# Tuberculosis in Malawian children under five years old: exploring non-invasive diagnostic strategies and the impact of malnutrition on treatment pharmacokinetics

> **NIH NIH K01** · HENRY FORD HEALTH + MICHIGAN STATE UNIVERSITY HEALTH SCIENCES · 2024 · $186,447

## Abstract

PROJECT SUMMARY/ABSTRACT
The International Research Scientist Development Award will provide tremendous support for the candidate’s
transition to independence. The candidate is a pediatrician and rising pediatric infectious diseases physician
with expertise caring for children with tuberculosis (TB) and severe acute malnutrition (SAM). The candidate’s
long-term goal is to conduct high-impact clinical studies and implementation research to improve detection and
treatment of TB and other infectious diseases in children living in low-income countries. This award will provide
the candidate with five years of mentored research and career development time, and he will spend >50% of
the award period based at Kamuzu University of Health Sciences (KUHeS) and KUHeS affiliate Malawi
Liverpool Wellcome Clinical Research Program in Blantyre, Malawi. The candidate’s primary mentors for this
award are Dr. Henry Mwandumba (Primary LMIC-based Mentor) and Dr. Karl Seydel (Primary US Mentor). Dr.
Mwandumba will provide excellent mentorship in the area of his expertise, implementing TB clinical studies in
this setting. Dr. Seydel brings a wealth of experience conducting high-impact pediatric clinical studies in
Blantyre and will provide guidance in this area. Through a combination of mentorship, coursework, and
practical experiences, the candidate proposes to develop expertise in the following key areas: leadership and
implementation of pediatric clinical research in Malawi; advanced study design (including clinical trials) and
statistical methods; and 3) pharmacokinetic study design and analysis. This training plan will coincide with, and
complement, a rigorous research plan. The proposed research focuses on TB in children under five years old
(U5s), an age group with unacceptably and disproportionately high mortality from TB. The large “case finding
gap” in this age group is a major problem globally and largely a consequence of the lack of TB diagnostic tools
that are both practical and accurate in U5s. There is also a knowledge gap regarding the effect of co-prevalent
SAM on the pharmacokinetics of first-line antituberculosis therapy in U5s. For Aim 1 of the proposal, we plan
conduct a prospective cohort study to evaluate the accuracy of promising new TB diagnostic strategies that
utilize non-invasively collected specimens (stool and urine) in hospitalized Malawian U5s with presumed
pulmonary TB. For Aim 2 of the proposal, we plan to longitudinally characterize the pharmacokinetics of first-
line antituberculosis therapy (rifampin, isoniazid, pyrazinamide, and ethambutol) in Malawian U5s with co-
prevalent SAM and TB as they recover from both diseases. This research will provide valuable insights into the
diagnosis and management of TB in U5s and put the candidate in excellent position to secure independent
research funding for more in-depth investigations in this setting in the areas of diagnostics and
pharmacokinetics for pediatric TB and other infectious disea...

## Key facts

- **NIH application ID:** 11230626
- **Project number:** 7K01TW012922-02
- **Recipient organization:** HENRY FORD HEALTH + MICHIGAN STATE UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Bryan Vonasek
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $186,447
- **Award type:** 7
- **Project period:** 2024-09-20 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11230626

## Citation

> US National Institutes of Health, RePORTER application 11230626, Tuberculosis in Malawian children under five years old: exploring non-invasive diagnostic strategies and the impact of malnutrition on treatment pharmacokinetics (7K01TW012922-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11230626. Licensed CC0.

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