Using Natural Language Understanding to Solve Pharma’s Big Data Problems

Clinical Trials, Drug Safety, Life Sciences, Pharmaceutical,
  • Monday, July 30, 2018

Pharma has a big text problem, including lots of useful information buried in unstructured data formats that is difficult to use. Natural language understanding (NLU) will help to turn what was once unusable data into meaningful insights that can be applied to the clinical trial development continuum. NLU engines also open up the possibility for users to have a more interactive relationship with their vast data stores using speech or chat messaging in a conversational experience.

Join this webinar to see how natural language understanding can be used to solve problems, including:

  • Tracking adverse events in the real world and clinical trials
  • Better matching patients for ongoing clinical trials
  • Uncovering hidden associations from interactions between physiology, therapies, and clinical outcomes

Speakers

Karim Damji, SVP Product Management and Marketing, Saama Technologies

Karim joined Saama from Plantronics where he led software strategy and product management, focusing on driving developer platforms, strategic partner integrations and contextually enabled UC solutions. Prior to joining Plantronics, Karim served in leadership positions spanning business development, product management, sales and network engineering at Cisco, Vocera Communications, MobileIron and DiVitas. Karim spent 7 years at Cisco building global VoIP and WAN networks, eventually transitioning to product architecture positions. At Vocera Communications and DiVitas, Karim was the founding head of products responsible for driving product concept to market-leading solutions.

Karim has served as a founder and strategic advisor to early-stage startups and is currently involved in mission-driven startups and IoT open-source communities. Karim studied computational and applied mathematics at San Jose State University.

Message Presenter

Malaikannan Sankarasubbu, VP of AI, Saama Technologies

Malaikannan Sankarasubbu is the VP of AI Research in Saama Technologies. He is currently working on optimizing and accelerating clinical trials using artificial intelligence. He specializes in deriving insights with unstructured data like text and images. He previously was Founder and CTO for Datalog.ai, creators of MyPolly, a chatbot building platform with its own natural language understanding engine where he built a community of 1,200 active developers, aka chatbot builders, around MyPolly. Malaikannan was part of the Enterprise Architecture team in Optum and Cognizant Technology Solutions. He understands healthcare and is passionate about advancing more applications of deep learning in healthcare and life sciences. Malaikannan loves building communities; he, along with a few others, built a community around Keras and he also created an active forum Indian deep learning initiative which has over 4,500 members. Malaikannan actively shares his knowledge in Meetups and conferences and loves to blog about artificial intelligence at malaikannan.io.

Message Presenter

Who Should Attend?

This webinar will benefit large to medium mid-market pharma/biotech companies and CROs conducting Phase I-IV clinical studies.

Relevant job titles include:

  • Heads of Clinical Operations, Development, Research, Strategy, Planning, Regulatory Affairs
  • Chief Medical Officers

What You Will Learn

Join this webinar to see how natural language understanding can be used to solve problems, including:

  • Tracking adverse events in the real world and clinical trials
  • Better matching patients for ongoing clinical trials
  • Uncovering hidden associations from interactions between physiology, therapies, and clinical outcomes

Xtalks Partner

Saama Technologies

Saama Technologies is the advanced data and analytics company delivering actionable business insights for life sciences and the Global 2000. Saama is singularly focused on driving fast, flexible, impactful business outcomes for its clients through advanced data and analytics. Saama’s unique “hybrid” approach integrates focused solutions and expertise across the life sciences domain, business consulting, machine learning, automated data management, cloud and big data technologies. Saama’s approach integrates manual and disconnected data initiatives into a well-aligned roadmap facilitating the client’s journey from strategy through solution implementation.

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