Clinical Trials AI

Oncology AI reading the full patient chart, founded 2021 on the observation that while software could already handle the roughly 20 percent of medical data that is structured, generative AI made the other 80 percent, the free text notes, tractable. OncoLLM is the underlying platform and the architecture is disclosed with unusual specificity: not one model but a constellation of eight specialized models ranging from 3 billion to 72 billion parameters, working agentically to interpret information at the patient level. Prism is the trial matching application, screening patients with upcoming appointments against all active trials and working in both directions, patient to trial and trial to patient, with continuous tracking. Matches are cited back to pathology, biomarkers, and note level evidence rather than returned as a bare recommendation. The platform has expanded beyond matching into verifiable patient summaries for visit preparation, cancer registry abstraction, and structured data generation for research. Reported results include a 40 percent increase in trial matches, more than 30 percent increase in enrollments, and 67 percent reduction in chart review time, with one NCI designated center reporting 100 percent screening coverage at three times the throughput of manual review. Peer reviewed validation has appeared in Nature Digital Medicine with presentation at ASCO, and a pilot study at the Medical College of Wisconsin Cancer Center covers gastrointestinal, genitourinary, breast, and thoracic teams. Mount Sinai Tisch Cancer Center deployed Prism in January 2026, becoming the first NCI designated Comprehensive Cancer Center in New York City to use it for systemwide matching. More than $36 million raised; co-founders Sarim Khan and Hrituraj Singh.

AI intelligence platform for life sciences medical affairs, scientific communications, and drug safety, which places it on the medical rather than commercial side of pharma and distinguishes it from vendors excluded from this index for pharmaceutical marketing. The Sorcero Intelligence Platform reads across a reported 263 million publications and 1.3 billion citations globally alongside congress sessions, reports, surveys, CRM interactions, safety cases, and medical inquiries, identifying which key opinion leaders and clinicians are active in specific research areas or treating relevant populations. Sorcero Medical serves medical affairs, with Field Medical Excellence and Insights including an iPad capture app and Congress Intelligence with scientific abstract integration, both introduced March 2026. Sorcero Safety, built with Springer Nature, covers literature and adverse event monitoring for pharmacovigilance. Sorcero MedTech came from the July 2025 acquisition of Axiom Health, extending the platform to medical device real world data and making it a unified platform across pharmaceutical and device organizations. The company describes a trust first approach with hallucination prevention and validated outputs, and an agentic architecture using specialized agents to validate medical information. Reported adoption is a third to 40 percent of the top 30 global pharmaceutical companies. Named a Leader in AI enabled pharmacovigilance software by CB Insights alongside IQVIA, Veeva, and Oracle. Six foundational medical AI patents; 2025 Google Cloud Partner of the Year for Healthcare and Life Sciences. $59 million raised in total including a $42.5 million Series B in November 2025. Co-founded and led by Dipanwita Das.

Indexed for the AI platform and agent portfolio rather than for the wider clinical research services, data, and consulting business, which is context under this index's product scoping rule. IQVIA (NYSE: IQV) launched IQVIA.ai in March 2026, a unified agentic platform and agent marketplace spanning clinical, commercial, and real world operations, built on the company's proprietary health data and Healthcare grade AI together with NVIDIA Nemotron, NeMo Agent Toolkit, Dynamo, and LangChain, following a collaboration begun over a year earlier. Disclosed agent use cases include target identification, clinical data review, literature review, market assessment, and healthcare professional engagement. The company reports filing more than 100 AI related patents and deploying more than 150 intelligent agents across internal teams and client environments, with 19 of the top 20 pharmaceutical companies having begun incorporating IQVIA agents into their workflows. IQVIA AI Assistant is a generative interface over the company's existing solutions and data products. The commercial side of the portfolio includes healthcare professional targeting and engagement, which sits closer to pharmaceutical marketing than to clinical operations and should be evaluated separately from the research and clinical agents.

