Now more than ever, technology is influencing the way we do business, communicate, move through and around the world, access and manage our homes, receive and administer healthcare, make purchases, secure information, and protect our most valuable property. Morrison Foerster keeps pace with this rapidly evolving landscape across our internationally recognized corporate, finance, intellectual property, and litigation practices. MoFo Tech brings together our insights relating to fields such as blockchain and distributed ledger, cloud and as-a-service technologies, driverless cars, drones, fintech, computer hardware and software, the Internet of Things, semiconductors, and telecommunications. The MoFo Tech blog offers real-time, in-depth analyses of the trends and complex issues shaping the global technology industry.<h2>ABOUT MORRISON FOERSTER</h2>Morrison Foerster is a leading global law firm that transforms complexity into advantage for its clients. Our clients include some of the largest financial institutions, banks, consulting and accounting firms, and Fortune 100, technology, and life sciences companies. Highlighting the firm’s commitment to client service, leadership in market-changing deals and impact litigation, and values-based culture, Morrison Foerster has been repeatedly recognized as one of the top 10 firms on The American Lawyer’s A-List. Year after year, the firm receives significant recognition from Chambers and The Legal 500 across their various guides, including Global, USA, Asia‑Pacific, Europe, UK, Latin America, and FinTech Legal. Our lawyers passionately care about delivering legal excellence while living our values. Morrison Foerster has a long-standing commitment to creating a culture that respects and celebrates differences, while providing an inclusive environment. The firm has achieved Mansfield Certification Plus since 2018 as a result of successfully reaching at least 30 percent women, communities of color, and LGBTQ+ lawyer representation in a notable number of current leadership roles and committees. The firm also has a long history of commitment to the community and society through providing pro bono legal services, including litigating for civil rights and civil liberties, improving public education and fostering the wellbeing of children, advocating for veterans, promoting international human rights, enforcing the right to asylum, and safeguarding the environment.

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Scott Llewellyn’s practice focuses on complex litigation in federal and state courts around the country, with an emphasis on patent and trade secret disputes. Over the past decade, he has worked on some of the most significant, high–profile IP cases involving technology for televisions, smartphones, and self–driving cars, relying on 40 years of experience with computer hardware and software. Scott also has significant experience with business divorce cases before courts and arbitrators, involving a mix of trade secret, patent, tort, and contract claims relating to technology development and implementation.Scott also has successfully tried general commercial arbitration and agency matters, briefed and argued various appeals in federal appellate court, and tried more than 20 cases for the Denver City Attorney’s office, most of them jury trials.Scott also has an active pro bono practice, having worked on a variety of criminal and immigration appeals, and having represented Colorado criminal defense and mental health organizations in high–profile suits against the state of Colorado for violations of the constitutional rights of defendants.At MoFo, Scott serves on the board of the Morrison & Foerster Foundation. In the broader legal community, he serves on the boards of the Colorado Lawyers Committee and Drop in the Bucket (a charity that builds wells and sanitation systems in sub–Saharan Africa).After law school, Scott clerked for the Honorable Clarence A. Brimmer, District of Wyoming, and the Honorable Diarmuid F. O’Scannlain, Ninth Circuit. He was also previously an adjunct professor at the Georgetown University Law Center.

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Partner

Scott Llewellyn’s practice involves complex litigation before state and federal courts around the country, with an emphasis on patent and trade secret disputes for high-tech companies, to which he brings more than 35 years of experience with computer hardware and software, in particular relating to the processing and transmission of audio, video, voice, and other types of data. Mr. Llewellyn has also tried commercial arbitration and agency matters; briefed and argued various appeals in federal appellate court; and tried more than 20 cases for the Denver city attorney’s office, most of them jury trials.

