Intellectual Property India Publishes Patent Application for A Non-Invasive Competitive Lateral Flow Assay-Based Point-Of-Care Device And Method For Prediction Of Menstruation Through Salivary Progesterone Detection

MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641085300 A) filed by Sathyabama Institute Of Science And Technology; Dr. Mercy Paul Selvan; Dr. P. Grace Kanmani Prince; Dr. Krupakar Parthasarathy; Dr. J. Bethanney Janney; Dr. S. Jancy; Dr. A. Viji Amutha Mary; and Dr. Sam Ebenezer Rajadas on July 12, 2026, for A Non-Invasive Competitive Lateral Flow Assay-Based Point-Of-Care Device And Method For Prediction Of Menstruation Through Salivary Progesterone Detection.

Inventors include Dr. Mercy Paul Selvan; Dr. P. Grace Kanmani Prince; Dr. Krupakar Parthasarathy; Dr. J. Bethanney Janney; Dr. S. Jancy; Dr. A. Viji Amutha Mary; and Dr. Sam Ebenezer Rajadas.

The application for the patent was published on July 17, 2026, under issue no. 29/2026.

Abstract: The present invention discloses a non-invasive competitive lateral flow assay-based point-of-care diagnostic device and method for predicting menstruation through salivary progesterone detection. The device comprises a Sample Pad Module, a Conjugate Pad Module containing gold nanoparticle-labelled anti-progesterone monoclonal antibodies, a Nitrocellulose Membrane Module comprising a Test Line coated with a progesterone-protein conjugate and a Control Line coated with goat anti-mouse IgG antibodies, an Absorbent Pad Module, and a Diagnostic Interpretation Module. During analysis, progesterone present in saliva competes with the immobilized progesterone conjugate for binding to labelled antibodies, producing an inverse relationship between progesterone concentration and test-line intensity. The physiological decline in salivary progesterone occurring approximately 24–48 hours before menstruation enables early prediction of menstrual onset. The device provides rapid, portable, economical, and user-friendly point-of- care testing suitable for home healthcare, clinical applications, caregiver-assisted monitoring, and integration with smartphone-based image analysis systems for quantitative interpretation.

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