Trademark Overview
On Tuesday, January 7, 2025, a trademark application was filed for GX with the United States Patent and Trademark Office. The USPTO has given the GX trademark a serial number of 98942685. The federal status of this trademark filing is NEW APPLICATION - RECORD INITIALIZED NOT ASSIGNED TO EXAMINER as of Tuesday, January 7, 2025. This trademark is owned by Aresnal Biosciences, Inc.. The GX trademark is filed in the Computer & Software Products & Electrical & Scientific Products and Computer & Software Services & Scientific Services categories with the following description:
Downloadable software for modeling and simulating T-cell behavior; downloadable software featuring machine learning algorithms for modeling and simulating T-cell behavior; downloadable software for researching and discovering drug targets; downloadable software featuring machine learning algorithms for researching and discovering drug targets; downloadable software for determining, discovering, and researching diagnostic signatures in patients; downloadable software featuring machine learning algorithms for determining, discovering, and researching diagnostic signatures in patients; downloadable software for determining, discovering, and researching patient stratification strategies; downloadable software featuring machine learning algorithms for determining, discovering, and researching patient stratification strategies
Providing online non-downloadable software for modeling and simulating T-cell behavior; providing online non-downloadable software featuring machine learning algorithms for modeling and simulating T-cell behavior; providing online non-downloadable software for researching and discovering drug targets; providing online non-downloadable software featuring machine learning algorithms for researching and discovering drug targets; providing online non-downloadable software for determining, discovering, and researching diagnostic signatures in patients; providing online non-downloadable software featuring machine learning algorithms for determining, discovering, and researching diagnostic signatures in patients; providing online non-downloadable software for determining, discovering, and researching patient stratification strategies; providing online non-downloadable software featuring machine learning algorithms for determining, discovering, and researching patient stratification strategies