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Kimberly Chew

Kimberly is a seasoned professional with a rich background in biotech research, leveraging her extensive experience to guide clients through the intricate landscape of clinical trials and academic research compliance.

As the co-founder and co-lead of the firm’s Psychedelic and Emerging Therapies practice group, Kimberly is particularly inspired by the potential of psychedelic therapeutics to address mental health conditions like PTSD. She skillfully navigates the legal intricacies surrounding these therapies, providing guidance through the clinical trial process at both state and federal levels.

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This is the third in a series of blog posts focused on AI and clinical trials/research space, highlighting topics to be discussed at the upcoming BIO International convention on June 22-25, 2026.

AI is transforming drug discovery faster than deal structures can adapt. Traditional licensing frameworks were built for linear innovation: researcher invents, institution owns, licensee commercializes. AI shatters that model by distributing inventive contributions across algorithms, datasets, and human researchers in ways that make ownership genuinely ambiguous. For business development teams, tech transfer offices, early-stage biotech CEOs, and investors, these ambiguities surface during due diligence, valuation negotiations, or post-acquisition integration as deal-killers.

This is the second in a series of blog posts focused on AI and clinical trials/research space, highlighting topics to be discussed at the upcoming BIO International convention on June 22-25, 2026.

Introduction

Your latest trial sponsor is using AI to accelerate protocol development and patient recruitment,[1] cutting timelines that once took months down to weeks. The efficiency gains are undeniable. Then your quality assurance team asks a simple question: “Can you reproduce these AI-generated inclusion criteria?” You realize you can’t. The same prompts produce different outputs each day. When you ask the AI vendor how to validate their tool under ICH E6(R2), they send you marketing materials about “cutting-edge technology,” not validation documentation.

This is the first in a series of blog posts focused on AI and clinical trials/research space, highlighting topics to be discussed at the upcoming BIO International convention on June 22-25, 2026.

A major research institution combines 15 years of patient genomic data with metabolomic profiles and clinical outcomes, feeding it into an AI model for drug target discovery. The resulting insights are groundbreaking—until the legal department asks: “Did any of those consent forms authorize AI analysis? Or data sharing across these datasets? Or commercial drug development?”

Earlier this month, Judge Rakoff of the Southern District of New York issued a first-of-its-kind ruling in United States v. Heppner. The case involved a criminal defendant, Heppner, who used a public generative AI platform (Claude) to “prepare reports that outlined his defense strategy (what he might argue with respect to the facts and the law that [his attorneys] anticipated that the government might be charging”). Although the defendant prepared the documents on his own, he later shared them with his attorneys. Heppner argued that these AI-generated documents should be protected by attorney-client privilege and the work product doctrine.

Everyone is talking about AI, but not everyone understands what AI is. AI, or artificial intelligence, refers to technology that enables machines to perform tasks that traditionally required human thinking—things like reading, writing, analyzing information, and making decisions.

A particularly powerful form of AI today is the large language model (or LLM), which is a type of AI trained on vast amounts of text that allows it to understand and generate human language, making it the engine behind popular tools like chatbots and AI writing assistants. Think ChatGPT or Google Gemini.

Blog SeriesConference Post (1)

This is the third in a series of articles designed to provide SXSW and LSI USA ’26 attendees and other MedTech professionals with practical considerations for efficiently executing mission-critical life science deals. On March 15, during SXSW, Husch Blackwell’s healthcare team will host two panels, bringing together founders and investors from healthcare, technology, and early-stage companies for candid discussion, practical insights, and plenty of time to connect.

Register here.

Doctor working on laptop computer

In my November 2025 blog post, I discussed the uncertainty surrounding the DEA’s then-pending telemedicine rule and its implications for ketamine clinics. At that time, the future of pandemic-era telehealth prescribing flexibilities was unclear, and clinics across the country were bracing for the possibility of a significant regulatory shift at the end of 2025.

The regulatory landscape for substance use disorder (SUD) treatment records is changing—and the impact will extend far beyond traditional addiction treatment programs. With treatment options for SUD limited, some providers are exploring ketamine as a potential therapy due to its effects on glutamatergic neurotransmission.[i] Additionally, psychedelic-assisted therapies involving certain Schedule I substances – such as psilocybin, ibogaine, and MDMA – are currently being studied by researchers as potential treatments for SUDs.[ii] While these investigational therapies are not yet available in clinical practice and the new federal privacy rules do not apply to research records, providers should be aware of the evolving treatment landscape as these therapies move closer to potential approval and clinical use.

Telehealth

The legal and regulatory landscape for ketamine clinics is shifting once again, as the Drug Enforcement Administration (DEA) prepares to release its “Fourth Temporary Extension of COVID-19 Telemedicine Flexibilities for Prescription of Controlled Medications.” While the full text of this rule is not yet public, its very existence signals that the DEA may continue the pandemic-era telehealth flexibilities that have proven vital for many clinics and patients. For owners and operators of ketamine clinics, understanding what’s at stake and how to prepare is more important than ever.

Laboratory Testing

In June 2025, the U.S. Department of Health and Human Services Office of Inspector General (OIG) announced a new item in its Work Plan: “Medicare Payments for Clinical Diagnostic Laboratory Tests in 2024.” This annual review, mandated by the Protecting Access to Medicare Act of 2014 (PAMA), focuses on analyzing the top 25 laboratory tests by Medicare expenditures for the previous calendar year. For clinical laboratories and healthcare providers, this announcement signals the need to pay close attention to billing practices, compliance programs, and potential audit risks.