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TOPIC 389 - INTELLIGENT SOFTWARE FOR RADIATION THERAPY PLANNING

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 75N91019C00053
Agency Tracking Number: N43CA190053
Amount: $300,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: NCI
Solicitation Number: N/A
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
3380 MITCHELL LN
BOULDER, CO 80301-2245
United States
DUNS: 079099850
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jonathan Edelen
 (720) 502-3928
 jedelen@radiasoft.net
Business Contact
 Jonathan Edelen
Phone: (720) 502-3928
Email: jedelen@radiasoft.net
Research Institution
N/A
Abstract

Besides surgeryradiotherapy is the most effective treatment modality for localized prostate cancerThe success of radiotherapy stems from the exploit of a therapeutic window in tumor response and normal tissue tolerance which maximizes the chance of sterilizing the tumor while sparing the surrounding normal tissue from severe damageThis requires an accurate and individualized radiation dose distribution generated from the examination of the patient s medical imagesRadiation therapy is technically complex and labor intensiveIntensive human supervision and intervention are needed throughout the path of patient careArtificial intelligence and machine learning technologies are adept at automating workflows and tasks in this case the development of cancer treatment plansWe believe that this machine learning has incredible potential to address inherent problems in the existing treatment planning workflowOur approach will mitigate the current issues with treatment planningintegrate seamlessly with day to day operationsand will serve as a treatment solution that benefits patients in a way that limits their risk and extends their livesThe goal of this project is to develop a start to end prostate cancer treatment planning systemWe will work with three expert radiation oncology teams to archive existing patient data for use in training of artificial intelligence algorithmsThese algorithms will enable high quality plans to be generated with easeAt the completion of Phase Iwe will have a prototype interface that will allow users to create treatment plans and segmentation using artificial intelligence algorithmsAdditionallyusers will be able to evaluate these plans against other expert plans and against the training data

* Information listed above is at the time of submission. *

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