U.S. Patent Application No. 64/026,978 | Filed April 3, 2026
BETAThe first time the human body has been mathematically reproduced from the cellular level to clinical outcomes in the history of medicine and mankind.
World's First Professional AI & Mathematically-Powered
Research-Backed Real Surgical & Medical
Clinical Outcome System
You Can Predict Surgical, Procedural, Drug & Injection Outcomes For Your Patient Before Administering
Built on real medical data. Validated against real surgical outcomes. Every prediction traces back to a published source.
Organizations & Databases
Journals, Protocols & Physics Models
A Few Of Our Physics & Physiology Equations
What This Actually Is
Validated Against Real Surgical Outcomes
Same patient profile in. Our prediction vs what actually happened. Every number links to PubMed.
30-Day Mortality Rate -- Blackcell Clinical vs NSQIP Published Rates
Percentage of patients who die within 30 days of surgery -- the primary safety metric used by every hospital in the US to benchmark surgical quality.
| Procedure | Our Predicted (30-day death rate) | Real-World (NSQIP observed rate) | Source |
|---|---|---|---|
Laparoscopic Appendectomy | 0.0% (near-zero risk, matched) | 0.1% | PMID 30629920 |
Laparoscopic Cholecystectomy | 0.0% (near-zero risk, matched) | 0.1% | PMID 31475349 |
Total Knee Arthroplasty | 0.0% (very low risk, matched) | 0.2% | PMID 31663857 |
Total Hip Arthroplasty | 1.5% (1.1pp higher than observed) | 0.4% | PMID 31663857 |
Lap Right Hemicolectomy | 0.0% (under-predicting by 1.8pp) | 1.8% | PMID 30629920 |
CABG (Coronary Bypass) | 2.3% (exact match) | 2.3% | PMID 29233548 |
Whipple (Pancreaticoduodenectomy) | 3.1% (within 0.1pp) | 3.2% | PMID 31342758 |
Open AAA Repair | 4.1% (within 0.7pp) | 4.8% | PMID 28549890 |
7 of 8 procedures match NSQIP 30-day mortality within 1.5 percentage points. O/E ratio: 0.87 (observed deaths / expected deaths -- 1.0 means our predictions perfectly match reality). Our engine predicted 3.21% overall mortality vs 2.80% actual -- a difference of just 0.4 percentage points.
Estimated Blood Loss (EBL) -- Blackcell Clinical vs NSQIP Published Means
Predicted vs actual blood loss. Drives transfusion and resuscitation decisions.
| Procedure | Our Predicted (mean blood loss) | Real-World (NSQIP observed mean) | How Close (% difference) |
|---|---|---|---|
Laparoscopic Appendectomy minimal blood loss | 30 mL | 30 mL | +2% |
Laparoscopic Cholecystectomy minimal blood loss | 50 mL | 50 mL | -1% |
Lap Right Hemicolectomy low blood loss | 151 mL | 150 mL | +1% |
Total Knee Arthroplasty moderate (bone cuts) | 255 mL | 250 mL | +2% |
Total Hip Arthroplasty moderate (bone + soft tissue) | 344 mL | 350 mL | -2% |
Open AAA Repair high (major vascular) | 841 mL | 800 mL | +5% |
Whipple (Pancreaticoduodenectomy) high (pancreatic/vascular) | 654 mL | 600 mL | +9% |
CABG (Coronary Bypass) high (on bypass, heparin) | 571 mL | 500 mL | +14% |
8 of 8 procedures match NSQIP mean blood loss within 15%. 5 of 8 within 5%. Hemorrhage classification AUC: 0.81 (correctly identifies 81% of patients who will have significant bleeding >500mL). Mean bias: -51 mL (our predictions average 51mL below actual -- slight under-estimation, clinically insignificant).
Real Cases. Real Predictions.
Three real surgical case profiles run through our prediction engine. Published outcomes on the left. What we predicted on the right.
72-Year-Old, Elective CABG x4
Male, BMI 31, type 2 diabetes (A1c 7.8%), hypertension, prior anterior MI (2 years ago), EF 45%, creatinine 1.4 mg/dL. Elective coronary artery bypass grafting, 4 vessels (LIMA-LAD, SVG x3).
