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The harness for n‑of‑1 medicine

Built to run clinical trial grade medicine for individuals. For concierge clinics running regenerative, peptide, and hormone protocols over years: one system of action for doctors, nurses and patients.

Request a walkthroughOne patient, two years
Users
3,000+
First-Year ROI
2.7x

We’re happy to walk through more of the specific expected outcomes based on your clinic’s profile and what we’ve achieved at our other clinics.

iksa’s launch film: one invented patient, their doctor, their nurse and their treatment companion on one plan that keeps changing, from a statin chosen for their genes reaching all three sides, to their message about a swollen knee after their cell therapy reaching their nurse and their doctor the same day, to everything in their record becoming one evidence read beside their doctor, who writes the decision into the note. It closes on the steel dial shifting its rings and locking into place at the center of the frame, then settling above the wordmark iksa.ai.

Where iksa’s team has worked and studied

  • Johns Hopkins University
  • Myriad Genetics
  • Novartis
  • Novo Nordisk
  • Pfizer
  • McKinsey & Company
A bright, quiet lobby with a small tree growing in a curved glass enclosure and low white seating along the wall.

A clinic that knows every patient between visits, not only on the day they come in

Over three years one woman’s doctor runs five treatments side by side, each changing on its own clock: menopause hormones from the first day, reviewed each year, a short androgen trial that ends when it does not help, a weight medicine raised month by month with strength training beside it from the start, then held at its dose when a body scan shows too much of her loss is lean mass, the same scan stepping up the training, and a cosmetic review once her face thins.

What is changing, and which patients this is about

A patient like this stays for years on protocols that keep changing, followed the way an oncologist follows someone through treatment, and they don’t have cancer.

Healthcare will be more personalized, more concierge, with stacked protocols, and people will pay the premium for results over time. It is changing the way healthcare is manufactured, delivered and consumed.

No clinic can afford a trial’s whole team for a single patient

A pharma trial has trial management, data capture, safety reporting, biostatistics and a team of people around one protocol. A clinic has its doctors. With no payer, the entire clinical, commercial and regulatory record is theirs to carry, and these micro-ecosystems of trial-grade medicine are running on spreadsheets.

One invented patient’s report, unwell since their latest dose increase and unsure their birth control still protects them, goes two ways at once: around a pharma trial’s protocol, trial management, data capture, safety reporting, biostatistics and a team of people each take a part, finish their own paperwork and hand it back, while beside them the same protocol has a single doctor, whose one seat takes every part, clinical, commercial and regulatory, until the stack bends it.

  1. Trial management

    Every visit leaves labs to chase, retests to schedule and messages to return, and the doctor keeps the list a trial pays people to keep.

  2. Data capture

    A trial checks every value against its source, while the charts built for clinics keep each visit on its own page and leave the trend to be pieced together.

  3. Safety reporting

    A side effect in a trial has a form, a clock and a named person, with a sponsor paying. At a clinic it’s a message to the clinician the patient trusts.

  4. Biostatistics and a team of people

    Monitors check that the protocol is followed and, where a trial has one, a data monitoring committee and its statistician ask whether it is safe and working. A doctor holds that answer in memory, for years.

Every patient is a trial of one, and iksa is the harness that runs it

The frontier moves faster than its trials, and patients often run combinations no single trial has tested. iksa built the AI harness for n‑of‑1 medicine to bring them a trial’s rigor. A harness is what the AI knows, the protocol it works inside, what it monitors and the clinician who decides.

  1. What it knowsThe doctor’s notes, labs, body composition, the genome report, the wearable and what the patient reports, with each lab read against its report’s range and the critical-value rules.
  2. What it works insideEach protocol the doctor wrote, often several at once, and your clinic’s approved answers, so every change stays with that doctor.
  3. What it monitorsThe markers and re-tests the doctor set, each on its own clock, from safety labs weeks into a dose step to a cell therapy’s months of follow-up, and any side effect a patient reports.
  4. Who decidesA clinician decides every change to a dose or a protocol, and a nurse reviews each patient’s profile before the AI answers them.

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

Stacked protocols interact, a cell therapy in the knee holding back the strength block that protects lean mass. So each side’s AI has read the same patient, and a small team works like a superhuman one. That delivers clinical outcomes for patients and commercial outcomes for the clinic.

  • A physician asks one invented patient’s chart whether a cholesterol-lowering drug still makes sense when their heart scan showed no calcium; the reply prints their heart-risk marker, unchanged across two years and above the goal their physician set, and a gene result that bears on which drug and how much of it, with the lab report and visit note it came from, while a dashed circle for that goal draws itself inside a plain circle for their current level.

    Doctors

    A research team behind every doctor

    Clinical Intelligence: AI for longevity medicine

    A doctor asks one patient’s whole record what moved and gets a sourced answer, while the markers and targets that doctor set keep being followed over months.

