Less than 14% of all clinical trials complete on time.1
Approximately 50% of clinical trials don’t meet enrollment goals.2
Less than 5% of cancer patients are enrolled in clinical research.3
We are taking on these numbers.
Our solutions directly address many of the inefficiencies that make it challenging to get novel therapies to patients who need them. And our results show it.
Patients
Enrolled
Our clinical trial matching platform is helping to securely identify and enroll more eligible patients for studies everyday.
%
Greater Patient
Accrual Rate
Our digitized clinical trials, electronic screening, and clinical support are consistently reported by sites to accelerate trial enrollment by nearly double.
%
Faster Feasibility and
Site Start-up
Our data enrichment is cited as reducing time needed to conduct clinical trial feasibility and activate sites.
Clinical Trial Patient Matching Solutions
Proven technology securely identifies more patients for clinical trials and presents a more complete understanding of patient populations.
Cancer Center Research Consortium
A real-world, longitudinal data set with millions of patients and hundreds of physicians and locations bring insight from EMR and other critical oncology data sources.
Life Sciences Analytics and Answers
Expertise and experience unite in applying an outstanding EMR and healthcare data solution to clinical and commercial challenges for biopharma, CROs, and Life Sciences consultants.
Clinical Expertise and
Services
Dedicated expertise optimizes productivity, helping to accelerate enrollment and collaboration with research teams to help identify and match patient candidates.
Clinical Trial Patient Matching Solutions
Proven technology securely identifies more patients for clinical trials and presents a more complete understanding of patient populations.
Clinical Trial Data Consortium
A real-world, longitudinal data set with millions of patients and hundreds of physicians and locations bring insight from EMR and other critical oncology data sources.
Life Sciences Analytics and Answers
Expertise and experience unite in applying an outstanding EMR and healthcare data solution to clinical and commercial challenges for biopharma, CROs, and Life Sciences consultants.
Clinical Expertise and
Services
Dedicated expertise optimizes productivity, helping to accelerate enrollment and collaboration with research teams to help identify and match patient candidates.

How We’re Different

Advanced NLP And Precision Matching

Unstructured to Structured Data

Digitized Clinical Trials
Deep, detailed digitization of the entire clinical trial protocol inclusion/exclusion criteria (e.g., diagnosis, stage, histology, molecular and diagnostic laboratory results), helps identify patients in a single key stroke.

EMR/EHR, Source-agnostic

Multiple Primary Real-World Data Sources & Types

Clinical Support Experts
Contact us to learn more about our unique, advanced platform for clinical research, translational medicine strategies and clinical decision support.
News and Insights
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Signify Research 2020 report explores how companies like Inteliquet are guiding the adoption of AI solutions for drug development and clinical trials
Inteliquet™, Inc. is featured as a leading company in AI in Drug Development &...
TrialSite News — What Can We Do About Clinical Trials As The Pandemic Continues to Get Worse?
Has anyone in your family had to cancel a doctor’s appointment or hospital visit in recent months?...
MedCity News — Covid-19 is derailing cancer clinical trials. Is new technology required to get them back on track?
It is time to make it our collective mission to bring data automation to patient recruiting for clinical trials…
2.) Managed Healthcare Executive. July 24, 2019. https://www.managedhealthcareexecutive.com/pharmacy/we-need-better-clinical-trial-recruitment-process.
3.) Agarwala, V., Khozin, S., Singal, et al. (2018). Real-World Evidence In Support Of Precision Medicine: Clinico-Genomic Cancer Data As A Case Study. Health Affairs, 37(5), 765-772. https://www.healthaffairs.org/doi/10.1377/hlthaff.2017.1579

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