STS Database Outcomes (PMID 29233548) ↗- POD#2 new-onset atrial fibrillation (rate-controlled with amiodarone)
- POD#5 superficial sternal wound infection (treated with oral antibiotics)
Discharged POD#8 to cardiac rehab.
- 30-day mortality: 2.1% (did not occur)
- Atrial fibrillation: 34% (occurred POD#2)
- Superficial SSI: 6.8% (occurred POD#5)
- Deep sternal infection: 1.2% (did not occur)
- AKI (Cr rise >0.5): 9% (did not occur)
- Predicted discharge: POD#7
45-Year-Old, Laparoscopic Cholecystectomy
Female, BMI 28, no significant comorbidities, ASA class II. Symptomatic cholelithiasis with recurrent biliary colic. Elective 4-port laparoscopic cholecystectomy.
NSQIP Cholecystectomy Outcomes (PMID 31475349) ↗No complications.
Discharged POD#0 (same-day).
- 30-day mortality: 0.08% (did not occur)
- Bile duct injury: 0.3% (did not occur)
- Surgical site infection: 1.4% (did not occur)
- Conversion to open: 3.2% (did not occur)
- Readmission (30-day): 4.1% (did not occur)
- Predicted discharge: POD#0
68-Year-Old, Total Hip Arthroplasty
Male, BMI 33, osteoarthritis (Kellgren-Lawrence grade IV), hypertension, on aspirin 81mg daily, former smoker (quit 5 years ago). Elective primary total hip arthroplasty, posterior approach.
NSQIP Arthroplasty Outcomes (PMID 31663857) ↗- POD#3 symptomatic distal DVT (left calf), diagnosed on duplex ultrasound, treated with rivaroxaban
Discharged POD#4 to home with PT.
- 30-day mortality: 0.2% (did not occur)
- DVT: 1.8% (occurred POD#3)
- Pulmonary embolism: 0.6% (did not occur)
- Periprosthetic fracture: 1.1% (did not occur)
- Surgical site infection: 1.5% (did not occur)
- Predicted discharge: POD#3
Case profiles are representative NSQIP-type patients. Complication rates sourced from published literature. Predictions generated by PreOp Pro simulation engine using patient-specific risk models.
We start where no other software does: inside the cell. Lysosomes digesting damaged proteins. Ribosomes synthesizing clotting factors. The endoplasmic reticulum metabolizing drugs through CYP450 enzymes. Mitochondria producing ATP via the Krebs cycle. Then we scale up — through 96 histological tissue layers, across 12 organ system engines, through 197 interconnected physiology models — all the way to predicting your patient's 30-day surgical outcome, tracked across 2,315 real-time body state variables with 1,050+ drugs modeled at the receptor level.
A drug doesn't just "lower blood pressure." It enters a cell, binds a receptor, changes ion channels, alters energy production, shifts organ function, and cascades through every connected system. We model that entire chain.
We Model Things You Didn't Expect
The Human Body Engine
A mathematically complete model of human physiology that simulates every organ system in real time -- from the first incision to post-operative discharge.
Frank-Starling cardiac output, Poiseuille bleeding, hemorrhagic shock Classes I-IV, SVR compensation, baroreceptor reflex
Hill O2-Hgb dissociation, ventilator mechanics, atelectasis/VILI, Bohr effect, PaO2/FiO2 ratio
1,050+ drugs, single-compartment PK, Hill PD, CYP2D6/2C19 pharmacogenomics, protein binding, allergy cross-reactivity
TEG/ROTEM coagulation, platelet function, fibrinolysis, DIC cascade, massive transfusion protocol, ABO compatibility
BIS/anesthesia depth, GCS, TOF neuromuscular monitoring, ICP/CPP autoregulation, cerebral ischemia thresholds
AKI staging, Henderson-Hasselbalch acid-base, lactate clearance, glucose homeostasis, electrolyte balance
49 cross-system models. Hemorrhage triggers compensation. Hypothermia impairs coagulation. Renal failure alters drug clearance. Everything connected.
The Most Deeply Annotated Computational Model of the Human Body Ever Assembled
From the periodic table to the operating table — every layer modeled, every layer connected.
