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Pharma company Aurinia falls after FDA official uses LinkedIn to call out lupus drug

Lupkynis, which was approved in 2021, is Aurinia’s primary source of revenue.

J. Edward Moreno

Aurinia Pharmaceuticals dropped on Monday after a Food and Drug Administration official criticized a method of evaluating drugs that was used to approve the companys flagship lupus medication.

George Tidmarsh, who has led the FDAs drug evaluation arm since July, said on LinkedIn that voclosporin, which is made by Aurinia under the brand name Lupkynis, has significant toxicity and has not been proven to benefit patients.

Specifically, he criticized the use of surrogate end points, which are indirect measures of patients health after taking a treatment that results in speedier trials. Tidmarsh said the FDA will be evaluating how it uses that kind of data for drug approval. Tidmarsh later deleted that post and in a subsequent post clarified that those were his personal views and not that of the FDA.

Screenshot 2025-09-29 at 3.57.01 PM
A screenshot of Tidmarsh's LinkedIn post. (Sherwood News)

Tidmarshs complete, since deleted LinkedIn post read:

CDER will be evaluating surrogate endpoints used for FDA approval. While there is no doubt that the use of such endpoints has benefited patients by bringing valuable treatments to patients sooner, there have been notable failures in confirmatory trials, such as those for exon skipping therapies in DMD. And for some diseases such as lupus nephritis, companies have not run trials to demonstrate a benefit on hard clinical endpoints like progression to end stage renal disease. So we have approved drugs with significant toxicity like voclosporin that has not been shown to provide a direct clinical benefit for patients. We will be taking a close look at the use of surrogate endpoints to see where we can further accelerate promising drugs faster while requiring companies to perform the trials necessary to confirm actual clinical benefit.

Lupkynis, which was approved in 2021, is Aurinias primary source of revenue. The company reported $235.1 million in sales last year, and analysts polled by FactSet have penciled in $270.5 million for 2025.

Aurinia fell as much as 21% after Tidmarsh’s post, and it ended the day down 16%.

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Michael Burry flags “troubling” jump in Nvidia’s supply commitments

The Big Short investor Michael Burry — famous for betting against the 2008 housing bubble — just warned of a major risk in Nvidia’s latest annual report, pointing to a sixfold surge in purchase obligations over the past year.

In a Substack post Thursday, Burry called the increase from $16.1 billion to $95.2 billion in just 12 months troubling, noting that Nvidia has been forced to place noncancelable purchase orders well before knowing the final demand for its AI chips. The surge is partly tied to supplier TSMC requiring longer-term contracts, he added.

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Vistra beats Q4 earnings expectations for adjusted EBITDA, but dips on income decline

Power provider Vistra, a key player in the AI energy trade, reported better-than-expected adjusted earnings results early Thursday, but shares dipped in early trading as Q4 net income dropped.

The Texas-based company, which supplies nuclear- and natural gas-fueled power to wholesale and retail markets, reported:

  • Net income of $233 million, a decline of 52% from Q4 2024.

  • Adjusted EBITDA from ongoing operations of $1.74 billion vs. the $1.71 billion expected by Wall Street analysts.

  • Vistra maintained previously issued guidance for full-year EBITDA from ongoing operations and adjusted free cash flow from ongoing operations.

Vistra shares soared 258% in 2024 amid a flurry of excitement over the AI energy boom. Last year was more muted, with the stock rising 17%. So far in 2026, shares were up roughly 9% before the report.

  • Net income of $233 million, a decline of 52% from Q4 2024.

  • Adjusted EBITDA from ongoing operations of $1.74 billion vs. the $1.71 billion expected by Wall Street analysts.

  • Vistra maintained previously issued guidance for full-year EBITDA from ongoing operations and adjusted free cash flow from ongoing operations.

Vistra shares soared 258% in 2024 amid a flurry of excitement over the AI energy boom. Last year was more muted, with the stock rising 17%. So far in 2026, shares were up roughly 9% before the report.

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Sandisk rises on partnership with SK Hynix to standardize memory chip architecture tailored for AI data centers

Sandisk is up 3% in premarket trading on Thursday after it began its global standardization strategy of high-bandwidth flash (HBF) memory solutions with SK Hynix.

SK Hynix commented in a press release on Thursday that by making HBF an industry standard, together with Sandisk, we will lay the foundation for the entire AI ecosystem to grow together,” adding that the companies will set up a dedicated workstream to work on the standardization under the Open Compute Project, the world’s largest organization dealing with data center technologies.

First debuted last February, Sandisk’s HBF technology lies in between ultrafast high-bandwidth memory (HBM) and high-capacity SSDs. That is, these have more storage capacity than HBMs, but are still fast enough to be utilized in AI inferencing (albeit not as quick as HBM).

Sandisk has previously argued that this hybrid architecture is central to AI services that need user applications but require a significant amount of fast interconnect between GPUs. The latest announcement also notes that HBF technology is expected to be more cost-efficient compared to alternatives of similar scale.

The launch, which was shared in an kickoff event on Thursday evening, starts SK Hynix and Sandisk’s workflow, which was announced when the two companies signed a memorandum of understanding “to standardize the specification, define technology requirements and explore the creation of a technology ecosystem” last August, per Sandisk’s press release at the time. Ultimately, by collaborating with SK Hynix, one of the three key HBM suppliers, to standardize and commercialize the technology, Sandisk is manufacturing somewhat of a first-mover advantage to offer the system-level “AI-optimized memory architecture” required for AI inference markets, rather than focusing on the performance of a single chip element.

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