Korean Patent Attorneys Association Officially Launches Patent Grading System 'AxisValue'

AxisValue logo. Provided by the Korean Patent Attorneys Association

[Asia Economy (Daejeon) Reporter Jeong Il-woong] The Korean Patent Attorneys Association announced that the patent grading evaluation system ‘AxisValue’ will be officially launched on the 7th.

AxisValue provides objective results of qualitative evaluations by involving many patent attorneys who are intellectual property experts.

This system is significant in that it reflects the rights and protection strength of individual patents, which were difficult to capture in existing quantitative evaluation systems.

In particular, the adoption of the ‘Delphi method’ to ensure the reliability of the evaluation is considered a strength of AxisValue.

The Delphi method was first developed in the 1950s at the RAND (Research and Development) Corporation in the United States as a verification method to objectify experts’ qualitative evaluations and is still widely used today.

The evaluation results through AxisValue are expressed in PA grades from 1 to 10, with PA grade 1 being the most excellent patent.

Prior to the official launch, a pilot operation of AxisValue was conducted in March, involving 446 patent attorneys who evaluated 384 patents from 19 domestic public research institutes.

Despite evaluators individually grading without knowing the scores given by other evaluators, the pilot operation produced highly consistent results, confirming the system’s stability and reliability.

In the pilot evaluation, the average PA grade of all 384 patents was 4.63, and among the 19 public research institutes, seven institutions including the Korea Research Institute of Bioscience and Biotechnology received grades above the average PA grade.

Hong Jang-won, president of the Patent Attorneys Association, said, “AxisValue is a system in which patent attorneys directly participate in the evaluation process, and unlike existing qualitative evaluations, it can be used as basic data necessary for intellectual property finance and commercialization, so it is expected to greatly contribute to the utilization of intellectual property in the future.”

This content was produced with the assistance of AI translation services.