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In our Data & Analytics Thought Leader Series, Datavant’s Head of Data Strategy, Su Huang, interviews leaders who are advancing data-driven use cases at their organization. This interview is with Sid Jain, Head, Global Development, Data Science at Janssen Research & Development, LLC. At Janssen, Sid and his team are focused on using data science tools and technologies, like artificial intelligence (AI) and machine learning (ML), to accelerate clinical development, with a commitment to not only making drug development faster, better and more efficient – but also making science possible that was not possible before.

In our Data & Analytics Thought Leader Series, Datavant’s Head of Data Strategy, Su Huang, interviews leaders who are responsible for defining the teams and processes for managing data and advancing data-driven use cases at their organization. Today’s interview is with Paul Petraro, Executive Director and Global Head of the Real World Evidence Analytic (RWE) Center of Excellence at Boehringer Ingelheim.

In our Data & Analytics Thought Leader Series, Datavant’s Head of Data Strategy, Su Huang, interviews leaders who are responsible for defining the teams and processes for managing data and advancing data-driven use cases at their organization.  Today’s interview is with Jane Urban, Senior Director of Commercial Data Management and Strategy at Takeda Pharmaceuticals.

In our Data & Analytics Thought Leader Series, Datavant’s Head of Data Strategy, Su Huang, interviews leaders who are responsible for defining the teams and processes for managing data and advancing data-driven use cases at their organization.  Today’s interview is with Anthony Philippakis, Chief Data Officer at the Broad Institute.

Life science companies have been burdened by lack of integration between internal and external data silos. Despite having access to various datasets for the same patient population, there has been no way to create a complete picture of the patient journey.

Conducting burden of illness studies and cost-effectiveness research is challenging without data that captures a patient’s complete journey from primary care to specialty clinics and inpatient care.

The benefits of leveraging real-world data (RWD) in clinical research are increasingly recognized and endorsed by regulators. As with any innovation, there is a gap between RWD availability and effectively leveraging the data, especially in the context of a randomized controlled trial (RCT).  One answer to this conundrum is to tokenize clinical trials data to enable connectivity to RWD. This webinar will focus on the operational processes to implement tokenization within a clinical trial to enable the ability to link to real–world data to answer research questions which could not previously be answered from traditional RCT designs.

Conducting burden of illness studies and cost-effectiveness research is challenging without data that captures a patient’s complete journey from primary care to specialty clinics and inpatient care.