# TOPIC 405: INTRATUMORAL BIOSENSING FOR IN VIVO PHARMACOTYPING

> **NIH NIH N44** · LODESTONE BIOMEDICAL, LLC · 2022 · $2,050,000

## Abstract

This project addresses the problem that several rounds of varied immunotherapy treatments over an extended period are often needed to find one that is effective in treating tumors in a particular patient. The proposed solution is an Immunotherapy Response Indication System (IRIS) to monitor treatment response directly in a patient’s own tumor while testing sub therapeutic doses of multiple candidate drugs to determine the best therapeutic option rapidly and safely. The intratumoral monitoring capabilities of the proposed IRIS implantable biosensor and wireless magnetic reader are key to enabling this pharmacotyping strategy. The work plan in this Phase II contract focuses on preclinical safety and performance testing that is foundational to future clinical translation. This pharmacotyping capability enabled by IRIS will allow clinicians to optimize treatment decisions in the early stages of treatment, and during the later stages of treatment in cases of acquired resistance. Our initial clinical product development goal is to track real-time responses within the tumor to immunotherapy in glioblastomas and melanoma brain metastases. Enabling faster selection of
patient-specific treatments could increase cancer survival rates in the future

## Key facts

- **NIH application ID:** 10724131
- **Project number:** 75N91022C00043-0-9999-1
- **Recipient organization:** LODESTONE BIOMEDICAL, LLC
- **Principal Investigator:** CHRISTIAN KNOPKE
- **Activity code:** N44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $2,050,000
- **Award type:** —
- **Project period:** 2022-09-19 → 2024-09-18

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10724131

## Citation

> US National Institutes of Health, RePORTER application 10724131, TOPIC 405: INTRATUMORAL BIOSENSING FOR IN VIVO PHARMACOTYPING (75N91022C00043-0-9999-1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10724131. Licensed CC0.

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