TriNetX, a global health research network that revolutionizes clinical research and enables discoveries through the generation of real-world evidence (RWE) has acquired Belgium-based Custodix NV and its InSite network. InSite network is a European-based provider of services for clinical trial design, patient feasibility, and enabling workflow for patient recruitment. Financial details of the acquisition were not disclosed.
InSite Clinical Data Network Background
The InSite platform is an
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Real World Evidence (RWE)
TriNetX Lands $40M to Expand Global Health Research Network
TriNetX, a Cambridge, MA-based global health research network that optimizes clinical research and enables discoveries through the creation of real-world evidence (RWE) has raised $40 million in Series D funding. The Series D funding round was led by Merck Global Health Innovation Fund (Merck GHIF) along with new investors Mitsui & Co., Ltd., ITOCHU Technology Ventures, ITOCHU Corporation, and existing investors MPM Capital, F2 Ventures, and Deerfield Management. To date, TriNetX has raised
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The State of EHR Data in the Midst of The Real-World Evidence Evolution
It’s time to search for answers beyond the structured fields of your EHR. Dan Riskin explains.“Wave” is a perfect word to describe the swell that is big data because it’s quite oceanic in the sense that it’s everywhere, but that doesn’t mean it’s readily consumable. Ubiquity is both the critical asset and challenge that big data brings to healthcare. It’s also the muse that has innovators not just thinking outside the box when it comes to creating HIT solutions but searching for valuable data
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VMT Lands Grant to Enable Accurate Extraction of Clinical Outcomes from Real World Evidence (RWE)
The National Science Foundation, today announced a grant to VMT for developing technology focused on pragmatic clinical trials allowing clinical outcomes to be extracted from real-world data. VMT is a medical technology incubation firm, developing and commercializing cutting-edge healthcare products to address critical healthcare needs. The approach uses artificial intelligence to dive deep into the electronic health record (EHR) for outcome data to enable EHR-based pragmatic clinical trials.
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