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The harness for n‑of‑1 medicine

Trial-grade medicine built for individual cash-pay economics. One system of action for doctors, nurses, and patients so that concierge clinics can retain and scale better.

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.

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.

The clinic is where people now act on their health, so each year a patient like this stays is one they choose again, and they stay where their protocols are followed that closely and every question reaches someone who knows their care, which is how a concierge clinic grows.

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

You’re being expected to run a miniature clinical trial while also managing full time clinic volume, and your system was made to schedule appointments. Your clinic has its doctors, and 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. What every visit leaves behind

    Every visit leaves labs to chase, re-tests to schedule and messages to return, and your doctors keep that list themselves on top of a full day of visits, so that list decides how many patients your clinic can carry.

  2. The trend across every visit

    The charts built for clinics keep each visit on its own page and leave the trend to be pieced together, so the most expensive hours in your clinic go to reading back through old reports before each patient walks in.

  3. The patient you stop hearing from

    A patient who goes quiet leaves nothing on the chart and nothing on the calendar, so the first sign a clinic gets is the year’s review that never gets booked, and by then that patient is one you have to win all over again.

  4. Whether each protocol is working

    Whether each protocol is safe and working is the answer a patient pays your clinic for, year after year, and your doctors are holding that answer in memory, for every patient they see.

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

The frontier moves faster than its trials, and your patients often run combinations no single trial has tested, so iksa built the AI harness for n‑of‑1 medicine to bring each of them a trial’s rigor with the team you already have. 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 the range that applies to that patient and the critical-value rules. It reads what each patient tells it every day, so its agents run every patient’s journey at once, from where each one actually is.
  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. Inside them, routine questions get answered at any hour and the rest go to the person whose call it is, so a nurse’s time goes where only a nurse will do.
  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. Each morning your nurse sees who needs a call and why, and the labs your doctors are watching stay on one list beside it, so your clinic reaches each patient ahead of their need.
  4. Who decidesA clinician decides every change to a dose or a protocol, and for each patient your clinic switches on, once your nurse has reviewed their profile, the AI takes their routine questions off your team’s list. The agents draft each follow-up and reply for a person to approve, so each nurse carries more patients and every decision stays with your team.

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 walks in prepared with a sourced answer, while the markers and targets that doctor set keep being followed over months. What the patient has asked their treatment companion is on that record too, so the next protocol the doctor proposes, and the patient chooses, starts from their own questions.

  • 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

    Every inquiry and patient message, from the channels your patients already use, reaches one inbox, where the nurse sees who is waiting and the doctor’s decision, with replies drafted from your approved answers, so the typing comes off your nurse’s day and what’s left is to approve, edit or skip.

  • 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, under your clinic’s name on the channel they already use, 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

Each year on this chart they chose your clinic again, so see it on a protocol you run.

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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. Long before anyone outside your clinic reads it, the same evidence is why a patient who pays for results stays with you, because what each protocol moved is measured, dated and in front of their doctor.

  1. Every value, back to its report

    Each value with the report it came from and the day it was taken, so your doctor reads each trend at its source, and the time it took to piece together goes to the next patient.

  2. A patient any of your doctors can pick up

    Each change to a protocol, back to the doctor who made it and the result it answered, so any doctor on your team picks up a patient from the last decision, and the standard holds as your clinic adds doctors.

  3. Which protocol each result came underEach result after an intervention, measured and dated under the protocol the patient was on, across patients, and in the same system you read what each therapy brings your clinic, month by month.

Trial‑grade medicine is already taking many forms across cash-pay clinics, from cell therapy and regenerative medicine to concierge and longevity

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

What clinic owners ask before they run trial‑grade medicine on iksa

How does this grow our clinic?

By winning and keeping more patients.Your clinic reaches out first, because the agents run every patient’s journey. Every inquiry, from the channels your patients already use, lands in one inbox as a lead, with a reply drafted from the answers your clinic has taught its own agents. Someone new with a medical question gets a drafted invitation to book a consultation, and the question goes to your clinicians. Each patient’s stage moves by itself, from first message to paying patient, and one who cancels with nothing booked moves to Lost while your team can still reach them. Routine questions from the patients you switch on get answered from their own plan, anything about a package or price reaches your front desk as a task, and a person approves every follow-up your clinic sends. So your clinic wins more of the patients who ask, keeps them through each protocol and runs 4.3x patients per nurse.

How does iksa help us keep patients from one year to the next?

Your nurse keeps each one in view.A patient who goes quiet comes up for your nurse with a message suggested from where their last conversation ended, to send or to let rest, and at each year’s review your doctor reads what their protocols moved and what they asked through the year, so the patient chooses their next year of care with your doctor from their own results. Each month you read your revenue as new, returning, growing, shrinking or lapsed, which tells you whether your patients are staying.

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, so your team books where it always has, and the inbox, the morning briefing and the follow-ups come on top of the systems it already knows.

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

No.It means a trial’s discipline on a protocol your doctor writes 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. iksa holds all of that for your team, so your patients stay in your care, nothing is randomized or blinded and no research paperwork comes your way.

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 research partner would read it only if your clinic takes part, de-identified, from patients who have consented, once ethics review is in place, so your team’s day stays as it is until your clinic chooses. The business associate agreement (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.