Misbranded Blog

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Misbranded is Patterson Belknap’s blog covering false advertising litigation—both consumer class actions and competitor suits—with a particular focus on FDA-regulated products (foods/beverages, pharmaceuticals, cosmetics, and dietary supplements).  Writing from the industry perspective, we provide timely updates on important cases, surveys of litigation trends, and in-depth analyses of “hot” legal issues.  Our firm pioneered the modern practice of false advertising law more than 40 years ago, bringing the first competitor suits under the Lanham Act.  In the decades since, we have continued to practice at the cutting edge, handling many of the field’s most groundbreaking cases on behalf of the nation’s best-known businesses.  Today, led by Steven A. Zalesin, our team advocates creatively, strategically, and efficiently on behalf of our clients at all phases of litigation, from pre-complaint demands to Supreme Court appeals.

Two Big Reasons Courts Dismiss Suits Alleging the Presence of Harmful Ingredients

“Contains detectable levels of the weed-killer chemical glyphosate.”

“Contains limonene, which causes kidney toxicity and tumors, and linalool, a cockroach insecticide.”

“Contains a potent biocide and endocrine disruptor, with detrimental health effects that are still becoming known.”

These are the sorts of headline-grabbing allegations the plaintiffs’ bar has recently relied upon in claiming that products advertised or positioned as “natural” are deceptively marketed.  At first blush, the presence of allegedly dangerous ingredients in foods, cosmetics, and other consumer products might seem like the basis of a strong false advertising case—especially when those substances are undisclosed.  How could a company so deceive the public by promising a “good-for-you” product that contains such “bad” ingredients?

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“Lack of Substantiation” Claims: A Substantively Lacking Liability Theory

As astronomer Carl Sagan famously said, “absence of evidence is not evidence of absence.”  Plaintiffs have not gotten the message.  They often allege that a defendant’s marketing or labeling statements are false and misleading on the sole basis that there is purportedly no evidence (or insufficient evidence) proving their truth.  These so-called “lack of substantiation” claims are easy to plead because a plaintiff does not need to conduct an investigation to identify evidence that the challenged statement is false.  Rather, she alleges only an absence of supporting evidence for the statement—and generally, in a conclusory manner.

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Class Damages Models After Comcast: Rigorous Proof or Expert’s Promise?

In Comcast v. Behrend, 569 U.S. 27 (2013), the Supreme Court held that a plaintiff cannot obtain class certification with an inadequate damages model.  In the years since, courts have diverged over how much a plaintiff must do to satisfy this requirement.  Often, plaintiffs seek class certification with nothing more than a skeletal proposal to develop and perform an analysis at some future point, using information they do not—and might never—possess.  While some courts have found such adumbrative “models” sufficient at the class certification stage, the better decisions require more.  As Comcast recognizes, Rule 23 “does not set forth a mere pleading standard.”  Rather, a plaintiff “must affirmatively demonstrate” through “evidentiary proof” that damages are measurable on a class-wide basis through a common methodology.  Faithful application of that principle obligates plaintiffs and their experts to offer a detailed methodology that is tailored to the facts of the case, and to show that any data that the model requires in fact exists and can be obtained.

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Conjoint Analysis: No Silver Bullet for Calculating Class-Wide Damages

Over the last few years, “conjoint analysis” has become the methodology du jour for false advertising plaintiffs seeking to demonstrate they can calculate class-wide damages.  Conjoint analysis is so named because it is used to study the joint effects of multiple product attributes on consumers’ choices.  At bottom, conjoint analysis uses survey data to measure the strength of consumers’ preferences for particular product features.  Or, put differently, it tries to isolate how much people care about an individual product attribute in a multi-feature product (in a more scientific manner than just asking them directly).

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