1.5 billion people live with chronic pain. Opioids work, but they addict. Topical creams are safe, but weak. Most new pain drugs are still found by trial and error.

We turn our own patient data into new pain drugs.

Our chemistry has already been tested in humans — in a published, randomized clinical trial run with Mount Sinai Hospital. AAI-201, the optimized successor, now heads into Phase 2a. And our AI engine, built on 7,000 patients of our own clinical data, is designed to deliver the next one.

One drug entering the clinic. One engine that designs the next.

Entering Phase 2aFDA pathway initiated
Non-OpioidZero addiction risk
7,000+ Patients TreatedFirst-party proprietary clinical data
AI Drug Discovery PlatformTrained on our own patient outcomes
5 Pharma PatentsDrug IP · Prosecution-ready
4 AI PatentsPlatform IP · Prosecution-ready
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The Problem
Every year, physicians write tens of millions of opioid prescriptions — not because opioids are the best option, but because topical alternatives are ineffective, wear off in 1–2 hours, and nothing better has come to market in decades. The same molecules have been recycled since the 1940s. Not one new mechanism of action has reached patients.
Our response: We generated what doesn't exist elsewhere: seven years of proprietary clinical data from 7,000+ patients treated with topical pain formulations. From that first-party dataset, we developed a novel prodrug now entering FDA Phase 2a — and are building an AI platform designed to develop the next generation of topical pain treatments, filling a pipeline gap the industry has left open for a generation.

Lidocaine: 1948. Diclofenac: 1973.
Capsaicin: ancient. Menthol: ancient.
These are still the options.

The Two Inadequate Options Available Today
Option A — Topical Anesthetics & NSAIDs

Safe. Local. Gone in under two hours.

Lidocaine, diclofenac, menthol, capsaicin — the entire topical pain pharmacy. All deliver short-duration, surface-level relief. Lidocaine fades in 60–120 minutes. Diclofenac requires multiple daily applications. Menthol and capsaicin mask pain rather than treat it. None sustain therapeutic analgesia beyond a few hours.

The benefit
Targeted delivery. Minimal systemic absorption. Safe for most patient populations.
The failure
Short duration. Frequent reapplication. No mechanism for sustained local release. When they wear off, patients escalate to systemic medication.
or
Option B — Systemic Analgesics

Sustained relief. Whole-body exposure.

Opioids and high-dose oral NSAIDs can maintain pain control for 8–12 hours. But to treat a localized injury, they alter brain chemistry and flood every organ system.

The benefit
Prolonged analgesic coverage. Effective for severe acute pain. Widely available.
The failure
Opioids carry addiction risk, sedation, respiratory depression, and transfer through breast milk. NSAIDs impair coagulation and wound healing. Both expose the entire body to treat a local problem.

This is the gap we built our company to fill.

The Analgesic GapWhere safe local therapy ends and opioid prescriptions begin

Local anesthetic
Unmanaged window
Systemic escalation
0h
1h
2h
4h
8h
12h
24h
Today
Lidocaine
The Gap
→ Opioids or systemic NSAIDs
What's needed
Single application → continuous local analgesia, up to 12 hours
When local anesthesia fades, patients enter a window of acute, unmanaged pain — typically 1–2 hours post-application. This is the precise moment systemic opioids are most commonly prescribed. No currently approved topical product can sustain pain control through this window. The clinical need is not incremental improvement. It is a fundamentally new class of locally-acting, sustained-release analgesic.
The Scale of This Unmet Need
313M
Major surgical procedures per year globally
Lancet Commission on Global Surgery
125K
Annual opioid overdose deaths worldwide
World Health Organization, 2019
1–2 hrs
Duration of topical lidocaine — the global standard of care
Clinical consensus; FDA labeling
0
Topical products delivering both fast onset and sustained relief
FDA product database; clinical review
The Pipeline Problem

This isn't just one missing drug.
It's an entire category that doesn't exist.

Until January 2025, no new class of analgesic had been approved in over two decades. The pipeline for topical, locally-acting, non-opioid pain therapeutics remains nearly empty. Solving this requires more than a single product — it requires a platform capable of systematically designing and accelerating new pain drugs from the molecular level up.