Indexed for the AI capabilities inside the Veeva Vault platform rather than for the platform itself, which is context under this index's product scoping rule. Veeva (NYSE: VEEV) is the dominant software platform for life sciences, spanning clinical, regulatory, safety, quality, medical, and commercial, with customers including Novo Nordisk, Gilead, Bristol Myers Squibb, Merck, Roche, Moderna, and BioMarin. Veeva AI Agents became available in December 2025, initially for Vault CRM (Free Text Agent flagging issues in call notes, Voice Agent for spoken input, Pre-call Agent assembling context) and PromoMats (Quick Check Agent scanning promotional content against brand and regulatory guidelines before medical, legal, and regulatory review, and Content Agent assisting reviewers). Agents are built on large language models from providers including Anthropic and Amazon, hosted on Amazon Bedrock but operating inside the Vault environment, accessible through the Vault interface or API and customizable through Veeva's AI framework. Safety and quality agents are reported live, with clinical and regulatory agents tied to the 26R2 release. Availability matters here and is stated rather than blurred: two further announced product lines are not yet available. Falcon, a separate platform for standardized agentic labor covering trial master file intake, safety case processing, and health authority interaction management, targets late 2026 for early adopters, and Agentic Authoring, which drafts submissible regulatory documents, is expected in late 2027. Neither is indexed as a shipping capability.

Indexed for the AI capabilities layered across the Medidata clinical trial platform rather than for the platform itself, which is treated as context under this index's product scoping rule. A Dassault Systemes brand, the underlying platform spans more than 38,000 trials and 12 million patients across roughly 2,300 customers and over one million registered users, anchored by Rave EDC. The AI products indexed here: Clinical Data Studio, an AI data quality management workspace that integrates Medidata and non Medidata sources, identifies data issues and safety signals, and is reported by one named customer to deliver up to 80 percent faster data review; Medidata AI Study Build within Designer, which automates study construction; and an AI imaging capability introduced at ASCO 2026 using proprietary algorithms including automated text detection that the company reports makes protected health information redaction 32 percent faster. Health Record Connect uses FHIR and health information exchanges to pull patient health records into trial data capture, reducing manual re entry at sites. The company reports its AI has supported more than 500 clinical studies over a decade, with more than 120 AI supported studies starting in 2025. Named customers for the AI products include Eisai.

AI platform for clinical data management and trial operations, sold to pharmaceutical and biotech sponsors. The Life Science Analytics Cloud is reported in use across more than 1,500 studies at over 50 pharma and biotech companies, and the company states its platform supported the trial behind the first COVID-19 vaccine. Core modules include Data Hub for harmonizing trial and real world data, Smart Data Quality which automates data review and query generation, Patient Insights, and Source to Submission which auto generates regulatory submission artifacts. An embedded generative AI co pilot writes and tests the code for cross domain data quality checks, removing manual programming from trial setup. In September 2025 the company introduced modular Clinical AI Agents built on its Agentic AI Framework, spanning study start to submission and designed explicitly to operate on partial autonomy with human oversight and controls, capable of independent reasoning, planning, and execution. Reported model depth is over 90 to 100 specialized models trained on life sciences data. Customer reported results with Pfizer include query handling time reduced by roughly 90 percent, data transformation time by roughly 50 percent, and submission timelines by roughly 35 percent. Named AI based Life Sciences Solution of the Year in the 2026 AI Breakthrough Awards, a third such recognition. Received a strategic growth investment of up to $430 million led by Carlyle with Amgen Ventures, Merck Global Health Innovation, McKesson Ventures, Pfizer Ventures, and Northpond participating.

Real world evidence generation, spun out of Stanford's Green Button project in 2020 and built to answer the question a clinician actually has at the bedside when no trial covers their specific patient. GENEVA OS is the underlying operating system across a federated network the company describes as exceeding 300 million anonymized patient records. ChatRWD is a chat based application that generates publication grade observational studies in minutes rather than months, without requiring a data scientist in the loop, and Green Button remains as a consultation service delivering evidence within 48 hours. Alexandria is the company's evidence library of pre computed evidence briefs. Two design decisions distinguish it: ChatRWD is an LLM independent framework, so an institution can maintain its own model security posture, and every answer carries a Real World Fitness Score rating how fit for purpose the underlying dataset was for that specific question, which is an explicit and unusual admission that evidence quality varies by question. Stanford Health Care has moved from using the service to embedding it in physician workflow and clinical notes. The Atropos Evidence Agent is distributed via the Databricks Marketplace under a partnership announced June 2025.

