Radiation Treatment Planning Automation

Let your AI agent handle plan generation, updates, and compliance checks so your oncology team can focus on patient outcomes, not paperwork.

You spend hours each week in Eclipse or ARIA, exporting data, recalculating doses, and writing summaries in Word or Excel. As a dosimetrist or radiation oncologist, you’re stuck updating plans after every protocol change, chasing missing info over email, and double-checking for errors before sign-off.

An AI agent that automates radiation therapy plan creation, revisions, and documentation for oncology teams using clinical data and protocols.

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What this replaces

✕Export patient data from ARIA into Excel for dose calculations
✕Manually update treatment parameters in Eclipse after protocol changes
✕Draft plan summaries in Microsoft Word for tumor board meetings
✕Email colleagues to clarify missing or inconsistent data
✕Recalculate and cross-check doses after every revision

The hidden cost

What this is really costing you

In hospital oncology departments, dosimetrists and radiation oncologists lose 8-10 hours each week manually building and revising treatment plans. They juggle patient data from ARIA, recalculate doses in Excel, and draft summaries for review meetings. Every protocol update means repeating these steps, risking missed details and compliance headaches. This repetitive work keeps specialists from direct patient care.

Time wasted

8-10 hrs/week

Every week, burned on work an AI agent handles in minutes.

Money lost

$20,800-$26,000/year

In salary, missed revenue, and operational drag — annually.

If you keep ignoring it

Ignoring this leads to documentation errors, delayed treatment starts, and potential compliance violations with bodies like the Joint Commission. Staff frustration grows, and patients may wait longer for care.

Cost estimates derived from U.S. Bureau of Labor Statistics occupational wage data and O*NET task analysis.

Return on investment

The math speaks for itself

Today — without agent

9 hrs/week

of manual work

$23,400/year/ year

With your AI agent

1.5 hrs/week

agent-handled

$3,900/year/ year

You save

$19,500/year

every year, reinvested into growing your business

Estimates based on U.S. Bureau of Labor Statistics median salary data and O*NET task importance ratings from worker surveys. Time savings assume 80% automation of eligible task components.

Jobs your agent handles

What this agent does for you

Complete jobs, handled end-to-end — so your team focuses on what matters.

Create a New Treatment Plan

You ask your agent to generate a plan for a new patient, incorporating all relevant clinical data.

Update an Existing Plan

You ask your agent to revise a plan after a physician requests a dosage change.

Prepare a Summary for Review

You ask your agent to draft a summary of the plan for the weekly oncology team meeting.

Check for Data Gaps

You ask your agent to review the plan and highlight any missing or inconsistent information.

How to hire your agent

1

Connect your tools

Link your existing treatment planning, electronic health record, and coding tools.

2

Tell your agent what you need

Example: 'Create a radiation plan for patient ID 2045, stage II lung cancer, with current CT data and physician notes.'

3

Agent gets it done

The agent delivers a ready-to-review treatment plan, complete with documentation and flagged issues for your attention.

You doing it vs. your agent doing it

Gather data, enter parameters, calculate doses, and draft plan by hand.
Agent assembles data and drafts plan automatically for your review.
45 min/plan
Manually update parameters and recalculate everything.
Agent updates plan instantly based on your instructions.
30 min/revision
Write up plan details and highlight key points for meetings.
Agent drafts a clear, shareable summary in seconds.
20 min/summary
Manually cross-check all plan elements for gaps or errors.
Agent flags missing or inconsistent data instantly.
15 min/check

Agent skill set

What this agent knows how to do

Plan Generation from Clinical Systems

Pulls patient data from ARIA and generates a draft radiation plan following NCCN guidelines for your review.

Instant Protocol-Based Revisions

Applies protocol updates from your clinical governance system to existing plans and recalculates doses in seconds.

Summary Drafting for Team Meetings

Creates concise, shareable plan summaries in Word or PDF format for tumor boards or weekly reviews.

Data Consistency Checks

Scans plans for missing demographics, outdated labs, or inconsistent parameters, flagging issues before sign-off.

Scenario Comparison Reports

Produces side-by-side comparisons of alternative treatment regimens, outputting results for team discussion.

AI Agent FAQ

Yes, the agent connects to ARIA and Eclipse via available APIs or HL7 interfaces. Your IT team can help set up secure connections to pull and update patient data directly.

All data is encrypted in transit using TLS 1.3 and never stored after processing. The agent operates within your hospital’s secure network and meets HIPAA requirements.

The agent supports standard protocols and most common cancer types. For rare or highly individualized cases, manual review and adjustment are still required. Always review outputs before final approval.

Typical plan generation or revision takes less than 2 minutes after you provide instructions. You can review, edit, and export results immediately for further use.

The agent can support multiple users, including dosimetrists and oncologists, within your clinical workflow. Assign tasks, review outputs, and collaborate securely across your department.

Browse more

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Related tasks

AI Agent for Plan the use of beam modifying devices, such as compensators, shields, and wedge filters, to ensure safe and effective delivery of radiation treatment. →AI Agent for Develop treatment plans, and calculate doses for brachytherapy procedures. →AI Agent for Advise oncology team members on use of beam modifying or immobilization devices in radiation treatment plans. →AI Agent for Calculate, or verify calculations of, prescribed radiation doses. →AI Agent for Develop requirements for the use of patient immobilization devices and positioning aides, such as molds or casts, as part of treatment plans to ensure accurate delivery of radiation and comfort of patient. →AI Agent for Record patient information, such as radiation doses administered, in patient records. →AI Agent for Perform quality assurance system checks, such as calibrations, on treatment planning computers. →AI Agent for Calculate the delivery of radiation treatment, such as the amount or extent of radiation per session, based on the prescribed course of radiation therapy. →AI Agent for Design the arrangement of radiation fields to reduce exposure to critical patient structures, such as organs, using computers, manuals, and guides. →AI Agent for Conduct radiation oncology-related research, such as improving computer treatment planning systems or developing new treatment devices. →

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