Why the Pipeline Stayed Empty — And What It Takes to Fill It
The absence of novel topical analgesics is not a failure of investment or scientific capability. It is a structural problem. Every new development attempt begins cold — because each failed program generates proprietary data that never enters the public domain. There is no shared clinical knowledge base for this drug class. AI-driven drug design has the potential to break this cycle, but machine learning models are only as valuable as the data they are trained on. For topical analgesics, that data does not exist in public repositories. It can only be generated through years of clinical use with novel formulations in real patients.
That is precisely what we spent seven years doing — and why our AI platform is built on a structural advantage that no competitor can replicate by starting today.
This Is Our Story
Our Story
This company didn't come from a pitch competition or a Silicon Valley lab. It came from a pharmacy bench — and seven years of watching patients walk in hurting and walk out with something that actually worked.
This is how a compounding pharmacy became an AI drug discovery company.
Compounding pharmacy laboratory

It starts in a compounding pharmacy. Not the kind you're picturing — not a back room mixing creams.

Under FDA regulations, compounding pharmacies operating at this scale maintained clean rooms, analytical laboratories, and qualified clinical pharmacists and chemists on staff. In practical terms, this was closer to a small-scale pharmaceutical R&D facility than a high street chemist.

The patients came in with pain. Post-surgical patients who couldn't sleep. Women recovering from childbirth with no safe options because they were breastfeeding. People with chronic wounds that wouldn't heal and wouldn't stop hurting. They'd already tried everything on the pharmacy shelf — the lidocaine creams that wore off in an hour, the menthol gels that did almost nothing, the diclofenac that required four applications a day and still left them reaching for pills by evening.

The pharmacy didn't hand them a standard tube and wish them luck.

They formulated. Tested. Listened to what patients and their treating physicians reported back. Reformulated. Adjusted concentrations, carriers, penetration enhancers. Listened again. Every outcome was documented — what worked, what didn't, how long the relief lasted, what the side effects were. Then they reformulated again.

Clinical pharmacist and chemist reviewing formulation data

This went on for seven years. Over 7,000 patients. Thousands of formulation cycles. A feedback loop between bench chemistry and bedside reality that most pharmaceutical companies never build — because the economics don't justify it and the patience doesn't exist.

But something happened that doesn't usually happen in this industry. The formula converged. Not incrementally better — fundamentally different.

Chemist working with Unguator mixer and precision equipment

A single application that delivered pain relief lasting up to 12 hours. No systemic absorption. No opioid risk. Safe enough that nursing mothers could use it — breast milk transfer measured below detection threshold. And beyond just numbing: it reduced inflammation and promoted wound healing.

That wasn't supposed to be possible from a topical.

42% pain reduction vs placebo. p < 0.001.
Zero serious adverse events.
Published, peer-reviewed clinical trial · Mount Sinai Hospital · 2022

The formulation was tested in a randomized controlled trial at Mount Sinai Hospital — one of the top-ranked medical institutions in the country. Forty-six postpartum women. The results were published in a peer-reviewed journal. Statistically significant pain reduction. Clean safety profile. A single application lasting up to 12 hours.

In pharmaceutical terms, that's not a concept. That's a clinical asset.

"Most companies would have stopped there."

A validated formulation. A published trial at a world-class hospital. A clear path to licensing or acquisition. That's a reasonable exit for most ventures.

But the data told a bigger story.

Seven years of clinical intelligence sat in those files — dosing patterns, tolerability signals, efficacy curves across pain types, formulation adjustments and their outcomes. Not a summary. Not an abstract. The raw, patient-level data from 7,000+ treatments with novel topical pain formulations.

This was a proprietary dataset for topical analgesics that didn't exist anywhere else. Not in any public database. Not in any pharma company's archives. Because nobody else had spent seven years doing what this team had done.

So instead of selling one drug, a different decision was made: develop the formulation into a novel chemical entity — a new prodrug with composition-of-matter patents, the kind of IP that underpins billion-dollar drug franchises and makes an asset genuinely acquirable — and simultaneously build an AI platform around that proprietary clinical dataset. Not to discover one drug. To generate a pipeline.

Asset 1 — The Drug

AAI-201

Novel prodrug. Not a reformulation. New chemical entity. Composition-of-matter IP. Validated in 7,000+ patients. Published clinical trial. Now entering FDA Phase 2a.