Scott F. Llewellyn

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AI Transparency in Healthcare: Navigating a Changing Regulatory Landscape

Recentive: Federal Circuit’s Patent-Eligibility Guideposts for Machine-Learning Inventions

Japan’s Approach to AI Regulation in 2025

Federal Circuit Clarifies Requirements for Prior Art Under Pre-AIA 35 U.S.C. § 102(e)

AI Agent as a Service in Medtech - Key Considerations for Commercial Contracts

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Transparency of artificial intelligence (AI) systems in healthcare is quickly becoming a central concern for regulators due to potential impacts on patient safety, healthcare quality, bias mitigation, and public trust. To address these challenges, the Office of the National Coordinator for Health Information Technology (ONC) introduced the Health Data, Technology, and Interoperability: Certification Program Updates, Algorithm Transparency, and Information Sharing (HTI-1) rule, establishing comprehensive transparency requirements for AI-based decision support intervention technology (DSI). Additionally, the Food and Drug Administration (FDA) has advanced transparency recommendations for AI models in medical product submissions, signaling a broader regulatory alignment toward robust AI accountability standards. This article reviews the impact of these regulatory developments on the use of AI in healthcare and compares the requirements to those applicable under the EU AI Act.Read the <a href="https://lifesciences.mofo.com/topics/ai-transparency-in-healthcare-navigating-a-changing-regulatory-landscape" target="_blank">full blog post</a>.

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Marijn Storm specializes on the intersection of law and technology, with a focus on cutting-edge technologies, such as (generative) artificial intelligence (AI) and large language models, ethical tech, and biometrics. 

Marijn Storm

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Brigid is a food, drug, and medical device lawyer who counsels life sciences companies on a wide range of U.S. Food & Drug Administration pre- and post-market regulatory issues.

Brigid DeCoursey Bondoc

Brigid is a food, drug, and medical device lawyer who counsels life sciences companies on a wide range of U.S. Food & Drug Administration pre- and post-market regulatory issues.

Brigid Bondoc

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Associate

Elena Catherine Klonoski

Elena Klonoski

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AI Transparency in Healthcare: Navigating a Changing Regulatory Landscape

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In one of the first cases from the Federal Circuit addressing patent eligibility for machine-learning (ML) inventions, the court ruled that applying “generic” ML techniques to a new data environment to automate a task previously performed by humans—in this case, “event scheduling”—is an “abstract idea” and thus not patent-eligible, even if the claim includes superficial limitations related to training and improving an ML model. See Recentive Analytics, Inc. v. Fox Corp., No. 2023‑2437, slip op. at 18 (Fed. Cir. Apr. 18, 2025).However, patent protection remains available when applicants disclose and claim an ML invention in sufficient detail, demonstrating that the new ML technique provides a technological advantage. For instance, the Recentive panel emphasized that there remains a path to patent protection for ML-based inventions, noting that:<blockquote>Machine learning is a burgeoning and increasingly important field and may lead to patent-eligible improvements in technology. Today, we hold only that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101. Recentive, No. 2023‑2437, slip op. at 18.