Development of User-Friendly Tuberculosis Screening Technology for Rural India

Development of Tuberculosis Screening Technology for Pervasive Rural Health Mission

Objective

• The objective of this project is to develop a user-friendly Tuberculosis (TB) detection kit based on appropriate TB antigens and antibodies interaction on a lateral flow assay. The specific objectives are as follows: Identification, production, and purification of antigens specific to Mycobacterium tuberculosis., Analysis of antigen-antibody interactions, including binding affinity, sensitivity, and specificity., In silico and laboratory-scale analysis of Antigen-Antibody Interaction and development of a prototype fabric matrix for lateral flow assays., Development and validation of a fabric matrix embedded with antibodies for the detection of tuberculosis.

Description

• Tuberculosis (TB) is a major public health threat, with a high mortality rate in India., Current diagnostic methods lack sensitivity and specificity, especially in resource-constrained settings., This project aims to develop a user-friendly TB detection kit based on TB antigens and antibodies., The technology will be accessible to rural and semi-urban populations, improving early detection., It will be especially useful for primary health workers with limited access to laboratories., The project also has the potential to extend its use to screen for other immune-suppressed disorders., AI-based systems may be employed for remote monitoring and diagnostics in the future.

Impact

• The development of this Tuberculosis Screening Technology is expected to have a significant impact on public health and the socio-economic status of the rural population. By providing an accessible and accurate TB detection method, it aims to: Reduce undetected TB cases among the rural population., Improve early diagnosis and treatment, reducing TB-related mortality., Enhance patient comfort and safety through non-invasive testing., Increase the availability of TB screening in resource-limited areas., Offer a cost-effective alternative to traditional laboratory testing methods., Create opportunities for scaling up and incorporating AI-based systems for remote monitoring and diagnostics.