Asset 2 — The Platform

AI Prodrug Design Engine

Trained on proprietary first-party clinical data from seven years of patient treatments. Designed to generate new topical pain drug candidates across multiple indications. The drug gets acquired. The platform stays and generates the next one.

"One company. Two assets. One dataset that took seven years and 7,000 patients to build — and that no competitor can replicate by starting today."

See Our Solution
The Solution
One application. Twelve hours of pain relief. No opioids. No pills. No reapplication. AAI-201 is the first topical pain treatment designed to replace the moment a doctor reaches for an opioid prescription. Its chemistry has already been tested in humans — in a published clinical trial at Mount Sinai Hospital.
The Solution

What if one application could replace an opioid prescription?

AAI-201 · The first topical that lasts long enough to make opioids unnecessary

Today, when a lidocaine cream wears off after one or two hours, the only option for sustained pain relief is a pill — usually an opioid. AAI-201 eliminates that choice entirely. Apply it as a liquid. It gels on contact with skin and locks into place. Pain relief lasts up to 12 hours. The drug stays at the wound — nothing enters the bloodstream, nothing reaches the brain, nothing shows up in breast milk.

01

Apply it like a liquid.

Pour it on the wound. On contact with skin, it transforms into a gel and locks into place — no wrapping, no patches, no repeated application. It stays exactly where the pain is.

Replaces patches, creams, and reapplication
02

Two drugs in one molecule.

The moment it reaches the wound, the molecule splits into two active agents. One stops the pain immediately. The other reduces inflammation and accelerates healing. No other topical does both.

Pain relief + healing in a single application
03

12 hours. One application.

The gel creates a slow-release depot at the wound site. Pain relief is continuous for up to 12 hours — covering the entire window where opioids are currently prescribed. The drug never enters the bloodstream.

Eliminates the opioid decision point
2–3×
Faster onset than current market leaders (EMLA, LMX)
0
Systemic absorption — the drug stays at the wound, not in the body
<0.1 ppm
Breast milk transfer — safe for nursing mothers from day one
Clinical Evidence
This isn't a concept. Our chemistry has already been tested in humans. Randomized, placebo-controlled trial run with Mount Sinai Hospital — 42% pain reduction versus placebo, zero serious adverse events — on the gen-1 formulation behind AAI-201. Across 7,000+ patients over seven years: zero serious adverse events.

Validated in Mt. Sinai Hospital Clinical TrialRandomized, placebo-controlled · Gen-1 formulation behind AAI-201 · 46 postpartum women

Neonatal Intensive Care
Vol. 35 No. 1 · Winter 2022
Placebo Group · VAS Pain Score 78 ± 5
Treated Group · VAS Pain Score 35 ± 3
42% pain reduction vs placebo p < 0.001
7,000+
Patients treated
2012–2019
0
Serious adverse
events reported
<0.1 ppm
Breast milk
transfer
12 hr
Single-dose
duration
The AI Platform
No new class of topical pain drug has reached patients in decades. The pipeline is nearly empty — not because the market is small, but because developing topical analgesics is uniquely difficult without clinical data that doesn't exist in public databases. We have that data. AAI-201 is the proof. Now we're building the AI platform designed to turn one drug into a pipeline — and fill a gap the industry has left open for a generation.
The Platform

The pipeline is empty. AI built on real clinical data is how we fill it.

There's a reason no one has built a new topical pain drug in decades. Topical drug development is a different problem than oral drugs. How a molecule penetrates skin, how long it stays local, whether it causes irritation — none of that can be predicted from the standard chemical databases the industry relies on. The data simply doesn't exist in public repositories. That's why the pipeline stays empty. Everyone starts cold.

We don't. We spent seven years treating 7,000+ patients with novel topical pain formulations. Every outcome was documented — what penetrated, what lasted, what was safe, what failed. That process produced AAI-201, a clinically validated drug now entering Phase 2a. But it also produced something no competitor has: the proprietary clinical dataset needed to train an AI platform purpose-built for topical pain drug discovery.

Built today: our data and our architecture. This round produces the first molecule the engine designs, made and tested in the lab. Every candidate molecule is graded against what worked in our own patients — a ranked shortlist of molecules to make and test.