</blockquote>Overview of Recentive Analytics, Inc. v. Fox Corp.A representative claim from U.S. Patent No. 11,386,367 that was at issue in Recentive recited iteratively training a machine-learning model to identify relationships between different event parameters and desired outcomes for the events, generating a schedule for a future series of events based on user-defined event parameters and desired outcomes, and updating the generated schedule based on real-time changes to event parameters. While the claim includes several “machine-learning” steps, there is no claim element that informs the reader of any technological improvement beyond conventional ML-techniques; the application of ML in the claims boils down to automation of a process previously performed by a human.Recentive argued that its claims are patent-eligible because they involve a “unique application of machine learning to generate customized algorithms, based on training the machine learning model, that can then be used to automatically create . . . event schedules that are updated in real-time,” asserting that it had “worked out how to make the algorithms function dynamically, so the maps and schedules are automatically customizable and updated with real-time data.” Recentive, No. 2023‑2437, slip op. at 8, 11–15. However, as conceded by Recentive, iterative training using updated data is “incident to the very nature of machine learning” and “do[es] not . . . mak[e] machine learning better.” Recentive, No. 2023‑2437, slip op. at 8–12. Because the court viewed the purported advance as nothing more than routine ML behavior applied in a new business context, the court held the claims could not clear § 101 and were thus patent-ineligible.In sum, Recentive tells patent applicants that:<ul><li>Iterative training and real‑time updates are not a technical improvement.</li><li>Field‑of‑use limitations (i.e., using ML in a new data environment) can’t rescue an abstract idea.</li><li>Increased speed and efficiency relative to human-performance of a task are not sufficient for eligibility.</li></ul>Recentive serves as yet another reminder for patent practitioners and applicants to ensure that their patent applications include robust disclosure of how a claimed invention provides a technical solution to a technical problem. After Recentive, AI inventors still have a clear runway to eligibility: claim either (i) innovations to the ML model itself (e.g., via a novel training process that improves the model for a given task, via a novel data preprocessing technique) or (ii) a concrete technical use of the model’s output—and ideally claim both. By anchoring claims in training specifics or downstream control actions, and by disclosing measurable performance gains, applicants can transform generic‑sounding AI “ideas” into patent-eligible claims that withstand § 101 scrutiny.Practitioner & Applicant Takeaways<ol><li>Explain how the model is trained and why those training steps matter. Training details can be critical to patent eligibility. In Recentive, the claims at issue broadly recited “iteratively training” the models “wherein such iterative training improves the accuracy of the ML model.” The Federal Circuit balked at this surface-level claiming. Applicants should ensure any training process is described in detail in the specification. In view of Recentive, applicants should also consider including key training steps in the independent claim.</li><li>Tie the ML model’s output to a technical action. A technical action might be one that controls or changes a physical or software process, such as dropping malicious packets, adjusting electromagnetic emissions, modulating drug‑delivery pumps, etc. This is particularly important when the ML model being claims is a generic or off-the-shelf model. In such cases, the improvement is not to the ML model itself but can be imparted by the downstream practical application of the model’s output.</li><li>Document technical performance improvements. Whenever feasible, ML-directed patent applications should include data showing how the model being claimed does, in fact, provide a technical improvement over the current state of the art. For instance, if the model provides improved image-enhancement abilities, compare the claimed model’s performance with performance of state-of-the-art models and include comparison data in the specification. As noted above, automating a manual process previously performed by humans is not enough; there must be a technological improvement, such as an improvement over existing ML techniques, other software, etc.</li><li>Describe how your ML model/architecture is unique and/or “improved.” The Federal Circuit emphasized that Recentive’s patents do not claim a specific method for “improving the mathematical algorithm or making machine learning better.” Applicants hoping to patent novel models/architectures that improve machine learning should ensure that their applications describe the model/architecture and such improvements in detail.</li></ol>

