
We're at the epic center of another revolution in healthcare and science; Data-Driven Real-World Evidence has become industry standard in both Life Sciences and Healthcare disciplines. Many companies today invest tens of millions of dollars in an attempt to build Real World Data-Platforms internally, and there are many who understand that partnering and licensing with mature platforms for that purpose is the ideal way to keep up in the current 'RWE-arms race'.
Data2Life is unique in its landscape for being the first to create a truly holistic, Patient-inclusive, Real-World-Data platform. To be able to put together both physician clinical reporting in medical records side by side to patient-reported outcomes spontaneously generated in online groups, there is some 'heavy machinery' applied to continually collect and process these (big) data assets, handle the unstructured data within, and create medical specializing machine learning algorithms to 'understand' it.
Data2Life's proprietary 'Diagnostic-NLP' (Natural Language Processing) understands patient- jargon and maps it to common medical data models. It has a distinctive superiority compared to other RWE platforms.
"Predominantly, Data2Life changes the old paradigm of how we attain Evidence, into Patient-Inclusive Evidence. Taking on itself to standardize 'patient voice' and transforming it into a usable form, aligned to industry standards, leaving no excuses to keep this data-dimension out of the RWE data-play. We are now forming the Next-Generation of how we do Science and Medicine, and now is the ideal time to have an AI-powered, Patient-Centric, Holistic, and Personalized Evidence," says Limor, Co-founder of Data2Life.
Started five years ago and until today, Data2Life distinctive offering is unmatchable. The company's vision and high-quality implementation of the Patient Inclusive cross-validated with a clinical data type of Evidence is what makes the company shine in its competitive landscape.
Limor feels disrupting institutionalized processes and methods in a highly regulated market poses a challenge, especially for an upstart company needing to bare the long-slow sales cycles that can go beyond 18 months and handling the early days of changing regulation and the market education.
Data2life is a partnership unto itself, which Limor founded together with her business partner and friend Dr. Itzik Lichtenfeld. She feels working in such settings makes one highly sensitized to the crucial but fragile significance of strategic partnerships. Being a disruptive startup company, operating in the densely consolidated and regulated arena of pharmaceutical and healthcare players, Data2Life had to find a foothold in the industry, one that would grant the company access to the larger incumbents. Data2Life's initial strategic partnerships were signed with one of the largest EHR (Electronic Healthcare Records) owner globally, granting the company access to a staggering medical database containing decades of records from the various healthcare encounters (clinics, hospital, procedures, prescriptions and more). This partnership granted Data2life the ability to compare and validate signals raised by patient's spontaneous reporting to the gold standard of RW-data(Clinical Records).
"In the midst of it all, are the investors who have decided to partner with us, and part with their funds, with faith in the potential and value of the innovation that we're creating," she added.
Limor BH Epstein is the founding mother of Data2Life; a Real-World Evidence Pioneer, harnessing technology and the abundance of health data we all generate to create the Next-Gen of 'Evidence Based Medicine'.
Limor brings a good mix of Clinical knowledge (Emergency medicine), Research methodologies (Epidemiology), Health policy understanding (Public Health), and Information Technology practices (Medical Informatics) with her.
She is a social data geologist, passionate about data and how it could serve the industry in driving key decision making and keen to use the latest (and greatest) technology as an enabler for data processing and analyses.
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