Decoding Patentable Subject Matter

Patently-O Patent Law Journal 1, 2018

Santa Clara Univ. Legal Studies Research Paper

10 Pages Posted: 22 Oct 2018

See all articles by Colleen V. Chien

Colleen V. Chien

Santa Clara University - School of Law; Stanford Computational Policy Lab

Jiun Ying Wu

Santa Clara University

Date Written: October 16, 2018

Abstract

The Supreme Court’s patentable subject matter jurisprudence from 2011 to 2014 has raised significant policy concerns within the patent community. Prominent groups within the IP community and academia, and commentators to the 2017 USPTO Patentable Subject Matter report have called for an overhaul of the Supreme Court’s “two-step test.” Based on an analysis of 4.4 million office actions mailed from 2008 through mid-July 2017 covering 2.2 million unique patent applications, this article uses a novel technology identification strategy and a differences-in-differences approach to document a spike in 101 rejections among select medical diagnostics and software/business method applications following the Alice and Mayo decisions. Within impacted classes of TC3600 (“36BM”), the 101 rejection rate grew from 25% to 81% in the month after the Alice decision, and has remained above 75% almost every month through the last month of available data (2/2017); among abandoned applications, the prevalence of 101 rejection subject matter rejections in the last office action was around 85%. Among medical diagnostic (“MedDx”) applications, the 101 rejection rate grew from 7% to 32% in the month after the Mayo decision and continued to climb to a high of 64% and to 78% among final office actions just prior to abandonment. In the month of the last available data (from early 2017), the prevalence of subject matter 101 rejections among all office actions in applications in this field was 52% and among office actions before abandonment, was 62%. However outside of impacted areas, the footprint of 101 remained small, appearing in under 15% of all office actions. A subsequent piece will consider additional data and implications for policy.

This article is the first in a series of pieces appearing in Patently-O based on insights gleaned from the release of the treasure trove of open patent data starting the USPTO from 2012.

Keywords: patents, patentable subject matter, empirical legal studies

JEL Classification: K20, L51, O31, O34

Suggested Citation

Chien, Colleen V. and Wu, Jiun Ying, Decoding Patentable Subject Matter (October 16, 2018). Patently-O Patent Law Journal 1, 2018; Santa Clara Univ. Legal Studies Research Paper. Available at SSRN: https://ssrn.com/abstract=3267742 or http://dx.doi.org/10.2139/ssrn.3267742

Colleen V. Chien (Contact Author)

Santa Clara University - School of Law ( email )

500 El Camino Real
Santa Clara, CA 95053
United States
408-554-4534 (Phone)
408-554-4426 (Fax)

Stanford Computational Policy Lab ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

HOME PAGE: http://https://sites.google.com/view/colleenchien/

Jiun Ying Wu

Santa Clara University ( email )

500 El Camino Real
Santa Clara, CA 95053
United States

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