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Jon Bockman is the head of the firm’s Technology Patent Practice. In this capacity, he leads the firm’s prominent group of patent practitioners with degrees in electrical engineering, mechanical engineering, computer science, computer engineering, chemical engineering, biomedical engineering and physics. 

Jonathan Bockman

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Jeff focuses his practice on domestic and international patent preparation, prosecution, and counseling.

Jeffrey Gerard Young

Jeffrey Young

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Of Counsel

Anna Yuan’s practice focuses on patent prosecution, IP due diligence, post-grant proceedings, and IP litigation support. 

Anna Yuan

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Josh Crawford's practice focuses on domestic patent prosecution, international patent portfolio management, patent infringement and validity determinations, inter partes review proceedings, and IP lit

Joshua A. Crawford

Joshua Crawford

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Briana’s practice focuses on patent preparation, prosecution, and counseling in the areas of biotechnology, pharmaceuticals, and artificial intelligence.

Briana Erin Mittleman Ph.D.

Briana Mittleman

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California Privacy Rights Act of 2020 Qualifies for November Ballot

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Following Shigeru Ishiba’s appointment as Prime Minister on October 1, 2024, Japan has been charting a cautious but innovation-friendly AI regulation strategy, culminating in a public announcement by the Prime Minister himself on March 3, 2025, expressly favoring a regulatory framework that “promotes innovation” and also “addresses risks.” This is in contrast to some indications in early 2024 where Japan appeared poised to introduce comprehensive, AI-specific regulations in step with moves by the EU and the United States. Consistent with this strategy, Japan’s legislative and regulatory bodies have sought to rely on technologically neutral, sector-specific laws and voluntary industry guidelines, rather than sweeping and restrictive statutes. Their approach seeks to balance fostering innovation with mitigating risks, avoiding excessive or new regulations that could stifle AI development, while addressing societal/security concerns by regulating AI under existing legal frameworks (for privacy, safety, etc.).<ul><li>Regulatory Framework and Legislative Measures In late February 2025, Japan’s Cabinet approved a new AI bill (titled “The Act on the Promotion of Research, Development, and Utilization of Artificial Intelligence-Related Technologies”) that aims at supporting AI research and deployment, and strengthening risk management. Notably, the bill avoids imposing strict new rules or penalties on AI developers. While it generally obligates companies to cooperate with government oversight and to correct any AI-driven infringements on people’s rights, it lacks any material penalty provisions for failure to comply. To coordinate Japan’s AI strategy, the legislation also establishes a high-level AI strategy headquarters led by the Prime Minister, uniting all Cabinet ministers to oversee AI policy implementation and risk response. This new body is expected to monitor emerging AI risks and exercise the authority to request cooperation from relevant agencies and private companies, while continuing to emphasize a supportive regulatory environment overall.</li></ul><ul><li>Cabinet Office Interim Report (February 4, 2025) Japan’s new course on AI regulation was crystallized in an interim report released on February 4, 2025, by the Cabinet Office’s AI Strategy Council and its AI Policy Study Group, which are tasked with proposing key recommendations for Japan’s AI regulatory framework. By emphasizing the balance between innovation and risk, the report clarifies that AI policies must promote innovation while addressing risks and acknowledges that over-regulation could impede AI’s benefits. Accordingly, the report states that Japan’s AI policy should rely on existing laws, sector-specific regulations, and “soft law” guidelines as much as possible and only introduce new regulations where truly necessary (i.e., where voluntary measures by businesses are insufficient). International cooperation and AI safety are prominently featured in the Cabinet Office’s recommendations. The report notes that global discussions (through the G7 Hiroshima AI Process, OECD, etc.) are actively shaping AI regulation and urges Japan to align domestic AI measures with internationally accepted principles and frameworks, both to facilitate Japanese companies expanding abroad and to allow Japanese citizens access to AI services worldwide. On AI safety, the report suggests that the government should establish guidelines (drawing on other countries’ practices and rules) to encourage responsible AI development. This includes voluntarily compliance by businesses with best practices, surveys to understand how companies are managing AI risks, and supporting companies (or intervening under existing laws) based on those findings. It also contemplates (1) the government’s introduction of AI safety evaluations or third-party certification systems to bolster public trust, and (2) in case of serious AI-caused accidents, the government’s collecting of information, alerting the public and developers, and taking steps to prevent recurrences. All of these measures hinge on cooperation with private companies. Thus, legal mechanisms to mandate information sharing and incident reporting from AI operators (both domestic and foreign) are suggested in the report as necessary backstops, but are not strictly mandated.</li></ul><ul><li>Financial Services Agency (FSA) AI Discussion Paper (March 2025) In the financial sector, Japanese regulators are similarly seeking a “balanced approach” to regulating AI. In March 2025, the FSA published a discussion paper (titled “Preliminary Discussion Points for Promoting the Sound Utilization of AI in the Financial Sector”) that calls on banks and fintech firms to address the potential of AI responsibly and proactively. The FSA highlights that AI offers significant opportunities for the sector, ranging from automating customer service chatbots to streamlining back-office operations and providing data-driven insights for decision making. The FSA also urges caution (especially regarding generative AI) and flags circumstances where AI could be misused: financial fraud, money laundering, or the spread of misinformation in the financial markets. Per these concerns, the FSA hinted that some regulatory measures may be advisable, including developing sector-specific standards for AI model validation, transparency requirements for AI-driven decisions, and oversight to ensure companies’ compliance with existing laws (e.g., on consumer protection and cybersecurity). The FSA paper calls for a “balanced approach” that neither hinders innovation nor ignores risk, and shows the FSA’s willingness to listen and adapt by seeking input on topics like best practices for AI governance, risk management, and areas where further discussion between the agency and companies is needed.</li></ul>Japan is charting a deliberately moderate course on AI regulation, by prioritizing innovation and international alignment while using existing legal frameworks to manage emerging risks. This approach reflects its administration’s strategic intent to foster AI growth without compromising public trust, safety, or regulatory accountability.For further insights into regulatory developments, explore our <a href="https://www.mofo.com/artificial-intelligence" target="_blank">AI Legislative Map and Resource Center. </a> This comprehensive tool provides detailed information on AI-related laws, regulations, and trends worldwide, helping you stay informed on the latest legal frameworks and analyses.

SoftBank and HAPSMobile’s renegotiation of the joint venture with AeroVironment, Inc.

A global software company’s joint venture to commence operations in Japan

Mitsubishi UFJ Financial Group’s US$706 million investment in Grab Holdings Inc.