Tech bio company combining biological large language models, multimodal patient data, and agentic software. The Owkin K co pilot has two environments: K Navigator, an agentic research environment free to academic researchers that accelerates literature review across 26.5 million articles and 19 biomedical databases and explores spatial multiomic patient data, and K Pro, an enterprise co pilot that uses a single orchestrator to select and combine specialized biological AI skills across drug discovery and development. Both are powered by Owkin Zero, a fine tuned biological reasoning model. The company reports K Pro accelerating internal drug target identification from more than 12 months to roughly 3 months, validated through collaborations with AstraZeneca, Bristol Myers Squibb, and Sanofi, including a three year AstraZeneca licensing agreement to build biopharma agents. Owkin operates a group of entities spanning a biology foundation model (Bioptimus), diagnostics (Waiv), and a clinical stage drug program (Epkin); this record covers the software platform. Founded 2016 by Thomas Clozel, MD and Gilles Wainrib, PhD.

AI models of tumor and immune biology applied to precision oncology, serving both clinical care and drug development. The Tumor Portrait test integrates DNA and RNA exome sequencing into a single end to end assay, approved under CLIA, CAP, and the New York State Department of Health, producing tumor driver, microenvironment, and actionable biomarker characterization from one sample. Kassandra is the company's cell deconvolution model for reconstructing tumor microenvironment composition. Clinical and analytical validation was published in Communications Medicine, part of the Nature portfolio, across more than 2,200 tumors, reporting high reproducibility and clinical actionability in 98 percent of cases. Research collaborations span MD Anderson Cancer Center, Weill Cornell Medicine, and the Parker Institute for Cancer Immunotherapy, with nine abstracts accepted at ASCO 2026, and biopharma partnerships include Takeda for trial design and biomarker signature identification. A Japan joint venture operates with NEC Corporation and Japan Industrial Partners.

AI for gastroenterology across two product lines. SKOUT is a real time computer aided polyp detection device that received FDA 510(k) clearance in 2022 for adults undergoing colorectal cancer screening or surveillance, applying computer vision to endoscopic video to flag suspicious tissue during the procedure. In a randomized controlled trial published in Gastroenterology, SKOUT demonstrated a 27 percent relative increase in adenomas detected per colonoscopy, and the company states it was evaluated in the largest US based multicenter clinical study completed for a computer aided detection device in this category. The vendor reports the device does not extend total procedure or withdrawal time. Distribution runs through an exclusive partnership with Provation, a GI documentation vendor reporting more than 3,500 customer facilities. The second line, Clinical Trial Optimization and AI Recruitment, applies machine learning to endoscopic image scoring and patient identification for inflammatory bowel disease trials, serving life sciences sponsors rather than providers.

Real world data company built on records patients choose to contribute, indexed for the life sciences data platform rather than the free consumer application, which is the collection mechanism rather than the product sold. Patients use a free app and web platform to aggregate their records from more than 50,000 US healthcare providers across Epic, Oracle Health, athenahealth, Quest, and the VA, then consent to contribute de identified data for research. Novellia's AI stitches those fragmented sources into structured longitudinal patient journeys spanning a reported 15 to 20 years, which the company positions against conventional real world data assembled by brokers from claims and partial hospital records. Buyers are biopharma teams in HEOR, market access, clinical operations, and medical affairs; the company reports customers among a majority of the top 10 to 15 global pharmaceutical companies. Raised an $18 million Series A led by Spark Capital in June 2026, bringing total funding to $28 million. Founded by Shashi Shankar, previously at Genentech working on real world data.

Clinical trial technology platform combining decentralized trial execution and electronic clinical outcome assessment with an agentic AI layer added in 2026. Agent Studio is a no code agent builder the company describes as the first agentic AI platform purpose built for clinical development, letting sponsor teams configure agents for protocol development, trial planning, and data workflows, with human in the loop validation and integration across life sciences systems. Shipped agents include TMF Agent for trial master file document management, announced January 2026, and a Digital Data Flow Agent that converts trial protocols into machine readable data. The underlying platform is reported deployed in nearly 400 trials across 70 countries and 120 languages, serving more than one million patients, and was named a Leader in eCOA by Everest Group. Founded 2014; CEO and cofounder Dr Michelle Longmire.