1
AAI-201 — The Proof — Seven years of clinical data from 7,000+ patients produced a validated drug. That same data is the training foundation.
2
The Engine We're Building — AI models trained on AAI-201's clinical dataset, designed to generate new topical pain drug candidates.
3
Pipeline Generation — Each new candidate targets a different pain indication — using the same data advantage that produced AAI-201.
4
The Flywheel — Every new clinical program (starting with AAI-201's Phase 2a) feeds more data back in. More data, better models, better drugs.

Do what AAI-201 did — faster

AAI-201 took seven years of manual iteration. The platform is being built to compress that cycle — using the clinical intelligence AAI-201 generated to design new candidates in months, not years.

From 7 years to months

Predict before the lab

AAI-201 taught us what penetrates skin, how long relief lasts, what causes side effects. Models trained on those real outcomes are designed to predict the same for new molecules — before a single patient is dosed.

AAI-201's data becomes the training set

Catch safety problems early

AAI-201's safety record across 7,000+ patients — zero serious adverse events, <0.1 ppm breast milk transfer — is the real-world safety dataset the platform learns from. Not computational guesses. Real outcomes.

Safety data from real patients

License to pharma partners

Every candidate the platform generates is a licensable asset. AAI-201 goes to Big Pharma. The next candidate gets licensed separately. The platform creates a repeatable revenue model.

AAI-201 is the first. Not the last.

AAI-201 is advancing through Phase 2a toward a Big Pharma exit. That's one drug, one transaction. But the dataset behind it — 7,000 patients, seven years of clinical intelligence — doesn't get sold with the drug. It stays with us. The platform we're building around it is designed to generate the next candidate, and the one after that. Every Phase 2a trial — starting with AAI-201 — feeds new data back into the engine. The acquirer buys one drug. We keep the data and the machine that makes them. That's why this raise funds both: the drug into Phase 2a, and the platform that turns one drug into a franchise.

The Market
Analgesia AI operates at the intersection of two high-growth markets: an $11 billion topical pain relief market that hasn't seen meaningful innovation in decades, and an AI drug discovery market growing at over 30% annually. The drug targets a market where a single product generates $575 million per year. The platform targets a market where companies with no approved drugs carry multi-billion-dollar valuations.
Two massive markets. Two revenue streams. One company at the intersection.
The Drug Market · AAI-201
TAMNon-Opioid Pain · Global
$45B → $70B by 2030
The global shift away from opioids across all pain categories. Growing 7.7% annually.
Grand View Research, 2024
SAMTopical Pain Relief · Global
$11B → $18B by 2034
The specific product category AAI-201 enters. Dominated by generic molecules from the 1940s.
Market.us, 2026
SOMObtainable · 2–3 Assets, Rx + OTC
$1B+
Exparel — one non-opioid product — sold $575M in 2025. Our target spans 2–3 assets across prescription and over-the-counter channels. SOM is a company target.
Pacira SEC filings; company analysis
The Platform Market · AI Engine
TAMAI in Drug Discovery · Global
$3.8B → $15.2B by 2030
The fastest-growing segment in pharmaceutical R&D. Growing over 30% annually.
BCC Research, 2025
SAMAI in Topical & Pain Drug Design
Underserved Niche
Broad-spectrum platforms focus on oral oncology and CNS therapeutics. AI-driven design of topical and transdermal analgesic candidates is an unoccupied niche.
Grand View Research, 2025; company analysis
SOMPlatform Enterprise Value
$1.5B–$4.2B valuation range
Based on current market valuations of comparable AI drug discovery platforms — none of which have proprietary first-party clinical data or a clinical-stage drug asset.
See Company Comparables below

What Single Products Generate in This Space

Exparel (Pacira BioSciences)
$575M/yr
Injectable sustained-release anesthetic. One delivery format. Not topical. No AI platform. Growing 6% YoY.
Pacira SEC Filing, January 2026
Lidoderm (Endo Pharma)
$1B+
Lidocaine patch. Peak annual revenue. Single indication — postherpetic neuralgia. Now generic.
Endo Pharmaceuticals historical filings
Pacira Total Revenue
$726M/yr
Three non-opioid pain products combined. Growing 4% YoY.
Pacira SEC Filing, January 2026

These revenues come from products with narrower mechanisms, fewer indications, and no AI platform generating additional candidates.

