Showing 131-135 of 147 researchers:
OM1 Lupus Registry Reaches More Than 25,000 Patients Prospectively Followed With Deep Clinical And Lab Data

OM1 LUPUS REGISTRY REACHES MORE THAN 25,000 PATIENTS PROSPECTIVELY FOLLOWED WITH DEEP CLINICAL AND LAB DATA Ready for collaborations, the registry enables faster, more cost-effective access to research-grade lupus data for better understanding, comparing, and predicting treatment outcomes BOSTON, October 17, 2018 — OM1, a leading health outcomes, registries and technology company creating solutions to[…]

Aug 30 – Next Generation Registries: Big Data, Advanced Analytics, More Dynamic Evidence

August 30, 2018 – 2:00 – 3:00 pm ET Registries continue to be a critical part of the real-world evidence equation, but over time they have become too trialized, too burdensome, and too separated from real clinical practice. Emerging methodologies, data digitization, and cognitive technologies have set the path for drastic changes needed to address[…]

Achieving a Win-Win for Pharma and Payers in Contracting Agreements

Published on PM360, April 2, 2018 The shift to value-based care and outcomes contracting type programs present the opportunity to align stakeholder interests around value and demonstrate a commitment to improving clinical and cost outcomes. From earlier detection to more precision management, the opportunities for pharma to partner around outcomes and value are growing. Win-wins[…]

Using Big Data Like Biomarkers to Advance Clinical Development & Commercialization

March 28, 2018 – 2 PM ET What if you could use predictive models like biomarkers to pre-emptively screen and more effectively target patients who are more likely to respond to your drug in trials and in practice? What if you could rapidly answer questions on comparative treatment outcomes and predict those most likely to[…]

Artificial Intelligence for Real-World Evidence

Published on HealthEconomics.com on January 3, 2018   As artificial intelligence (AI) and Big Data are lauded for their potential uses in life sciences and healthcare, it is becoming difficult to differentiate between the myriad of terms and technologies and their real value in advancing real-world evidence (RWE).   In this article, we explore key AI[…]

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