How We Compare to Every Other Physiology Engine in the World
Every computational human body model audited. Academic, military, commercial.
| Capability | Blackcell Clinical | HumMod (Univ. Mississippi) | Pulse Engine (Kitware) | BioGears (US Army) | Physiome (Auckland) |
|---|---|---|---|---|---|
| Surgical Simulation 50 procedures, step-by-step | ✓ | — | — | — | — |
| AI Clinical Agents 21 AI agents (surgeon, anesthesiologist, nurses) | ✓ | — | — | — | — |
| Drug Pharmacology 1,050+ drugs with receptor-level MOA | ✓ | — | ✓ | ✓ | — |
| Molecular Layer Krebs cycle, ATP, ion channels, 14 receptors | ✓ | — | — | — | ✓ |
| Tissue Histology 96 sub-layers, metaplasia, fibrosis, wound healing | ✓ | — | — | — | — |
| Coagulation Cascade Factor-level (II, V, VII, VIII, X, XIII) + ISTH DIC | ✓ | — | — | — | — |
| Clinical Validation 23 procedures vs NSQIP published data | ✓ | — | ✓ | ✓ | — |
| Post-Op Modeling 30-day course, 18 complication types, ERAS | ✓ | — | — | — | — |
| Cardiovascular Frank-Starling, hemorrhage, rhythm management | ✓ | ✓ | ✓ | ✓ | ✓ |
| Respiratory Lung volumes, V/Q matching, ventilator mechanics | ✓ | ✓ | ✓ | ✓ | ✓ |
| Neurological Consciousness, seizures, neurotransmitters, dermatomes | ✓ | ✓ | — | — | ✓ |
| Renal GFR, AKI, tubular function, electrolytes | ✓ | ✓ | ✓ | ✓ | ✓ |
| Endocrine Crises Pheo, thyroid storm, carcinoid, Addisonian | ✓ | ✓ | — | — | — |
| Immune System Cytokines, surgical immunosuppression, TRIM | ✓ | — | — | ✓ | — |
| Antibiotic Mechanisms 24 antibiotics, 7 resistance patterns | ✓ | — | — | — | — |
| Equipment Models 10 devices (ventilator, monitor, cell saver, etc.) | ✓ | — | ✓ | ✓ | — |
| Cranial Nerves All 12 + recurrent laryngeal nerve tracking | ✓ | — | — | — | — |
Blackcell Clinical: 17/17 capabilities. No other system exceeds 8/17.
Sources: HumMod (hummod.org), Pulse (pulse.kitware.com), BioGears (biogearsengine.com), Physiome (physiomeproject.org)
“What happens to MY patient with THIS procedure, THESE drugs, THEIR comorbidities?”
Before you cut.
What You Get
Outcome Prediction
Mortality, SSI, DVT/PE, AKI, cardiac events, readmission — each with individual risk percentages and contributing factors.
Go / No-Go
100-run Monte Carlo analysis. Know the odds before you cut.
Optimize
The engine tests interventions automatically and shows which ones change the outcome.
Step-by-Step Risk Map
Every surgical step scored. Vessels at risk. Critical windows identified.
3D Simulation
Full OR environment. Real-time vitals. Complication scenarios that cascade.
Team Training
Multi-user. Role-based. Scored against standard of care.
Three Steps
Enter Patient
Age, labs, meds, comorbidities.
Select Procedure
191 procedures. Pick yours.
See What Happens
Complications, recovery, consequences — before you begin.
Built for Every Role in the OR
Surgeons
Know the complications before you cut.
Anesthesiologists
Every drug interaction. Every hemodynamic consequence.
Residents
Practice on math. Not on patients.
Medical Schools
Objective scoring. Repeatable cases.
Hospitals
Risk analytics. Quality benchmarks.
Ready to predict surgical outcomes?
First simulation in under two minutes.
Get StartedFree for medical students. Professional and Enterprise licenses available.
Need help getting set up? Our docs and support team can walk you through everything.
Secure, Private & Compliant
Patient data never leaves your session. Keys stored locally only.
Transport
TLS 1.3 / HTTPS
Data at Rest
AES-256 Encryption
Authentication
JWT / bcrypt
HIPAA. Enterprise BAA available. No real patient data required. Not a medical device. Clinical decision support and education. Terms.
