Genomic Sequencing + AI-Assisted Analytics = Functional Precision Medicine

THE AMERICAN Cancer Society (ACS) expected more than two million new cancer cases to be diagnosed and more than 618,000 people to die from cancer in 2025 in the U.S. However, while ACS said progress is being made to reduce the number of people being diagnosed with cancer due to decreases in smoking, advances in treatment and early detection for some cancers,¹ cancer diagnoses and treatments remain two of healthcare’s most complex challenges.

Historically, cancer has been treated with standardized protocols driven by population-level data or trial-and-error approaches. More recently, evolving artificial intelligence (AI)-driven functional precision medicine (FPM) platforms combine patient-derived tumor biology with advancements in proprietary cell enrichment processes, automation, robotics and AI. FPM platforms enable oncologists to rapidly test how an individual patient’s cancer responds to hundreds of U.S. Food and Drug Administration (FDA)-approved drugs and combinations, delivering ranked treatment options within days.²

What is FPM?

FPM is an advanced medical approach that takes a patient’s living cells — most commonly from a tumor — and tests them directly against hundreds of different drugs or drug combinations in a laboratory. Instead of relying solely on DNA sequencing to find genetic matches, it measures which treatments actually kill the cells.

While traditional precision medicine uses DNA or genomic sequencing to identify specific mutations, it can only guide treatments for a fraction of patients whose tumors have a known, targetable mutation. FPM provides immediately actionable, personalized data by directly perturbing a patient’s viable cells and physically measuring the response. This method bypasses the limitations of genetics by revealing how the unique biology of an individual’s disease behaves in real time.³

What Are the Benefits of Functional Precision Medicine?

FPM provides additional treatment avenues for patients who have exhausted standard-of-care options or who lack actionable genetic mutations. It also reveals which drugs a tumor responds to and which ones it resists, preventing the prescription of ineffective drugs and reducing unnecessary toxicity.

According to an article from Trends in Molecular Medicine, “Growing evidence has … shifted the mindset in oncology, considering cancer as a highly individualized disease that requires a tailored therapeutic strategy, based on both molecular and functional data, thereby emphasizing the value of FPM approaches.”⁴

By using FPM AI platforms, doctors can now accelerate the discovery of novel targets, predict the effectiveness of treatments, identify potentially lifesaving clinical trials and diagnose multiple diseases earlier.

Many oncology companies have developed FPM AI platforms to identify types of cancers and how those cancers are expected to progress, as well as to identify the best course of treatment specifically tailored to each patient’s cancer. Following are summaries of First Ascent Biomedical, Tempus and Strata Oncology’s FPM AI platforms.

First Ascent Biomedical

First Ascent Biomedical is a precision oncology company that provides oncologists and patients with data, based on each patient’s biology, to enable them to design an evidence-based, personalized treatment plan for patients who have failed the standard-of-care regimens.

The company’s FPM platform, called xDRIVE (Ex Vivo Drug Response Identification & Validation Engine), is an AI-powered clinical decision support for oncologists treating refractory or treatment-resistant cancers. xDRIVE combines three core components: functional drug validation, genomic sequencing and AI cancer weakness mapping.

First Ascent’s proprietary live-cell approach is the first and only platform capable of testing up to 150-plus FDA-approved therapies and combinations in parallel on both liquid and solid cancers that delivers precise, patient-specific evidence on how an individual’s cancer responds in approximately 10 days or less.⁵

xDRIVE begins with a fresh tumor or blood sample containing viable cancer cells. Those living cancer cells are tested ex vivo against a broad panel of FDA-approved therapies and combinations to observe how the patient’s cancer actually responds.

First Ascent then integrates those functional drug-response results with genomic DNA/RNA data and individualized machine learning (ML)-guided analysis to identify the tumor’s vulnerabilities and prioritize treatment options for the treating physician.

For physicians, the key distinction of xDRIVE is that it does not rely on genomics predictions. Genomic testing can identify mutations, molecular markers and potential targets, but it does not always indicate whether a patient’s living cancer cells will respond to a specific drug or combination of drugs.

xDRIVE bridges that gap by adding a functional layer through direct testing of the patient’s own viable cancer cells. The resulting data is intended to support, not replace, the oncologist’s clinical judgment.

First Ascent’s current FPM AI platform is focused on cancer treatment decision support, rather than broad disease diagnosis. Its potential to change care lies in shifting oncology from a largely population-based model toward a more individualized model based on the biology of each patient’s living cancer cells.