AI companies have no patient data. Pain companies have no AI.

Company
Non-Opioid
Local, Not Systemic
Own Patient Data
AI Engine
Vertex / Journavx
— pill
Pacira / Exparel
✓ injected
Lidocaine patches
Recursion ~$1.5B
Insilico ~$4.2B
Analgesia AI
✓ topical
✓ 7,000 patients

AI drug companies without patient data carry valuations of $1.5B–$4.2B. Pain companies without AI generate $575M+ per product. Analgesia AI is the only company with both — raising at $36.1M pre-money.

Why the Window Is Open Now

January 2025

NOPAIN Act

Separate Medicare reimbursement for non-opioid postsurgical therapies in outpatient settings. First structural payer incentive for non-opioid adoption at scale.

CMS Proposed Rule, 2024
January 2025

Journavx (Vertex)

First new analgesic class approved in 20+ years. Signals FDA appetite for non-opioid innovation. Oral, not topical — the topical space remains empty.

FDA; Vertex Pharmaceuticals
Ongoing

125,000 Deaths/Year

Annual opioid overdose deaths worldwide. Regulatory pressure, hospital mandates, and payer incentives to find non-opioid alternatives have never been stronger.

World Health Organization, 2023

The revenue benchmarks in this space speak for themselves: $575 million per year for a single injectable anesthetic. Over $1 billion at peak for a single lidocaine patch. AI drug discovery platforms with no approved drugs and no proprietary clinical data command valuations of $1.5 billion to $4.2 billion. Analgesia AI enters this market with a clinical-stage drug, a published trial, a proprietary first-party dataset, nine patent applications, and an AI platform designed to generate additional candidates — assets that, in comparable companies, have been valued independently.

Invest
One clinical-stage drug. One AI platform being built on data no one else has. Nine patent applications. A $45 billion non-opioid pain market — and a raise of $8.9M at $36.1M pre-money, a valuation that is a fraction of companies with fewer assets.

A clinical-stage drug. A proprietary dataset. An AI platform in development.
Two assets. One window.

Most biotech startups ask you to believe a molecule might work. We're past that. Our chemistry has already been tested in humans — in a randomized, placebo-controlled trial run with Mount Sinai Hospital: 42% pain reduction vs placebo, zero serious adverse events. AAI-201 is the optimized successor — same active chemistry, reformulated for duration and delivery — now entering FDA Phase 2a. Phase 2a is where pharma buys non-opioid pain drugs.

But this isn't a one-drug company. The seven years we spent treating patients generated something just as valuable as the drug itself: a proprietary clinical dataset that doesn't exist anywhere else. No public database has it. No competitor can download it. We're building an AI platform on top of that dataset — designed to generate new pain drug candidates systematically, across multiple indications. AAI-201 is the proof the data works. The platform is how we turn one drug into a pipeline.

That's two independent assets. The drug advances through Phase 2a and exits to Big Pharma. The platform stays, generates the next candidate, and creates a repeatable licensing model. One company, two paths to value — and the dataset underneath both took seven years and 7,000 patients to build. No one starting today can replicate it.

$8.9M
Raise · $36.1M Pre-Money
Companies without our data, without a clinical drug, and without a published trial carry valuations of $1.5B–$4.2B.
$45B
Target Market
Non-opioid pain, global — growing to $70B by 2030. Topical analgesics alone: $11B, dominated by generics from the 1940s.
9
Patent Applications
5 pharma + 4 AI. Protecting the drug and the platform. Two independent IP portfolios. Prosecution-ready.

$8.9M. Three things in 28 months. At the end: human data from Phase 2a, a molecule the engine designed, and all nine patent families filed.

57.5% · $5.1M
Phase 2a and Patents
Runs the next human study of AAI-201 through to its result. Files all nine patent families.
26.5% · $2.4M
The Engine
Takes the AI from architecture to its first molecule, made and tested in the lab.
16.0% · $1.4M
Team and Operations
Core hires, clinical operations, legal and regulatory support across the 28 months.

The opioid crisis created the need. Seven years of clinical work created the data. Our chemistry is proven in humans. Now the engine designs the next molecule. At the end of 28 months: human data, a molecule the engine designed, and nine patent families filed.

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