Open Genomics and Privacy: New Case Law in South Africa Affirms a Key Principle

by Donrich Thaldar

As the era of genomic medicine dawns, large-scale genomics projects are becoming increasingly central to health care advancements. Projects like FinnGen in Finland, the UK Biobank, and the All of Us initiative in the United States are charting new frontiers in precision medicine, enabling researchers to unlock the genetic codes underlying a wide array of diseases. These initiatives collect genetic data from hundreds of thousands of individuals, providing an invaluable resource to identify disease markers and tailor medical treatments to individuals’ genetic makeup. Such projects are not only pushing the boundaries of medical knowledge but are also laying the foundation for a future where treatments are more effective and personalized.

However, in the Global South, large-scale genomics projects are far fewer. Qatar has taken strides with its own Qatar Genome Program, but examples are still limited across Africa and other regions, where genomics research is often constrained by funding, infrastructure, and representation issues. In Africa, where genetic diversity is high but research representation has historically been low, the need for such projects is critical. Without local genomics data, the benefits of precision medicine may largely bypass African populations, further exacerbating global health inequities.

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When AI Turns Miscarriage into Murder: The Alarming Criminalization of Pregnancy in the Digital Age

by Abeer Malik

Imagine: Overjoyed at your pregnancy, you eagerly track every milestone, logging daily habits and symptoms into a pregnancy app. Then tragedy strikes—a miscarriage. Amidst your grief, authorities knock at your door. They’ve been monitoring your digital data and now question your behavior during pregnancy, possibly building a case against you using your own information as evidence.

This dystopian scenario edges closer to reality as artificial intelligence (AI) becomes more embedded in reproductive health care. In a post-Dobbs world where strict fetal personhood laws are gaining traction, AI’s predictive insight into miscarriage or stillbirth are at risk of becoming tools of surveillance, casting suspicion on women who suffer natural pregnancy losses.

The criminalization of pregnancy outcomes is not new, but AI introduces a high-tech dimension to an already chilling trend. At stake is the privacy and the fundamental right of women to make decisions about their own bodies without fearing criminal prosecution. Alarmingly, the law is woefully unprepared for this technological intrusion.

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Health Care, AI, and the Law: An Emerging Regulatory Landscape in California

by Rebekah Ninan

This past month, California Governor Gavin Newsom signed a wave of artificial intelligence-related legislation into law. Much public debate has been focused on SB 1047, a proposal ultimately vetoed by Governor Newsom, which would have held AI companies liable for “catastrophic harms” from AI models. Comparatively little attention has been paid to three new laws aimed at health care-related AI and data privacy. Three laws are AB-3030, SB-1223, and SB-1120. AB 3030 requires that health care providers disclose when they have used generative AI to create communications with patients. SB 1223 amended the California Consumer Privacy Act of 2018 to include neural data as sensitive personal information, whose collection and use companies can be directed to limit. Finally, SB 1120 limits the degree to which health insurers can use AI to determine medical necessity for member health care services. This article seeks to summarize these developments in the law.

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Protecting Health Privacy is a Royal Pain

Heightened Scrutiny of Your Royal Highness

On Sunday, March 10, tabloids were in quite a frenzy when the British royal family published a photoshopped picture of Catherine, princess of Wales. The hubbub was extra hubbubbly, because this was the first official photo after the princess had abdominal surgery this past January. The order of events caused some people to speculate the edits indicated there was something to hide about the princess’s health status.

Shortly after the public reaction, the princess issued an apology for the edits. Sadly, less than two weeks later, the rumors were confirmed to be true: Princess Catherine did have a health problem. She had been diagnosed with cancer and had commenced preventative chemotherapy. As part of this announcement, Princess Catherine bravely encouraged the public, “For everyone facing this disease in whatever form, please do not lose faith or hope. You are not alone.” Read More

EU and US Regulatory Challenges Facing AI Health Care Innovator Firms

By Suzan Slijpen, Mauritz Kop & I. Glenn Cohen

1. Introduction: A Fragmented AI in Healthcare Regulatory Landscape

In the past few years, we have witnessed a surge in artificial intelligence-related research and diagnostics in the medical field. It is possible that in some fields of medicine in the future AI tools used in diagnostics will generally perform far better than a human clinician. Prime examples of this can be found in radiology, particularly in the detection -and even the prediction- of malignant tumors.