Jim Foote, co-founder and CEO of First Ascent Biomedical, said, “In conventional oncology, treatment selection is often guided by tumor type, stage, population-based standard protocols and, increasingly, genomic markers. These tools are essential, but they can still leave physicians with difficult questions, particularly in relapsed, refractory, rare or aggressive cancers. A genomic test may show no actionable mutation, or it may identify a possible target without proving that the cancer will respond to a specific therapy. First Ascent’s premise is that physicians need both molecular information and functional evidence: not only ‘What mutations does this cancer have?’ but also ‘Which drugs actually affect this patient’s cancer cells?’

“This is where individualized ML becomes important. The xDRIVE platform generates and integrates multiple layers of information, including live-cell drug response, genomic sequencing, cancer characteristics and treatment sensitivity patterns. ML is used to synthesize the data and highlight treatment vulnerabilities that may not be obvious from genomics or standard pathology alone. First Ascent believes this can help physicians move away from trial-and-error treatment selection and toward faster, evidence-based prioritization of therapies for individual patients, because all of the data used to train the ML model is specific to each patient.

“For health systems, this approach could have implications beyond the individual case. If validated at a larger scale, FPM could help reduce time spent on ineffective therapy, limit avoidable toxicity, identify rational drug combinations and make better use of FDA-approved drugs. For patients with advanced disease, time matters. A platform that can return actionable treatment information within roughly 10 days may help physicians make decisions while the patient is still clinically eligible for therapy.

“The goal [of FPM] is not to replace today’s standard of care, but to strengthen it with evidence specific to the individual patient.”

A recent example of a cancer patient who has benefited from First Ascent’s xDrive platform is Logan Jenner, a child treated through the FPM approach developed with investigators at Florida International University and Nicklaus Children’s Hospital.

“Logan was diagnosed with acute myeloid leukemia at age 3. He received chemotherapy and a bone marrow transplant but his cancer returned 14 months later,” said Foote. “He was enrolled in the clinical trial, and the functional testing results identified a drug combination that appeared likely to work for his cancer. The results also helped indicate that idarubicin, a drug associated with cardiac toxicity at very high doses, could be withheld without reducing the expected efficacy of the regimen. Thirty-three days after starting treatment guided by the results, Logan reached remission; five years later, he remained cancer-free and without any heart problems.”

Strata Oncology, Inc.

Strata Oncology is a next-generation precision oncology company that combines molecular profiling tests, biomarker algorithms, — such as the Immunotherapy Response Score (IRS) and Antibody-Drug Conjugates (ADCs) biomarkers — real-world data, and a large-scale clinical trial platform to identify and deliver optimal treatments for patients who have advanced cancer.

Launched in 2023, the Strata Select platform is a first-of-its-kind pan solid tumor molecular profiling test integrating DNA and quantitative RNA sequencing. The platform features the IRS, a proprietary, pan-solid tumor predictive biomarker for anti-PD-1/PD-L1 checkpoint inhibitor monotherapy benefit that has been validated in multiple publications. IRS has been shown to have utility beyond standard biomarkers used to guide anti-PD-1/PD-L1 therapy, including tumor mutation burden, microsatellite instability and PD-L1 immunohistochemistry.

Strata Select also provides comprehensive genomic profiling results, along with supplemental information, including quantitative RNA gene express-based results that provide insights that can be informative for other classes of therapy such as ADCs.

ADC Biomarker, Strata’s proprietary multi-factorial biomarker, can predict response to ADCs across multiple targets and tumor types. Independent evaluation showed improved response rates, progression-free survival and overall survival for biomarker-high patients.

The company’s Strata PATH (Precision Indications for Approved Therapies) is a 700-patient pan tumor clinical trial that evaluates the safety and efficacy of multiple FDA-approved therapies in new, biomarker-guided populations. The trial matches patients with specific therapies based on advanced DNA and RNA analysis.⁶

“Identifying patients who will successfully respond to immunotherapy treatment is key to providing the best possible therapy for patients with cancer,” said Dan Rhodes, PhD, co-founder and CEO of Strata Oncology, Inc. “Using a single small tissue sample, our integrated platform provides treatment selection guidance across therapeutic modalities.”⁷

Tempus

Tempus is a healthcare technology company advancing FPM in oncology through the application of AI. With one of the world’s largest libraries of multimodal data and an operating system to make that data accessible and useful, Tempus provides AI-enabled precision medicine solutions to physicians to deliver personalized patient care and in parallel facilitates discovery, development and delivery of optimal therapeutics. The goal is for each patient to benefit from the treatment of others who came before them by providing physicians with tools that learn as the company gathers more data.

