance: household-level health architecture, diagnostic gaps in One Health AMR surveillance, and linking diagnostic data to surveillance and policy.

A central question guiding my work is: How can resistance detection be translated into timely, equitable clinical and public-health decisions?

I welcome collaboration in drug-resistant infections, AMR, antibiotic stewardship, tuberculosis, One Health, diagnostics, machine learning for resistance prediction, implementation science and health policy.

I teach at Karolinska Institutet, KTH Royal Institute of Technology and Uppsala University, and have supervised master's theses in global health, focusing on diagnostics, global burden of diseases and policy implementation.