What Analytics Says About Patent Trials
Obtaining a patent is the best way to protect your intellectual property, but sometimes you must defend that patent in court. Lex Machina, a provider of analytics for the legal industry, recently used its big data capabilities to analyze what’s going on at the federal Patent Trial and Appeal Board (PTAB).
The PTAB is an administrative law body of the United States Patent and Trademark Office (USPTO) that decides issues of patentability. The board was created in 2012, and employs more than 100 administrative patent judges.
Lex Machina, which was bought last year by LexisNexis, recently dove into the entire PTAB dataset to pull out any patterns and trends evident across the 2,700 petitions that have been filed with the board since 2012.
Not surprisingly, many petitions never get decided by a judge, according to its report, which was authored by Brian Howard, Lex Machina’s legal data scientist and director of analytics services. The company found 20% of petitions were denied institution (an intermediate step before a judge’s final decision), and another 19% of petitions were settled before the institution decision was reached, the company says.
Only 18% of the time could the petitioner claim victory–resulting in a claim being held unpatentable by a judge– while 5% of claims ended with the patent owner disclaiming claims. Mixed findings were as common under the PTAB as judges upholding all claims, at 3%.
Apple (NASDAQ: APPL) is the top filer of 252 PTAB trials, but interestingly, the tech giant has never appeared as a patent owner, according to Lex Machina’s analysis. Samsung Electronics is the second most active petitioner, having filed a total of 155 PTAB trials, appearing as a patent owner in 11 of them.
East Texas upheld its reputation as the patent-trial capital of the country, accounting for nearly 44% of all PTAB petitions. Courts in California, Delaware, and Illinois also led in terms of volume.
Lex Machina emerged from Stanford University in 2010 and is backed by venture firms and angel investors, including the former CEO of Thomson Reuters, the former general counsel of Apple and Oracle, and the co-founder of Yahoo.
The company, which uses natural language processing and machine learning algorithms to tease patterns out of legal data, says its dataset goes much deeper, down to individual claim results. Clients gain an edge, it says, by knowing exactly which claims have been petitioned, which enables them to connect the claims that matter most to them.