04 · 21 proprietary layers
Layer 21 of 21 · Longitudinal intelligence
Dynamic Twin Updates Periodic model updates over time.
Why it's needed
How does the model change when new data or relevant evidence arrives?
What it draws on
5 of 8 evidence domains.
What it produces
An updated view with change context, where implemented.
Why it's essential
Layer 21 of 21.
1 · What it does
What Dynamic Twin Updates does
The Twin is designed to change as the cancer journey changes. Dynamic Twin Updates is intended to describe how the Twin is updated when new data or relevant evidence arrives during the six-month journey, and how each change is reviewed and versioned.
2 · Scientific question
The question it addresses
How does the model change when new data or relevant evidence arrives?
Intended function
Describe the real update triggers, frequency, review workflow and versioning.
3 · Data inputs and required context
What it draws on
- 01 Molecular & genomic
- 03 Clinical context
- 04 Imaging integration
- 06 Treatment exposure
- 08 Evidence ecosystem
New results, clinical updates and evidence changes arriving after the baseline.
4 · Scientific basis
The science behind it
Scientific basis
An updated model is only as current as its most recent inputs. Update triggers might be new test results, new clinical information or evidence changes; each update needs review before it informs care.
5 · Output and evidence sources
What it produces
Main output
An updated view with change context, where implemented.
Output type
- Twin workflow function. Part of how the Twin is created, reviewed or updated, rather than an analytical result.
6 · Why it\u2019s essential
How it powers the Twin
Produces the updated longitudinal view and connects the six-month journey to the follow-on tracking options.
Report section
7 · Why it\u2019s needed
What it changes — for doctors, patients and researchers
Patients & caregivers
The Twin can be revisited as new information arrives; it does not watch the patient in real time.
Patient & Caregiver8 · Dependencies and limitations
Limitations
9 · Review and uncertainty
How the output is handled
Output status
An AI-assisted analytical output presented as structured findings for clinician review. It becomes part of a report only after the treating oncologist has reviewed and signed it.
How uncertainty is communicated
Each version states the date and the inputs that changed, and keeps the earlier version for comparison.
10 · Claim boundary
What this layer does not establish
It does not provide continuous, real-time monitoring of the patient.
The treating oncologist owns every decision. Every Twin report is reviewed and signed by the treating oncologist, then taken to KPCIRC's Molecular Tumour Board.
KPCIRC sign-off process