Although the actual development of a clinically usable, deployable deep-learning algorithm is a challenge in and of itself, we have moved from an early period where there was not enough guidance as to ethical and other issues to an era where many guidelines have proliferated. While one might ordinarily say “let a thousand flowers bloom,” the fact that they partially overlap, sometimes diverge, and are often written at different levels of generality make it difficult for well-meaning companies to keep up. This is specifically the case for innovative firms who aim to bring their product into the European market.

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blue brain hovers over bright blue circle.

Is OI the New AI? Questions Surrounding “Brainoware”

By Adithi Iyer

The idea of artificial intelligence is just seeping into our collective consciousness, but as we watch new developments in the space, the true “new kid on the block” may be a new type of infused human-technology intelligence — one derived from a blob of cells no larger than a grain of rice. These new units of computational prowess are brain organoids, grown in-lab and capable of producing very basic, but real-time, neurological activity. Brain organoids are a specific, and arguably the most interesting, subset of organoid models that are just beginning to enter legal debates.

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Culturing cells in tissue culture plates.

R&D Mini-Me? New Legal Questions for Organoids

By Adithi Iyer

I have written previously about the not-so-distant possibility and promise of regenerative medicine, an area concerned with therapies that encourage the body to repair or heal itself. Cell-mediated and tissue-based technologies hold promise in inducing self-repair from within the body, and they’re making their way to market in traditional medicine. Much has been made of recently discussed CAR-T cell therapies for cancer, which have been around since 2017, and in-human sickle cell treatment Casgevy. Such applications of regenerative medicine and tissue engineering are wide-spanning and range across the bench-to-bedside pathway.

One application of regenerative medicine gaining some ground in the R&D space is the organoid. Organoids are lab-grown masses of cells and tissue that assemble to form miniature organs or organ systems in vitro. They come, too, in different forms and types, and while some organoid applications are heavily modified for specific functions, many are meant to recreate and model the naturally occurring organ systems we would find in our own bodies.

Organoids may sound especially futuristic, but are currently used regularly in labs for different research and therapeutic applications. A functional “organ” model not attached to a human body could offer the opportunity to model diseases and test treatments in real time without the need for an animal model (like the mice used today), especially in preclinical and early clinical trials for new drugs. Organoids generate information and data, and a single organoid model can even be hooked up to a “system” with other organoids to model systems and interrelated processes at once. The production of these models occurs in-lab, often involving stem cells that can divide and organize into tissues and organs on their own.

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Newspapers and Laptop.

AI, Copyright, and Open Science: Health Implications of the New York Times/OpenAI Lawsuit

By Adithi Iyer

The legal world is atwitter with the developing artificial intelligence (“AI”) copyright cage match between The New York Times and OpenAI. The Times filed its complaint in Manhattan Federal District Court on December 27 accusing OpenAI of unlawfully using its (copyrighted and paywalled) articles to train ChatGPT. OpenAI, in turn, published a sharply-worded response on January 8, claiming that its incorporation of the material for training purposes squarely constitutes fair use. This follows ongoing suits by authors against OpenAI on similar grounds, but the titanic scale of the Times-OpenAI dispute and its application of these issues to media in federal litigation makes it one to watch. While much of the buzz around the case has centered on its intellectual property and First Amendment implications, there may be implications for the health and biotech industries. Here’s a rundown of the major legal questions at play and the health-related stakes for a future decision.

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A surveillance camera on a white background.

Combatting Elder Abuse in Long-Term Care: Challenges and Opportunities of Electronic Monitoring

By Laura C. Hoffman

The aging population is growing at an extraordinary rate in the U.S. By 2040, it is anticipated that the U.S. aging population (defined as those ages 65 and older) will double, totaling 80 million.

Given this growth, preventing elder abuse must be at the forefront of policymaking. The U.S. Centers for Disease Control and Prevention (CDC) has recognized elder abuse as a “serious” problem that is commonly occurring, yet significantly underreported, in the U.S.

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