Ainnocence Launches Self-Evolving, Multi-Objective AI Drug Discovery Platform


Ainnocence, a worldwide biotech firm on a mission to speed drug discovery through a quick, self-evolving AI drug design platform, made its debut today at the BIO International Convention in 2022.

Ainnocence, which was founded by a diverse group of biomedical scientists and computer scientists, provides small- and large-molecule design platforms that drastically reduce the costs and dangers of drug discovery, bringing the industry closer to addressing some of humanity’s most difficult ailments.

“We want to equip biotechs and pharmas to tackle moonshot cures that have until now been out of reach due to staggering discovery costs and low ROI. Never before have drug discovery teams had a system of such power at their disposal”, “If a science team provides us with just the sequence information of their biological targets, we can screen billions of molecules and compounds in just hours, and in many cases completely bypass high-throughput wet-lab experimentation.”

Lurong Pan, CEO of Ainnocence

Today, Ainnocence is debuting two services that automatically generate highly optimized drug-like molecules within just hours to solve some of the most complex drug discovery challenges:


a de novo antibody and fusion protein engineering engine that performs antibody design and optimization based solely on sequences. Capabilities include protein-protein binding affinity maturation, protein humanization, off-target toxicity prediction, protein stability and post-translational modification prediction.


a de novo small-molecule and PROTAC design engine for multi-objective pharmacological profile optimization. Capabilities include target binding and selectivity optimization, molecule generation, ADME and PK evaluation, and compound off-target prediction.

Ainnocence provides drug design services and pipeline collaborations for small molecules, biologics, and other new modality drugs. InnocentAITM, a self-evolving AI cloud platform that runs natively on AWS and supports numerous drug-design AI modules with unbounded scalability, powers these services. The accuracy of this computational platform is always improving thanks to its intrinsic self-learning skills and an automatically updated data-integration and algorithm-optimization engine.

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