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The harness for n‑of‑1 medicine

A three-sided system of action for doctors, nurses and patients

When a doctor writes a protocol change in their note, the nurse opens the patient to it and the patient’s next answer starts from it. That is the harness at work, with a clinician deciding every change.

Request a walkthroughFollow one patient’s two years
One woman’s care seen from three sides, in turn. Her physician reads what has moved since her previous yearly assessment and writes the decision into the record. Two high pressure measurements she took at home reach her nurse, who has the physician’s instruction about them open, rewrites one line of a prepared answer to pass it on, and sends it. On her own side, Patient AI answers a question about her plan from what her physician wrote, gives the emergency advice first for those measurements, and says her nurse has them.
Illustrative

A doctor’s change moves the follow-up too, because one record holds protocol and business

Follow Patient G, 52, from their first visit into their third year. At each turn, what their protocol monitored and what the doctor decided sit beside the follow-up and the visit that came of it.

Patient G, 52, in her third year with the clinic, Month 0 to Year 2 on one record. Month 0: First visit, Agentic CRM, Protocol, Clinical Intelligence. Clinical: Her own baselines set at the first assessment; Metabolic protocol starts, ApoB target 70. Commercial: Inquiry answered; First visit, booked. A new patient’s question gets a reply from her nurse in the clinic’s own wording, and of three appointment times put to her, the one she took now holds her first appointment. At her first assessment two of her readings are pinned as her own starting points, her physician draws the lower number to aim for on one of them, and a metabolic plan of strength and interval sessions begins from that same line. Month 6: Monitoring, Patient AI, Decision, Clinical Intelligence. Clinical: Visceral fat 134 cm², above range; Protocol adjusted. Commercial: Visit, booked. Six months in, a new scan lands above her starting figure and above the reference, and the reply she gets sets her exercise plan out as her physician wrote it, says her nurse has the result, and leaves it for her physician to go through with her at her appointment. Year 1: Decision, Renewal, Agentic CRM. Clinical: Year 1 review: ApoB 83, visceral fat 121; Protocol held. Commercial: Year 1 review message; Renewed for Year 2. Month 14: Monitoring, Decision. Clinical: Short sleep reported; Wearable 6.1 hours, below her usual 6.4; Sleep plan added. Month 18: Monitoring, Decision. Clinical: Visceral fat 126 cm², above range; Plan held, DEXA again at Year 2. Commercial: Visit confirmed. Month 23: Renewal. Commercial: Lab draw change requested, times offered; Test preparation message. Year 2: Monitoring, Decision, Renewal. Clinical: ApoB 80 mg/dL, above target; Visceral fat 133 cm², above range; A third strength session added; Statin chosen for her SLCO1B1. Commercial: Renewed for Year 3. At her two-year mark her physician starts a cholesterol-lowering drug picked to suit one of her genes, on a fat-lowering diet and after a liver blood test, because her heart-risk marker has sat above the goal set for her at every test, with the two documents the call rests on set out beneath. After her second-year review her nurse crosses out one plain line of a prepared message, writes in that her physician is beginning the cholesterol drug they discussed once her bloods have been checked, sends it, and her record gains a tab for her third year.

What would the last protocol you changed look like across these two years?

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When a protocol changes, the doctor, nurse and patient each act on it

All three work from that one change, and what they add up to is clinical outcomes for patients and commercial outcomes for the clinic.

A man’s third yearly review: his latest lab results with his main cholesterol marker above the goal his doctor set while the more familiar cholesterol number sits within normal limits, no new plaque on his heart scan, and his doctor’s note that he takes his two cholesterol medicines as prescribed and that a third is added.

Doctors · Clinical Intelligence

A research team behind every doctor, whose change the other two start from

Clinical Intelligence: AI for longevity medicine
A patient writes that she has been unwell since her latest dose increase and asks whether her birth control still protects her; her nurse, with the treatment plan and the physician’s newest entry open beside a prepared answer, replaces one sentence so that it carries the physician’s answer, her birth control and her dose both kept with a second method added, and only then does it go out.

Nurses · Agentic CRM

Every nurse works from the patient’s protocol, so the patient comes back

Agentic CRM: scheduling and follow-up
A woman asks whether her hormone dose is wrong; the reply asks her not to change it on her own, says her nurse will follow up and names the visit note it repeats.