  • One invented patient’s note about poor rest, with their nightly figure, reaches their nurse, who has the upcoming appointment and the physician’s most recent call to hand; the nurse crosses out a line of a prepared reply, writes in that call in its place with a question about night sweats, and it goes out under the nurse’s role.

    Nurses

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

    Agentic CRM: scheduling and follow-up

    The nurse sees what’s due, what was flagged and the doctor’s decision beside a drafted reply, and approves, edits or skips it before it reaches the patient.

  • Late in the evening one invented patient asks why their physician’s number for a heart marker is stricter than the one on their lab printout; a plain reply prints, separates the two and passes the reasoning to their nurse, and as it prints a small scale fills in around their own value, which sits within the printout’s limit and above their physician’s.

    Patients

    A concierge for every patient

    Patient AI: the treatment companion

    A question at eleven at night gets an answer from that patient’s own protocol, and anything clinical goes to their nurse.

One patient. Every side. Every year.

Patient G, 52, in her third year with the clinic, drawn as one timeline from Month 0 to Year 2 in seven lanes. Visits: booked and seen at Month 0, visits at Month 6 and 18, and a review at Year 1 and Year 2, each booked ahead. Protocol: metabolic protocol from Month 0; adjusted from Month 6; sleep plan from Month 14. Measures, Visceral fat area · cm², range up to 100 cm², against the patient's own baseline of 128 at Month 0, dotted: 128 at Month 0, above range; 134 at Month 6, above range; 121 at Year 1, above range; 126 at Month 18, above range; 133 at Year 2, above range. Wearable: sleep each night as a continuous line against the patient's own baseline of 6.4 hours. Messages: 12 from the patient. Clinician's decisions: Month 6, protocol adjusted, visceral fat 134 cm² at Month 6, no lower than at Month 0 after six months on the protocol; Year 1, protocol held, visceral fat 121 cm² and ApoB 83 mg/dL at Month 12, calcium score 0, so the nutrition in the protocol is given the year; Month 14, sleep plan added, her message at Month 13, and the wearable below her own baseline; Month 18, plan held, dexa again at year 2, visceral fat 126 cm² at Month 18; Year 2, a third strength session added, visceral fat 133 cm², above the 100 cm² reference; lean mass index down to 6.1 kg/m²; knee pain limited her lower-body training; Year 2, statin chosen for her slco1b1, ApoB 80, above target at every draw: lifetime exposure. Renewal: renewed at the Year 1 and Year 2 reviews.

Illustrative

See it on a protocol your clinic runs.

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Every protocol produces the evidence regulators require and life sciences acquires

If you run the protocol properly, the evidence falls out of care. That is what opens partnerships with biotechs for decentralized trials, with research and investment running inside the clinic.

  1. What a study can open

    Each value with the report it came from and the day it was taken.

  2. Who a study can follow

    Each change to a protocol, back to the doctor who made it and the result it answered.

  3. Which protocol each result came underEach result after an intervention, measured and dated under the protocol the patient was on, across patients.

Trial‑grade medicine is already taking many forms, from longevity to integrative oncology

Our vision is autonomous personalized medicine in dispersed micro-ecosystems globally operating at trial-grade.

  • Longevity

    See longevity
    Patient J, 51's ApoB stays at 78 mg/dL while his doctor strikes the old target of under 80 and sets a new one of under 60, because his Lp(a) is 168 nmol/L and his CT shows plaque.

  • Anti‑aging

    See anti‑aging

  • Concierge medicine

    See concierge medicine

  • Women’s health

    See women’s health

  • Men’s health

    See men’s health

Also

What owner-physicians ask before they run trial‑grade medicine on iksa

Does this replace our EHR?

No.Your doctors keep charting where they chart, and the calendar and payments stay put. iksa reads it all where it connects, takes the rest in as documents and holds each patient’s protocols beside them over years, writing nothing back by default.

Does trial‑grade mean we are running a registered trial?

No.It means a trial’s discipline on a protocol written for one patient: a baseline, what each intervention should move, the side effects to watch, a dated re-test, a stop rule, the doctor’s decision and a source behind every result. Patients stay in your care, and nothing is randomized or blinded.

Why not use a general AI model?

It doesn’t understand your protocols.It wasn’t specialized for your segment, it is often behind the times, and when a patient asks, it creates anxiety where they needed your guidance. iksa is a white-labeled physician AI for your patients, carrying doctor-approved guidance, and a Clinical Intelligence that beats the general models for your doctors, because it follows each protocol’s markers, re-tests and targets.

Can our clinic take part in research?

Your clinic decides.Care run with a trial’s discipline produces evidence as it goes, and a study would read it only if your clinic takes part, de-identified, from patients who have consented, once ethics review is in place. The BAA governs how iksa handles your patients’ data every day.

n‑of‑1 medicine, in fullWhy personalized medicine, why nowHow clinics startSecurity and trustWhat iksa adds

Run your hardest protocols at trial‑grade, for every patient you keep

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

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