Mitsubishi Heavy Industries’ US$550 million carve-out acquisition

SoftBank Group’s US$9.6 billion investment in Xiaoju Kuaizhi Inc.

Alibaba Group’s acquisition of an equity interest in Ant Financial.

Toshiba’s divestiture of its legacy TV business to Hisense Electric Co., Ltd.

A global technology consulting firm’s software licensing and open source issues

Softbank’s US$1 billion investment in OneWeb

Kaken Pharmaceutical’s various development and commercialization partnerships

SoftBank’s IP and commercial issues

Otsuka’s development and commercialization agreement

TDK’s joint venture with Qualcomm

Splunk’s acquisition of Caspida, Inc.

AccuWeather’s joint venture with Huafeng Media Group

Yahoo! Japan’s partnerships with various advertising technology service providers

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Seth Graham is a partner in Morrison & Foerster’s Technology Transactions Group and advises clients on a wide range of transactional matters involving technology and intellectual property, including licensing arrangements, technology transfers, outsourcing transactions, development agreements, and other commercial and services arrangements.

Seth M. Graham

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Evan Kim is an associate in the Technology Transactions Group of Morrison & Foerster’s Tokyo office.

Evan Kim

Evan Y. Kim

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Knowing what qualifies as prior art is a core requirement of patent practitioners—whether in life sciences, in the technology sectors or in post-grant proceedings.  It is important to keep abreast of changes to the rules, especially if the Federal Circuit weighs in. On March 24, 2025, the Federal Circuit issued a precedential decision in In Re Riggs, Case No: 22-1945 (Fed. Cir. Mar. 24, 2025) clarifying the standard for determining whether a published patent application can be considered prior art as of its provisional filing date. Although this case was decided under pre-AIA law, the standard elucidated by the Federal Circuit reinforces the importance of drafting detailed provisional applications and knowing the requirements for establishing prior art under both pre-AIA and AIA law.Pre-AIA 35 U.S.C. § 102(e) and AIA 35 U.S.C. § 102(a)(2) deal with what many in the field refer to as “submarining prior art.” Even when armed with a bullet-proof prosecution strategy, “submarining prior art” can still take patent applicants and inventors by surprise. “Submarining prior art” is based on the principle that a patent application remains “secret” for typically 18 months from its filing date, until the USPTO publishes the patent application or the corresponding patent. During this period of “secrecy,” a competing inventor is unaware of the existence of the unpublished, pending patent application (hence the term, “submarining prior art”). As such, the inventor may prepare and file a patent application directed to what he or she believes is a patentable invention but that happens to cover the same or similar technology as that disclosed in the earlier-filed, as-yet-unpublished patent application. Only after the earlier-filed patent application publishes (like a submarine surfacing from underwater) does it become prior art as of its filing date. As one could imagine, this is potentially problematic for the competing inventor; the earlier-filed, now-published patent application might be prior art to the inventor’s later-filed patent application. In Re Riggs addresses when a patent or patent application qualifies as prior art under this type of situation.The Riggs patent application—U.S. Patent Application No. 11/005,678 (hereafter, “the ’678 application”)—had a priority date of July 28, 2000. During prosecution, the Examiner rejected the ’678 application under pre-AIA § 102(e) as anticipated by a patent publication, Lettich et al. (hereafter, “Lettich”). Lettich was filed on April 26, 2001 and claimed priority to a provisional application filed on April 27, 2000. In order to qualify as prior art under § 102(e), Lettich needed to be entitled to its April 27, 2000 priority date, which pre-dated the ’678 application’s July 28, 2000 priority date. Riggs addressed whether Lettich is entitled to the April 27, 2000 filing date of its provisional application for the purposes of qualifying as prior art to the ’678 application under § 102(e).The Examiner and the Patent Trial and Appeal Board (PTAB) relied on Dynamic Drinkware[1], Amgen[2], and MPEP § 2136.03 in determining whether Lettich qualifies as prior art under § 102(e). Specifically, they considered whether Lettich’s provisional application provided written description support for at least one claim in Lettich. Without any such written description support in the provisional, Lettich’s priority date for the purposes of 35 U.S.C. § 102(e) would be the April 26, 2001 non-provisional filing date, which would be insufficient to render Lettich prior art to the ‘678 application. The PTAB found that Lettich satisfied the aforementioned written description test identifying support in the provisional application for each limitation of claim 1 in Lettich. The PTAB concluded on this basis that Lettich was available as prior art under 35 U.S.C. § 102(e).The Federal Circuit agreed with the PTAB “that a prior art patent or published application cannot be accorded the benefit of its provisional application’s filing date absent a showing that the provisional application provides support for a claim of the patent or published application”[3] However, the Federal Circuit held that this finding alone is insufficient to determine whether a patent or published application qualifies as prior art under § 102(e).