AI platform that retrieves, aggregates, and structures fragmented medical records into longitudinal patient histories, originally built for oncology and since extended to all therapeutic areas. The Clinical Clarity Engine applies natural language processing and machine learning to unstructured records; the company reports processing more than 300 million medical records from over 550,000 healthcare locations, with every structured output linked back to its source document. The xDECIDE provider portal presents structured data, autogenerated summaries, and AI assisted treatment option reports with scientific rationale, ranked by the xCORE engine and reviewed through a virtual tumor board; xINFORM is the patient facing portal. Data products supply longitudinal real world oncology datasets to research and regulatory programs. Holds HITRUST e1 certification. Raised a $46 million Series B in June 2026.

Precision health technology company, indexed here for its business to business products rather than its consumer app. Lightpath is an AI enabled chronic care management program sold to health plans, employers, and pharmacy benefit managers, using agents to triage and escalate members to a clinical team of physicians, pharmacists, and dietitians, with Lightpath Metabolic covering diabetes, prediabetes, and obesity. Workbench is a research data environment used by the NIH All of Us Research Program, the Michael J. Fox Foundation, and Helix. Sightline is a wastewater based epidemiology program for early infectious disease detection. The free Verily Me consumer application is outside the scope of this record. Formerly an Alphabet subsidiary; became an independent company in March 2026 alongside a $300 million investment round.

Generative AI drug discovery company (HKEX: 3696) operating both as a platform vendor and a clinical stage biotech. Pharma.AI comprises PandaOmics (AI target identification and indication prioritization), Chemistry42 (generative molecular design using generative tensorial reinforcement learning rather than library screening), and inClinico (clinical trial outcome prediction). The platform's flagship validation is rentosertib, a TNIK inhibitor for idiopathic pulmonary fibrosis where AI selected the target, generated the molecule, and informed trial design: it entered a 320 patient Phase III trial in July 2026, with discovery published in Nature Biotechnology and Phase IIa results in Nature Medicine. The vendor reports reaching preclinical candidate nomination in 12 to 18 months on average against a 2.5 to 4 year industry norm, and 13 programs cleared for IND.

AI clinical trial matching and enrollment platform for oncology. SYNERGY-AI extracts structured information from patient records including biomarker data and matches against a reported 19,000+ active oncology and hematology trials, with matches audited by certified oncology case managers before use. The platform includes physician and patient facing assistants and a trial enrollment orchestration layer (TrialRelay). Peer reviewed evidence is unusually strong for this category: a prospective evaluation in 3,804 metastatic cancer patients published in ESMO Real World Data and Digital Oncology reported matching four times faster than conventional methods using a neuro symbolic, multi agent architecture with an oncology specific knowledge graph. Reports 200,000+ onboarded patients and customers spanning pharma, CROs, and community oncology practices.

Precision medicine company (NASDAQ: TEM) whose provider software is what this index covers: Next, an AI clinical decision support system that alerts clinicians to patients who may have fallen off care guidelines, backed by a vendor reported 662 patient prospective study across six sites; Hub, a physician platform rebuilt on an agentic architecture including a prior authorization agent; and David, a generative AI clinical assistant deployed directly into the EHR, with Northwestern Medicine as the first health system. Tempus acquired Deep 6 AI in March 2025, adding a precision research platform that applies natural language processing to structured and unstructured EMR data to match patients to clinical trials in near real time and to generate real world evidence. Deep 6 reports real time EMR feeds across more than 30 health systems, an ecosystem of over 1,000 research facilities including 18 academic medical centers and 11 NCI designated cancer centers, and that sites find more than 25 percent more patients than with traditional recruitment; the company notes 92 percent of trial inclusion and exclusion criteria benefit from unstructured data and that 15 to 20 percent of eligible patients are found through unstructured data alone. Outputs are positioned as decision support requiring trial team validation before action. The sequencing and pharma services businesses are context, not indexed products.