Tempus AI, Inc. (NASDAQ: TEM) announced today the launch of Tempus Loop, a groundbreaking oncology-focused platform designed to transform target discovery and validation processes in pharmaceutical research. The proprietary platform integrates real-world patient data (RWD), human-derived biological models, and CRISPR-screens, all powered by artificial intelligence to accelerate novel target identification for pre-clinical therapeutic development.
The pharmaceutical industry has long struggled with translating promising preclinical experiments into effective patient treatments. Traditional approaches rely heavily on cell lines or animal models that often fail to accurately represent human tumors. Loop addresses this fundamental challenge through a novel integrated approach.
How Loop's Technology Works
Loop leverages Tempus' extensive real-world data repository to identify patient subpopulations with similar clinical, pathologic, and molecular patterns. The platform then employs systems biology approaches to reveal novel target genes and multimodal signatures. These signatures enable Tempus to map patient subcohorts to relevant patient-derived organoids (PDOs), which the company has been cultivating for years.
The seamless integration between real-world data and PDOs allows Tempus to validate targets using high-throughput functional screens in models that more closely reflect actual patient attributes. This RWD-to-PDO-and-back approach facilitates rapid hypothesis generation and testing in the most relevant disease models, significantly accelerating the target discovery and validation process.
"Novel target discovery continues to be a major challenge in oncology. Despite increased spending in R&D, we still have a 90% failure rate for preclinical assets to become real-world medicines," said Kate Sasser, PhD, Chief Scientific Officer at Tempus. "With Loop, we have integrated vast multimodal patient data, which includes outcome data, with more relevant human biological models and high-throughput functional screens, all wrapped with AI tooling, to ultimately help find new patient cohorts of interest and unique and clinically relevant targets."
Early Success with Pharmaceutical Partner
The platform has already demonstrated promising results. Tempus has deployed Loop to prioritize drug targets in patient subpopulations with severe unmet needs for a large pharmaceutical company. By incorporating a lab-in-the-loop strategy, its biological modeling and functional screening capabilities confirmed and validated these targets within a year—a significant acceleration compared to standard discovery timelines.
Addressing the Preclinical-to-Clinical Translation Gap
The 90% failure rate of preclinical assets becoming approved medicines represents one of the most significant challenges in drug development. This high attrition rate is largely attributed to the limited translatability of preclinical models to human disease.
Loop's approach directly addresses this gap by ensuring continuity between real-world patient data and the biological models used for target validation. By using patient-derived organoids that more accurately reflect human disease characteristics, Tempus aims to increase confidence in target relevance before significant resources are invested in clinical development.
AI-Driven Precision Medicine
Tempus has established itself as a leader in applying artificial intelligence to advance precision medicine. The company maintains one of the world's largest libraries of multimodal healthcare data and has developed an operating system to make that data accessible and useful for personalized patient care.
The Loop platform represents a natural extension of Tempus' mission to leverage AI and data to improve therapeutic development. By connecting real-world patient outcomes with biological modeling and high-throughput screening, Loop creates a more efficient and potentially more successful path to identifying novel therapeutic targets in oncology.
Dr. Sasser noted that early results have been encouraging, with the platform "speeding up the timelines for our drug discovery customers, while also increasing confidence in the clinical relevance of these targets."
As the pharmaceutical industry continues to face challenges in improving R&D productivity, platforms like Loop that bridge the gap between preclinical research and clinical relevance may play an increasingly important role in the future of drug discovery and development.
