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Disclosed Species Within A Count Establishes Constructive Reduction To Practice

Client Alert | 1 min read | 09.20.07

A Federal Circuit panel in Frazer v. Shlegel (No. 06-1154; August 20, 2007) reverses the Board of Patent Appeals and Interferences award of priority and remands the case to the U.S. Patent and Trademark Office. The Board held that Frazer was not entitled to the benefit of an early Australian application because the disclosure “did not provide a described and enabled anticipation under 35 U.S.C. § 102(g) of the subject matter of the count.” The Federal Circuit reverses, finding that Frazer is entitled to the priority date of the Australian patent application. In particular, the Federal Circuit determines that “the Australian application contained complete details of the method that is the subject of the interference count, and depicts the [virus] particle of the count with full disclosure of how to produce it.” As such, the panel concludes that the Australian application’s “description of the procedures used, and the successful production of the virus-like particles there achieved and reported, disclose and enable a species within the count.” Thus, the Board erred in ruling that Frazer’s Australian application did not prove conception of a species within the count. Frazer’s Australian application was thus a constructive reduction to practice of the invention and Frazer is entitled to the priority benefit of the Australian filing date.

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Client Alert | 3 min read | 08.03.26

New Jersey Takes Aim at Algorithmic and Surveillance Pricing: What Landlords and Retailers Need to Know About the FAIR Act and the Fair Price Protection Act

On July 20, 2026, New Jersey Governor Mikie Sherrill signed the Forbidding the Algorithmic Inflation of Rent (FAIR) Act into law, making New Jersey the fourth state to regulate algorithmic rent-setting practices. Three days later, on July 23, 2026, Governor Sherrill signed the Fair Price Protection Act, which targets “surveillance pricing”—the practice of using or collecting personal data about a user and using an algorithm or artificial intelligence to charge different consumers different prices for the same products. Together, these laws represent a significant expansion of New Jersey's consumer protection framework in the algorithmic pricing context....