Can AI-Generated Molecules Be “Obvious” Under §103? Rethinking Nonobviousness in Algorithmic Chemistry
As artificial intelligence becomes an increasingly central tool in molecular design, a new question emerges for patent law: can a molecule generated by an AI system be deemed “obvious” under 35 U.S.C. §103? Traditional obviousness doctrine assumes human-driven experimentation guided by known chemical principles. AI-driven molecular generation, however, operates by probabilistic search across immense chemical…
Who Is the Inventor When AI Designs a Molecule? A Legal Analysis of Conception in the Age of Machine Learning
Artificial intelligence is increasingly used to generate candidate drug molecules, proteins, and other biologically active compounds with minimal direct human design. In some cases, machine learning systems propose chemical structures or amino acid sequences that no human explicitly conceived in advance. This raises a fundamental question for patent law: when an AI system designs a…
AI-Designed Proteins as a New Class of Biologic Inventions: Technical Foundations and Legal Implications
Artificial intelligence has recently crossed a threshold in protein science: from predicting protein structure to designing entirely novel proteins with specified functions. Using deep learning models trained on massive protein sequence and structure datasets, researchers can now generate amino acid sequences that fold into predetermined three-dimensional shapes or catalyze desired chemical reactions. This development reframes…
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