Stock Markets February 18, 2026

Tempus AI Shares Climb After Rollout of HRD-RNA Cancer Detection Tool

Company introduces a 1,660-gene RNA model aimed at identifying patients likely to benefit from platinum chemotherapy or PARP inhibitors

By Priya Menon TEM
Tempus AI Shares Climb After Rollout of HRD-RNA Cancer Detection Tool
TEM

Tempus AI, Inc. (NASDAQ:TEM) saw its stock rise 3.5% Wednesday following the announcement of HRD-RNA, a 1,660-gene logistic regression algorithm that evaluates Homologous Recombination Deficiency via tumor gene expression rather than DNA scarring. The algorithm is available for research use now, with clinical availability expected later this year. Tempus reported real-world validation data showing reduced mortality risk for HRD-RNA positive metastatic pancreatic patients treated with first-line platinum regimens, with full supporting data to be published later this year.

Key Points

  • Tempus AI shares rose 3.5% Wednesday after the company announced its HRD-RNA algorithm for detecting Homologous Recombination Deficiency.
  • The HRD-RNA model is a 1,660-gene logistic regression algorithm designed to identify patients likely to respond to platinum-based chemotherapy or PARP inhibitors.
  • The algorithm assesses gene expression to provide a functional, dynamic view of tumor HRD status, and is available for research use now with clinical availability expected later this year.

Tempus AI, Inc. (NASDAQ:TEM) shares rose 3.5% Wednesday after the precision medicine technology company unveiled a new RNA-based algorithm intended to improve detection of Homologous Recombination Deficiency, or HRD.

The model, branded HRD-RNA, is a 1,660-gene logistic regression algorithm developed to identify patients who are more likely to respond to platinum-based chemotherapy or PARP inhibitors. Tempus described the approach as an RNA-driven assessment that evaluates gene expression to provide a functional readout of tumor biology.

Tempus contrasted the HRD-RNA approach with traditional DNA-based tests. While DNA tests look for relatively static signatures of structural damage often called genomic scars, the company said the RNA model assesses the transcriptome and therefore reflects a more dynamic picture of tumor functional status. According to Tempus, that difference allows the model to detect HRD in patients and in cancer types where genomic scarring may be difficult to identify.

In outlining clinical relevance, Tempus cited a real-world validation study in metastatic pancreatic cancer. The company said HRD-RNA positive metastatic pancreatic patients who received first-line platinum-based regimens showed a significant reduction in mortality risk versus those treated with non-platinum first-line therapies. Tempus noted that the complete supporting data will be published later this year.

"Our HRD-RNA algorithm gives physicians a critical tool to better inform treatment decisions," said Halla Nimeiri, MD, Chief Development Officer at Tempus. "By looking at the transcriptome, we can identify a functional HRD status that is more dynamic than what can be seen in the genome alone."

Tempus indicated that the HRD-RNA algorithm is currently available for research use only. The company expects clinical availability later this year.


The announcement and preliminary validation results connect diagnostic innovation with potential treatment selection impacts, particularly in oncology. The firm has positioned an RNA-based classifier as a complementary or alternative tool to DNA-based HRD tests, with implications for physicians deciding between platinum chemotherapy and targeted PARP inhibitor strategies where HRD status is a determining factor.

Risks

  • The HRD-RNA algorithm is currently available for research use only, and its clinical availability is still pending later this year - affecting near-term clinical adoption in healthcare and diagnostics.
  • While Tempus reported a real-world validation indicating reduced mortality risk for HRD-RNA positive metastatic pancreatic patients treated with first-line platinum regimens, the company has not yet published the complete supporting data - creating uncertainty for oncologists and payors in the biotech and pharmaceutical sectors.

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