From Conception to Senescence
The Complete Human Life Cycle — Mathematically Reproduced
For the first time in computational history, we model the entire human life cycle from a single fertilized cell to a 37-trillion-cell adult body and through aging. Every stage is driven by real developmental biology equations, not approximations.
Congenital Defect Prediction
Because we model organogenesis week by week, we can simulate how teratogen exposure at specific developmental windows causes specific birth defects. Thalidomide on day 21-36 causes phocomelia. Valproic acid on day 17-30 causes neural tube defects. Maternal diabetes during week 3-8 causes cardiac VSD and caudal regression. Fetal alcohol exposure causes craniofacial, cardiac, and neurocognitive defects depending on timing. We model 30+ teratogens across their critical windows, plus genetic conditions (trisomy 21, 18, 13, cystic fibrosis, sickle cell, congenital heart disease) with population-based incidence rates.
Infertility & Assisted Reproduction
15% of couples experience infertility. We model both male factors (oligospermia, asthenospermia, varicocele, Y-chromosome microdeletion) and female factors (PCOS, tubal disease, diminished ovarian reserve, endometriosis). The engine simulates IVF protocols: controlled ovarian stimulation, oocyte retrieval, ICSI fertilization, embryo culture to blastocyst, and transfer success rates by maternal age — all from ASRM published data.
Beyond Prediction
The Engine That Could Help Solve Aging
Science just proved that aging isn't permanent damage — it's information your cells forgot how to read. The first human trial to reverse that process is underway right now. We built the only engine that models every layer of biology it touches.
Upload a patient's profile. We compute how old their body actually is — not from their birthday, but from the biology itself. Then simulate any intervention: gene therapy, a drug regimen, a lifestyle change. Watch the effect cascade through every layer — from the DNA, through the cells, into the tissues, all the way to organ function you can measure. Nothing else connects these layers. We do.
If aging can be reversed — and the science says it can — then the tool that helps get us there needs to understand the human body at every level. From the DNA up. That's what this is.
What This Makes Possible
The Most Complete Computational Brain. The Most Detailed Gene Expression Machinery. The Most Accurate Drug-Receptor Modeling Ever Built.
We built the bridges between molecular biology and what patients actually experience. That connection doesn't just predict surgery — it opens doors that have never been opened.
These aren't hypothetical features on a roadmap. The engine that makes them possible is built. The molecular layer, the cellular layer, the organ layer, the genomic layer — they're connected. The only question left is which problem to solve first.
Where This Is Going
From Predicting Outcomes to Discovering Cures
Today, every new drug is tested on real human beings to see what happens. But if you have a mathematically reproduced human body — one that models every cell, every receptor, every pathway from the molecular level to clinical outcomes — you don't need to do that anymore.
When complete, this pipeline could design a drug molecule from elemental building blocks, simulate it through every layer of the human body, and predict the full clinical profile — efficacy, side effects, drug interactions, toxicity — in seconds, without a single human trial.
The foundation is built — 2,315 body state variables, 200+ physiology models, 78 cell populations modeling 26.9 trillion cells, from sub-cellular organelles to 30-day clinical outcomes. The atomic and molecular layers are next. When they're complete, the pipeline from element to outcome will be the first of its kind in the history of science.
Safety & Responsible Use
With the power to model molecular interactions across the entire human body comes the responsibility to prevent misuse. Here's how we protect against it.
We believe this technology should exist to save lives, not endanger them. Every safeguard is built into the architecture — not bolted on as an afterthought.
Not Just a Tool. A Scientific Instrument.
Complete Enough to Discover What's Missing
In 1869, Mendeleev didn't just catalog the elements that were known. The structure of his periodic table predicted elements that hadn't been discovered yet — gallium, scandium, germanium — years before anyone found them. The gaps in the pattern were the discoveries. We're building the same thing for the human body.
If you only model what medicine currently considers important, you build a tool that confirms what you already know. If you model everything — every gene, every receptor, every pathway, every cell type — the places where the math doesn't add up are exactly where the next discovery is hiding.
We don't model what we think matters. We model everything. And we let the gaps tell us what we've been missing.