The Tempus xH platform is a comprehensive whole-genome sequencing (WGS) assay and analytical tool designed to uncover actionable oncologic targets. By utilizing a next-generation sequencing (NGS) approach, it consolidates multiple tests into a single, cost-effective assay to streamline workflows in clinical settings and drug development pipelines. xH is expected to be commercially available for clinical ordering in late 2026.

The company recently announced the upcoming clinical availability of the xH test, first announced in January 2025 for research use, a next-generation sequencing test that uses a WGS approach for the detection of actionable oncologic targets in peripheral blood and bone marrow samples from patients with hematologic malignancies. Specifically, this test was developed for use in acute myeloid leukemia, myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN) and overlap syndromes (MDS/MPN). It is optimized for myeloid neoplasms and is designed to support disease understanding, biomarker discovery and therapeutic research.

The performance of Tempus’ xH test was established in an analytical validation study using 235 unique specimens, including whole blood, bone marrow and cell lines. Assay performance was evaluated by comparison with established orthogonal methods to assess analytical accuracy and precision across multiple variant classes.

The analytical validation demonstrated high accuracy across all major alteration types and achieved a positive percent agreement (PPA) of 97.29 percent for single nucleotide variants (SNVs) and insertions and deletions (indels) against the Tempus xT (DNA; 648 gene) assay, 92.86 percent PPA for structural variants (SVs) against the Tempus xR (RNA; whole transcriptome sequencing [WTS]) assay and confirmation Sanger sequencing, and 93.43 percent PPA for CNAs against an oligo-SNP chromosomal microarray.

In addition to high accuracy, the xH assay demonstrated excellent precision, ensuring reliable and reproducible results. The assay achieved a positive predictive value (PPV) of 98.97 percent for SNVs and indels, and 100 percent for SVs. These results indicate a low false-positive rate and support high confidence in the assay’s reported genomic findings.

Data presented at the 2026 American Society of Clinical Oncology Annual meeting demonstrate the assay’s clinical utility in resolving historical diagnostic blind spots. In a blinded study of an MDS cohort, xH achieved greater than 99 percent sensitivity and uncovered 40 percent more clinically relevant genomic findings, surfacing critical actionable genomic variations that were completely missed by traditional standard-of-care techniques.⁸

“When we introduced xH, our goal was to create a standardized WGS platform that could transform care in hematologic oncology,” said Tom Schonherr, CEO of Diagnostics at Tempus. “We’ve realized that vision by replacing multiple time-consuming diagnostic tests with a single, high-throughput whole-genome workflow that helps clinicians make faster, smarter decisions. At the same time, xH provides biopharma partners with a comprehensive multiomic foundation to improve clinical trial design, accelerate biomarker discovery and support the development of next-generation targeted therapies.”⁹

Looking Forward

The Society for Functional Precision Medicine, whose vision is to make FPM a rigorous, clinically actionable and measurable part of how precision medicine is used to treat cancer, believes the next decade will require marrying tumor profiling with systematic, scalable functional testing directly on patient-derived tissue and models to guide therapy, accelerate discovery and benefit patients.¹⁰

An article in Trends in Molecular Medicine states, “We envision the integration of AI into FPM programs as the cornerstone of the future of personalized cancer care, enabling the personalization of monotherapy and combination therapy regimens tailored to the unique characteristics of each cancer patient across all ages and cancer types.”⁴

In an article published in the journal Cancer Cell titled “Functional Precision Oncology: Testing Tumors with Drugs to Identify Vulnerabilities and Novel Combinations,” the authors write, “We predict that the next five years will see an increasing marriage of these two approaches [genomics and FPM] in clinical trials whose completion will be necessary for the establishment of functional precision medicine as a standard tool in clinical oncology. This union will be necessary for the rational selection of active combination regimens that will ultimately be necessary for precision medicine in oncology to provide its greatest benefit to patients.”¹¹

“The biggest breakthrough in cancer care is unlikely to be a single drug or algorithm,” added Foote. “It will be the engineered intersection of biology, technology, AI and therapeutics working synergistically around each individual patient.”¹²