Patients · Patient AI

A concierge for every patient, answering from the plan their doctor last changed

Patient AI: the treatment companion

The clinical context platform keeps each patient’s whole record beside your EHR

It reads notes, labs, genetics, wearables and messages, each with its source, and it will only compound as models get better because it is a unified system of record.

A genetics finding, a late-night message from one invented patient, a run of her sleep data, a physician’s written decision and a blood result each come in looking like what they are and settle, in date order, as a line naming where and when it came from, until her two years stand as one chart, closing on her physician’s latest decision, beside the clinic’s EHR, which goes on holding her appointments and notes.
  1. What a general model never hearsA model anyone can buy will never know this doctor changed this patient’s protocol, while the harness starts every answer from that change, which is how Clinical Intelligence beats the general models.

  2. When a lab report lands

    Every value is checked against its source and set on the patient’s own line beside their first draw, the range and the target the doctor set. A critical value raises an alert. Markers the protocol follows, like lipids and blood counts on weekly mTOR inhibition, lead the doctor’s view, and a person decides what happens next.

  3. When a patient-reported outcome comes in

    A possible adverse event becomes a card with what the patient reported and the background from their record, and goes by urgency to the nurse or doctor. What the patient reports joins the labs on the record, so the doctor reads both before the next decision.

Run every protocol properly and your clinic practices n‑of‑1 medicine on every patient

  1. Four patients at once, each read in their own form against their own first draw, with a doctor deciding each change: Patient B's ApoB against the target his doctor set with his coronary CT beside it, Patient C's draws at each of her doctor's decisions as a ledger, Patient D's wearable as a line against her usual, and Patient E's scans as bars from his own first scan.

    Every patient you keep runs as their own n‑of‑1

    Each patient’s own series runs through every protocol they stack over the years, from an incretin and a hormone to a cell therapy, so a doctor reads each result against where that patient started and decides each change.

    What is n‑of‑1 medicine?
  2. Patient G's and Patient C's care set out row by row, each doctor's decision with the reading beside it, the next reading after it, the patient's own baseline and the report and month each value came from.

    The evidence falls out of care

    The record you keep to care for each patient already shows how they answered each change a doctor made, with the source and date a study needs.

    Research with clinics
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What your partner will ask once you’ve walked them through one protocol change

How clinics start
Is iksa one system, or three products?

One system.Clinical Intelligence is the clinical AI your doctors ask, Agentic CRM is the CRM your nurses follow up from and Patient AI is the treatment companion your patients write to. All three work on the same patient, so a change the doctor writes on Tuesday is there for the nurse and is what the patient’s next answer starts from.

Is this protocol management software?

It starts there.Treatment protocol tracking is the first thing it does, with each patient’s markers, dates and targets on one line, and then the doctor, the nurse and the patient each act on what changed.

Where does the doctor make the change?

In their own note.iksa reads that note into the patient’s record with the reasoning behind it, so nobody enters it twice and the nurse and the patient start from what the doctor wrote.

How does iksa run n‑of‑1 medicine for every patient?

Each patient’s line starts at their first draws. Every lab after them joins that line, with the range on its report and the target the doctor set, and their genetics, wearables and what they tell the clinic sit beside it. When something moves, the doctor sees the change next to its report and decides, and the next read starts from that decision.

Do we keep our EHR?

Yes.Your EHR stays the record of each visit. iksa reads it directly where it connects and as documents where it doesn’t, and beside it keeps the years of each patient’s care, the protocol and each decision on it and why, writing nothing back by default.

Do we have to take all three at once?

No.A clinic begins with its doctors, then brings on its nurses with Agentic CRM and its patients with Patient AI over the months that follow.

Can iksa change a protocol on its own?

Never.Every clinical decision stays with your clinicians. A follow-up iksa drafts waits for the nurse to approve it, the patient’s answers stay inside the plan the doctor wrote with anything clinical going to their nurse, and an emergency gets the instruction to call for help straight away.

Compare iksa with your EHR

See one protocol change reach all three sides

Bring a protocol you run. We’ll walk one patient through it.

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