As therapies become more targeted, the central challenges of drug development have intensified. Trial protocols are more complex, and finding the right patients for biomarker-driven studies is increasingly difficult, leading to costly enrollment delays and high failure rates.^{1, 2}

At Tempus, we believe the solution is not just a better process, but a fundamentally new model for clinical development. We have built an integrated approach on a foundation of multimodal data, artificial intelligence, and a connected clinical network to address these challenges head-on.

By creating a system to de-risk trial design, accelerate site activation, and identify the right patients at scale, we aim to help our life science partners design smarter trials, shorten timelines, and ultimately bring novel therapies to patients faster. This article outlines the key pillars of our model, from our foundational data platform to our full-service clinical research organization (CRO) and advanced multi-omics solutions.

The foundation: An intelligent platform built on multimodal data

The engine behind our approach is an intelligent platform designed to break down data silos. The platform unifies a patient’s molecular profile with structured clinical notes, lab results, medication history, and radiological scans. By applying AI and machine learning to this comprehensive dataset, we generate insights that support precise therapy selection, automated clinical trial matching, and real-time treatment optimization.

This platform is fed by our extensive sequencing capabilities, with our laboratories running approximately one million tests annually. This scale, combined with our library of over 8.5 million de-identified research records, provides a resource for identifying “needle-in-a-haystack” patient populations for highly specific, biomarker-driven protocols.

Addressing the core challenge of modern clinical trials

The increasing complexity of clinical trials presents a significant hurdle. While more precise inclusion and exclusion criteria can lead to better patient outcomes, they also make recruitment exponentially more difficult. According to the American Cancer Society, approximately 85% of oncology trials are delayed or fail due to incomplete patient enrollment. This is compounded by low provider awareness, with only about 0.2% of physicians discussing trials as a primary option with their patients.²

We address this challenge by leveraging our integrated platform and connected network to optimize trial design and recruitment. The four key pillars of our solution include:

• Designing smarter trials by using real-world data to model and refine inclusion and exclusion criteria.
• Finding and engaging the right patients through a vast, data-linked clinical network.
• Activating sites at speed using pre-negotiated, standardized contracts.
• Unlocking deeper molecular insights with end-to-end genomics and multi-omics solutions.

The TIME Trial Network: Activating sites and engaging patients at scale

A cornerstone of our model is the TIME Trial Network, a nationwide network of clinical sites capable of rapidly activating trials. Poised to be the largest data-linked oncology network in the country, TIME includes over 100 sites and 800 locations, providing us with visibility into more than 4 million cancer patients.

A key advantage of the network is its focus on community-based settings, which represent 85% of its sites. This allows for a more diverse and representative patient sample, addressing a critical gap in traditional trial recruitment, which has historically relied on major academic centers.

To operationalize trials efficiently, we use two primary site activation models within the TIME network:

1. The expedited model: Best for early-stage trials with common biomarkers, this model activates a few large site systems with broad, matching patient populations.
2. The just-in-time model: Ideal for trials targeting rare populations or later-stage disease, this model activates a site only when an eligible patient is identified.

A blended approach is also available, providing maximum flexibility. This operational efficiency is demonstrated in a recent case study with a biotech partner on a Phase I first-in-human study. We achieved trial readiness in seven weeks and enrolled the first patient just four weeks later, highlighting the speed of the network.

Unlocking deeper insights with genomics and multi-omics

Beyond operational efficiency, we provide the molecular certainty needed to help de-risk targeted therapy programs. Our integrated next-generation sequencing (NGS) solutions offer a regulatory and technical bridge across the entire development lifecycle, from early-phase retrospective biomarker discovery to the execution of an FDA-approved companion diagnostic.

To address the biological complexity of disease, we offer a broad portfolio of Omics solutions, including genomics, proteomics, epigenetics, and methylation arrays. By employing a multi-omic approach, our partners can stratify patients with the right biomarkers and better understand a drug’s pharmacodynamics, efficacy, safety profile, and potential resistance mechanisms. These capabilities allow our partners to analyze disease biology at a deeper level, both before a trial begins and throughout its lifecycle.

A flexible partnership for accelerated development

We offer a full-service CRO with a flexible partnership model designed to meet the specific needs of each life science partner. For large pharmaceutical companies, we can supplement internal teams to solve complex challenges like finding rare patient populations or accelerating enrollment. For emerging biotechs, we can act as an end-to-end clinical development engine, providing the speed and capital efficiency critical to reaching key milestones. By integrating data, AI, and a connected network, we are building a new model to help partners bring therapies to patients faster.

Note: Content edited for clarity. Please note that the content in this document has been revised for clarity and conciseness. Some language and formatting may have been adjusted to enhance readability while preserving the original meaning and intent of the discussion.

Footnotes

1. Costs of drug development and research and development intensity in the US, 2000-2018 | Clinical Pharmacy and Pharmacology | jama network open | jama network. Accessed April 9, 2026. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2820562.

2. Idnay B, Fang Y, Butler A, et al. Uncovering key clinical trial features influencing recruitment. Journal of clinical and translational science. September 4, 2023. Accessed April 9, 2026. https://pmc.ncbi.nlm.nih.gov/articles/PMC10565197/.