Predictive Oncology develops liver toxicity models for Labcor

Published 12/06/2025, 13:38
Predictive Oncology develops liver toxicity models for Labcor

PITTSBURGH - Predictive Oncology Inc. (NASDAQ: POAI) has developed two 3D liver toxicity organoid models for Labcorp (NYSE: LH), a $21.8 billion healthcare services giant currently trading near its 52-week high, the company announced Thursday. According to InvestingPro data, Labcorp maintains a strong financial health rating with annual revenues exceeding $13 billion.

The human and rat models were designed to represent the liver microenvironment for evaluating drug metabolism and liver toxicity. According to the company, these models aim to predict in vivo drug clearance, drug transport, and hepatotoxicity. This development aligns with Labcorp’s position as a prominent player in the Healthcare Providers & Services industry, where seven analysts have recently revised their earnings expectations upward, as reported by InvestingPro.

"These models provide highly relevant, species-specific data based on their physiologic hepatic microenvironments while also capturing hepatic cellular heterogeneity," said Dr. Arlette Uihlein, Senior Vice President Translational Medicine and Drug Discovery for Predictive Oncology.

The organoid models complement Predictive Oncology’s existing AI-driven platforms that utilize the company’s biobank of over 150,000 frozen tumor samples.

John Kendrick, Ph.D., NAMs scientific strategy lead at Labcorp, stated that the company is "committed to developing and using new approach methodologies in preclinical studies." He added that Labcorp may consider expanding this work to other species to support wider preclinical analyses.

Data sets demonstrating liver morphology and function were generated from the models, including cell junction formation, transferrin staining, hepatotoxicity measurements, canalicular structure visualization, and cell viability confirmation for up to 14 days.

Predictive Oncology, headquartered in Pittsburgh, specializes in AI-driven drug discovery with a platform that reportedly predicts with 92% accuracy if a tumor sample will respond to certain drug compounds.

The information in this article is based on a press release statement from Predictive Oncology. For deeper insights into Labcorp’s financial health, growth prospects, and comprehensive analysis, access the full Pro Research Report available exclusively on InvestingPro, along with data for 1,400+ other US stocks.

In other recent news, Laboratory Corporation of America, commonly known as Labcorp, reported a 5.3% increase in revenue for Q1 2025, reaching $3.3 billion, although this fell short of the forecasted $3.41 billion. The company achieved an adjusted earnings per share (EPS) of $3.84, slightly surpassing expectations. Morgan Stanley raised its price target for Labcorp to $283, maintaining an Overweight rating, citing durable demand and potential growth driven by underlying trends such as an aging population and advances in diagnostics. Mizuho Securities also increased its price target to $274, maintaining an Outperform rating, reflecting confidence in Labcorp’s earnings visibility despite economic challenges.

Additionally, Labcorp shareholders approved new incentive plans during the company’s Annual Meeting, including the 2025 Omnibus Incentive Plan and the 2025 Employee Stock Purchase Plan. These plans aim to align employee and shareholder interests through stock-based compensation and discounted stock purchases for employees. Labcorp’s recent acquisitions, such as Invitae, are expected to become accretive by the second half of 2025, supporting margin expansion.

The company is also targeting $100-$125 million in cost savings through its Launchpad initiative. Analysts from Morgan Stanley and Mizuho expressed optimism about Labcorp’s strategic positioning and financial prospects, with the company projecting diagnostic revenue growth of 6.5-7.7% for 2025.

This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

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