Particularizing Patent Pleading: Pleading Patent Infringement in a Post-Twombly World

The Supreme Court\u27s recent jurisprudence has reinvigorated the role of pleading in civil litigation. As a result, in order to survive a motion to dismiss, plaintiffs must now include more detailed allegations that demonstrate a plausible entitlement to relief. This article examines how these changes interact with the pleading requirements for patent infringement litigation. In recent years, the number of patent infringement lawsuits has increased dramatically, in part because of lax notice pleading requirements. This patent litigation explosion imposes exorbitant costs on defendants and has a detrimental effect on innovation. As courts begin to apply the new plausibility pleading regime, this article argues that they should seize the opportunity to rein in abusive patent litigation by requiring particularized allegations of infringement. Adopting this regime effectuates Twombly and Iqbal, reduces the number of nuisance-value patent infringement suits, and begins to address the problems that cause the patent system to inhibit, rather than promote, progress in science and the useful arts

Time for an Upgrade: Amending the Federal Rules of Evidence to Address the Challenges of Electronically Stored Information in Civil Litigation

In recent years, electronically stored information (ESI) has begun to play an increasingly important role in civil litigation. Although the e-discovery amendments to the Federal Rules of Civil Procedure in 2006 provided guidelines for the discovery of this information, no accompanying changes were made to the Federal Rules of Evidence to govern the admissibility of this information at trial. This article outlines the vastly different ways courts have addressed this problem in three areas: authentication, hearsay, and the best evidence rule. After discussing the various approaches courts take in these areas, this article proposes specific amendments to the Federal Rules of Evidence that would provide guidance to courts and litigants as to the admissibility of electronically stored information at trial

A Patent Panacea? The Promise of Corbinized Claim Construction

A patent\u27s claims define the scope of a patent-holder\u27s right to exclude others. Because patent infringement actions often hinge on how a court construes claim terms, the interpretative approach that a court uses has a significant effect on the scope ofpatent rights. This article examines claim construction through the lens of contract law. In theory, the Federal Circuit has explicitly rejected the application of contract interpretation principles to claim construction, despite historical acceptance of the patent-contract analogy. In practice, however, the Federal Circuit applies the theory of contract interpretation espoused by Samuel Williston, a theory that focuses on the text of the document itself Unfortunately, this approach has resulted in a claim construction jurisprudence that lacks certainty and divides the judiciary. Accordingly, this article argues that courts should construe patent claims by following the theory of contract interpretation outlined by Williston\u27s rival, Arthur Corbin-a theory that values substance over form. If applied in the patent context, this theory would expand the quality of sources used to interpret a claim and mitigate the problems spawned by the use of a Willistonian approach. In light of these advantages, Corbinized claim construction offers a doctrinal solution to the problems plaguing the Federal Circuit\u27s current claim construction jurisprudence

A Patent Panacea?: The Promise of Corbinized Claim Construction

A patent\u27s claims define the scope of a patent-holder\u27s right to exclude others. Because patent infringement actions often hinge on how a court construes claim terms, the interpretative approach that a court uses has a significant effect on the scope ofpatent rights. This article examines claim construction through the lens of contract law. In theory, the Federal Circuit has explicitly rejected the application of contract interpretation principles to claim construction, despite historical acceptance of the patent-contract analogy. In practice, however, the Federal Circuit applies the theory of contract interpretation espoused by Samuel Williston, a theory that focuses on the text of the document itself Unfortunately, this approach has resulted in a claim construction jurisprudence that lacks certainty and divides the judiciary. Accordingly, this article argues that courts should construe patent claims by following the theory of contract interpretation outlined by Williston\u27s rival, Arthur Corbin-a theory that values substance over form. If applied in the patent context, this theory would expand the quality of sources used to interpret a claim and mitigate the problems spawned by the use of a Willistonian approach. In light of these advantages, Corbinized claim construction offers a doctrinal solution to the problems plaguing the Federal Circuit\u27s current claim construction jurisprudence

The Cost Of Privacy: Riley v. California’s Impact on Cell Phone Searches

Riley v. California is the United States Supreme Court’s first attempt to regulate the searches of cell phones by law enforcement. The 2014 unanimous decision requires a warrant for all cell phone searches incident to arrest absent an emergency. This work summarizes the legal precedent and analyzes the limitations and practical implications of the ruling. General guidelines for members of the criminal justice system at all levels consistent with the Supreme Court’s decision are provided

Dissecting Trait Heterogeneity: a Comparison of Three Clustering Methods Applied to Genotypic Data

Background: Trait heterogeneity, which exists when a trait has been defined with insufficient specificity such that it is actually two or more distinct traits, has been implicated as a confounding factor in traditional statistical genetics of complex hu man disease. In the absence of de tailed phenotypic data collected consistently in combination with genetic data, unsupervised computational methodologies offer the potential for discovering underlying trait heteroge neity. The performance of three such methods – Bayesian Classification, Hyperg raph-Based Clustering, and Fuzzy k -Modes Clustering – appropriate for categorical data were comp ared. Also tested was the ability of these methods to detect trait heterogeneity in the presence of locus heteroge neity and/or gene-gene interaction , which are two other complicating factors in discovering genetic models of complex human disease. To dete rmine the efficacy of applying the Bayesian Classification method to re al data, the reliability of its intern al clustering metr ics at finding good clusterings was evaluated using permutation testing. Results: Bayesian Classifica tion outperformed the other two method s, with the exception that the Fuzzy k -Modes Clustering performed best on the most comp lex genetic model. Bayesian Classificati on achieved excellent recovery for 75% of the da tasets simulated under the simplest genetic model, while it achieved moderate recovery for 56% of datase ts with a sample size of 500 or more (across all simulated models) and for 86% of datasets with 10 or fewer nonfuncti onal loci (across all si mulated models). Neither Hypergraph Clustering nor Fuzzy k -Modes Clustering achieved good or excellent cluster recovery for a majority of datasets even under a re stricted set of conditions. When usin g the average log of class strength as the internal clustering metric, th e false positive rate was controlled very well, at three percent or less for all three significance levels (0. 01, 0.05, 0.10), and the false negative rate was acceptably low (18 percent) for the least stringent sign ificance level of 0.10. Conclusion: Bayesian Classificati on shows promise as an unsuper vised computational method for dissecting trait hetero geneity in genotypic data. Its control of fa lse positive and false negative rates lends confidence to the validity of its results. Further investigation of how differ ent parameter settings may improve the performance of Bayesian Classification, especi ally under more comp lex genetic models, is ongoing

1862-11-13 Jonathan L. Moore of Bucksport requests a position in a hospital

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