# One-click Automated 3D Treatment Planning for Radiopharmaceutical Therapy

> **NIH NIH R44** · VOXIMETRY, INC. · 2024 · $2,000,000

## Abstract

PROJECT SUMMARY/ABSTRACT
The Radiopharmaceutical Therapy (RPT) market is projected to surpass the Technitium-99m market by 2025,
with an emphasis on metastatic prostate cancer, neuroendocrine tumors, and lymphoma. Driven by well-
tolerated treatments and fewer side-effects, experts have estimated 150 new theranostic centers will be needed
in the U.S. to deliver an estimated 50,000–200,000 treatment cycles/year. Currently, all RPT treatments
administer a standard therapeutic dose despite unique patient physiology and pharmacokinetics. From
experience with external beam radiation therapy (EBRT), we know that patient-specific prescriptions based on
absorbed dose leads to better patient outcomes. A key technology required to enable this personalization is fast,
accurate, whole-body patient-specific dosimetry. In a prior Phase II SBIR, Voximetry was able to integrate our
fully benchmarked and IP-protected Monte Carlo dosimetry algorithm into a cost-effective RPT treatment
planning solution (TorchTM) by adding additional features such as image registration, contour propagation, and
voxel-based pharmacokinetic (PK) modeling. Torch was designed to model uptake and clearance routes of any
drug class (e.g., small molecules, peptides, antibodies) and any radionuclide, effectively adding a ‘swiss army
knife’ tool into the clinician’s RPT toolkit. Leveraging the gamma rays emitted by the RPT agent, Torch can
calculate how much radiation energy is deposited within each voxel of organs and tumors throughout the body.
Estimates of voxel-level whole-body patient-specific dosimetry are better correlated with response than the
standard uptake value (SUV) information that is clinically available today. Using this approach, Voximetry has
developed a fast, accurate, RPT treatment planning solution aimed to inform clinicians with extremely accurate
voxel-based Monte Carlo (MC) dosimetry in a matter of minutes. Additionally, Vox has developed a GPU
accelerated Monte Carlo SPECT reconstruction algorithm that leads to dosimetry estimates which differ from
conventional reconstruction algorithms by at least 25%, which is seen as clinically significant. This information
will support clinical decisions to personalize safe therapeutic doses. Automation of this RPT dosimetry workflow
is especially important for healthcare systems that would like to implement dosimetry-guided therapy in clinical
practice but are currently ill-equipped in terms of expertise and resources to perform advanced dosimetry for
RPT. By enabling automation, Vox will ultimately benefit cancer patients by making available a personalized
treatment that targets metastatic cancer that in many cases is more efficacious and has fewer side effects than
chemotherapy. The specific aims that will be accomplished in the proposal are to (1) Develop automated
segmentation tools for organs and risk and tumors using artificial intelligence, (2) develop scanner calibration,
partial volume correction, and Monte Carlo reco...

## Key facts

- **NIH application ID:** 10909885
- **Project number:** 5R44CA221491-05
- **Recipient organization:** VOXIMETRY, INC.
- **Principal Investigator:** Joseph Grudzinski
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $2,000,000
- **Award type:** 5
- **Project period:** 2018-04-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10909885

## Citation

> US National Institutes of Health, RePORTER application 10909885, One-click Automated 3D Treatment Planning for Radiopharmaceutical Therapy (5R44CA221491-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10909885. Licensed CC0.

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