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NEW • AUG 2026
167M PARAMS +0.15 AUC vs ESM2 PROTEINGYM SOTA
PRESS RELEASE August 2026 • bioRxiv Preprint

AINN-P1: Small Model, Big Intelligence

A 167M-parameter sequence-first protein foundation model that leads ProteinGym on stability and generalizes to unseen antibody programs — outperforming the 650M ESM2 by 0.15 AUC on new programs with 3.9× fewer parameters, and beating a 100B-parameter model on stability by 39%.

LP

Dr. Lurong Pan

Founder & CEO, Ainnocence

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SENTINUSAI® • JUL 2026
91.4% SUCCESS 28 PROGRAMS TO LICENSE
PRESS RELEASE July 10, 2026

Ainnocence Reports 91.4% Program Success Rate Across 58 Antibody Affinity Maturation Campaigns

Structure-free AI platform delivers picomolar leads while cutting wet-lab validation to 20–50 samples per round. Ainnocence opens a 28-program biologics pipeline — antibody, bispecific and ADC assets across oncology, immunology and metabolic indications — to licensing and partnering.

75
Programs
53%
De Novo Hits
28
Sub-nM
10,000×
Cheaper Compute
View SentinusAI®
WSJ
Dec 2022 • Press Coverage

How AI That Powers Chatbots and Search Queries Could Discover New Drugs

Dr. Lurong Pan on how NLP-style sequence modeling — the same tech behind ChatGPT — can revolutionize drug discovery.

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How sequence-based AI achieves whole genome screening for billions of candidates in hours

The platform has been applied across 60+ therapeutic programs, including antibodies, small molecules, cell therapies, siRNA, and synthetic biology applications.

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NatmolAI™: Computational Expansion and Optimization of Natural-Product Chemical Space

Natural molecules remain a foundational source of bioactive compounds, yet their discovery and optimization are constrained by scarcity and structural complexity.

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Beauty Engineered: Ainnocence Launches CosmeticAI™ for AI-Driven Innovation in Skincare

CosmeticAI™ shifts early-stage discovery from experimental screening to in silico design, generating large populations of candidate molecules.

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AI Meets the Formula: Predictive Intelligence Redefines Chemical Design and Manufacturing

Using a formula-centered knowledge graph combined with process-level digital twin simulations, FormulaAI™ predicts formulation stability and compatibility.

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From Code to Cure: Accelerating Oligonucleotide Design with AI

Oligonucleotide engineering has traditionally been slowed by challenges in sequence selection, immunogenicity, durability, and delivery compatibility.

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Ainnocence Announces AI Platform for Material Performance Prediction

Material AI operates on the same computational backbone powering Ainnocence's platforms in small molecules, biologics and RNA therapeutics.

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