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Professionals 25 results
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Practice Area
Product Liability & Mass Torts
Major multinational companies trust Winston to defend their products and reputations in high-profile, high-stakes product liability and mass tort claims. Our Product Liability & Mass Torts Practice is one of the industry’s most seasoned, with a deep bench of experienced lawyers and a unique combination of extensive trial experience and expansive technical knowledge.
Practice Area
Addressing a crisis in today’s climate requires both swift action and careful consideration of all potential risks. Winston & Strawn is a trusted business adviser to clients facing complex, fast-moving, high-profile crises.
Practice Area
Environmental Litigation & Enforcement
With today’s rapidly evolving rules of engagement, paired with the often contentious nature of environmental disputes, clients rely on Winston for our practical experience and substantive knowledge of the broad-ranging issues involved in environmental litigation, enforcement, and investigations.
Experience 9 results
Experience
|March 16, 2026
Winston & Strawn LLP Paris advised La Phocéenne de Cosmétique in connection with the acquisition of Laboratoires de Biarritz.
Experience
|July 8, 2024
Winston assists Milexia in Acquiring Cabcongroup
Winston has advised Milexia Group, a European leader in the sale of high-tech components, systems, and scientific instruments, with branches and warehouses in France, Germany, Italy, Spain, and the United Kingdom, in the acquisition of the Danish group Cabcon, which specializes in the distribution of electrical components. With this strategic acquisition, Milexia continues to expand its presence and service offerings in Europe and Asia, further reinforcing its commitment to providing high-quality, reliable, and efficient technological products and supply chain solutions across various sectors.
Experience
|January 16, 2024
Winston & Strawn represented The Honey Pot Company Holdings, LLC (“The Honey Pot Co.”), a leading better-for-you feminine care brand in connection with the acquisition of a controlling stake in the business by Compass Diversified (NYSE: CODI) ("Compass”). Compass and The Honey Pot entered into a definitive agreement for an enterprise value of $380 million (excluding working capital and certain other adjustments upon closing). The Honey Pot Co. will continue to be led by its current leadership team and existing owners and management will retain a significant minority stake in The Honey Pot Co.
Insights & News 148 results
Product Liability & Mass Torts Digest
|April 3, 2026
|8 Min Read
A Recipe for Exclusion: Why the Baby Food MDL Experts Failed Under Daubert
In a high-stakes decision on expert exclusion authored late last month, the District Court for the Northern District of California granted defendants’ motion to exclude plaintiffs’ general causation expert witnesses in In re Baby Food Products Liability Litigation—a consolidated mass tort of over 100 pending cases regarding the alleged presence of toxic heavy metals in baby food.
Product Liability & Mass Torts Digest
|December 9, 2025
|3 Min Read
From Credibility to Admissibility: Reblending the Expert Playbook Under Rule 702
The recent decision in Mendoza v. SharkNinja Operating, LLC by the District of Colorado offers a practical illustration of how federal courts are applying the heightened reliability standard under the 2023 amendments to Rule 702.
In the Media
|September 23, 2025
|2 Min Read
Kathi Vidal Discusses Gender Gap in Patents with MLex
Winston & Strawn partner Kathi Vidal was featured in a MLex article where she discussed the gender gap in patents, outreach efforts in the U.S. Patent and Trademark Office under her leadership as the former Director, and how the office can support women inventors. A 2022 study from the USPTO showed that office policy can help close the gap between men and women in the US patent system. The paper studied the effectiveness of the Pro Se Pilot Examination Unit (PSPEU), which provides additional communication and assistance to inventors attempting to prosecute a patent without representation.
Other Results 10 results
Site Content
In the product liability context, general causation is the legal and scientific determination of whether the product in question has the inherent capability to cause the alleged injury under certain circumstances. Establishment of general causation is a critical aspect of a plaintiff’s case, and typically requires scientific evidence, such as epidemiology or toxicology, and expert testimony to establish a causal connection between the product’s design, manufacturing, or warnings and the injury or injuries at issue. As contrasted to specific causation, the focus in a general causation inquiry is on whether the product or exposure, as a general matter, can cause the type of injury claimed by the plaintiff. A general causation inquiry does not assess any facts unique to a particular plaintiff.
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Specific causation is the legal and scientific determination of whether the product in question was the direct cause of a plaintiff's specific injury. While general causation inquires whether a broader connection exists between a product and a type of harm, a specific causation assessment focuses on the unique circumstances surrounding a particular plaintiff's case. It typically requires expert testimony demonstrating that the alleged defect or issue in the product was responsible for the specific injuries suffered by the plaintiff. Alternative explanations for the plaintiff’s specific injuries must also be ruled out—typically via a differential etiology—for specific causation to be established.
Site Content
Generative AI tools can create new content, such as text, computer code, images, audio, sound, and video, in response to a user’s prompt, often in the form of a short written description of the desired output. Generative AI tools are based on machine learning, trained using enormous amounts of data.[1] Generative AI tools are built on a system of inputs and outputs. First, the tool goes through a machine learning period whereby it is trained to generate predictive models and creative outputs through a large data set, often varied and diverse but tailored to the goal of the tool (i.e., customer service, generating scientific or marketing models, etc.). For in-house tools, this can be done with the company’s own data; for larger tools such as ChatGPT, this is done with the creator’s data set.[2] Once the tool has been trained, the individual user “inputs” a short prompt for the tool to synthesize and produce an “output.” Inputs are often retained on the servers controlled by the company that supports the tool, for monitoring of the tool’s performance and, in some cases, continued learning. The “outputs” are created by combining the machine learning during the training period with the inputs to produce an output.[3]