[4] As a second step of the analysis, “the provisional application must also provide written description support for the specific portions of the patent specification identified and relied on in the prior art rejection.”[5] The Federal Circuit noted that neither Dynamic Drinkware nor Amgen addressed the problem at issue here, as the appellants in those cases failed to satisfy the initial requirement that the provisional provide support for at least one claim. As such, there was no need in those cases to address the subsequent question of whether the specific text in the patent document relied on by the Examiner in the rejection also had written description support in the provisional application.The Federal Circuit clarified that even if a provisional application provides written description support for at least one claim of the patent document cited in a rejection, the provisional application must also provide written description support for the specific portions of the specification identified and relied on by the Examiner in the rejection. As the Federal Circuit reasoned, “[i]t makes no sense to suggest that if a single claim is supported by the provisional application, then everything in the later filed application gets the benefit of the provisional date whether supported or not.”[6] The Federal Circuit vacated and remanded the PTAB’s decision because the PTAB did not address the second step of the analysis.The Riggs decision aligns with MPEP § 2136.03 (III). It explains that two elements must be satisfied in order for a published patent application or patent to have the benefit of its provisional filing date under § 102(e):<blockquote>[A]t least one of the claims in the reference patent, patent application publication, or international application publication is supported by the written description of the provisional application in compliance with pre-AIA 35 U.S.C. 112, first paragraph, or 35 U.S.C. 112(a) . . . [and] . . . [t]he provisional application must also describe, in compliance with pre-AIA 35 U.S.C. 112, first paragraph, or 35 U.S.C. 112(a), the subject matter relied upon in the reference patent or publication to make the rejection.[7]</blockquote>When it comes to AIA law, the MPEP, like that for pre-AIA law, requires that a provisional application to which a reference patent document claims a right of priority “describe[] the subject matter” relied upon in the reference patent document in a prior art rejection.[8] Although Riggs is applicable only to pre-AIA law, given the related guidance in the MPEP regarding the treatment of prior art under pre-AIA 35 U.S.C. § 102(e) and AIA 35 U.S.C. § 102(a)(2), as well as the Federal Circuit’s stated rationale in its decision, one may reasonably expect that a similar outcome may apply in the AIA context too.What does all of this mean for patent practitioners going forward?As the Federal Circuit emphasized, “it is best to treat a published provisional application—like a published non-provisional application or patent—as prior art for all that it teaches as of its filing date.”[9] Taking this into account, patent practitioners should draft provisional applications with as complete a disclosure as possible.  A cursory provisional application may be necessary when circumstances do not permit a more fulsome drafting process. However, filing a fully fleshed-out provisional application will have benefits not only in ensuring entitlement to an earlier priority date for the eventual non-provisional filing, but also in ensuring entitlement to the earliest priority date for the purposes of qualifying as prior art against later patent applicants.  Although In Re Riggs has not made it any easier to predict “submarining prior art,” it has provided additional means for patent applicants and patent owners in post-grant proceedings to challenge the availability of a patent or patent publication as prior art as of its provisional filing date. Indeed, while “submarining prior art” may still bring an element of surprise, patent practitioners now have more tools in their arsenal when confronting such art during prosecution and post-grant proceedings. [1] Dynamic Drinkware, LLC v. National Graphics, Inc., 800 F.3d 1375 (Fed. Cir. 2015).[2] Amgen Inc. v. Sanofi, 872 F.3d 1367 (Fed. Cir. 2017).[3] In Re Riggs, Case No: 22-1945, 12 (Fed. Cir. Mar. 24, 2025).[4] Id.[5] Id.[6] Id.[7] MPEP § 2136.03, supra, note 3.[8] MPEP § 2154.01(b).[9] In Re Riggs, supra, at 13.

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Lisa N. Silverman focuses on patent portfolio management and strategic patent counseling in the areas of chemistry and life sciences. She has extensive experience in securing U.S. and foreign patent p