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Spur Pharmaceutical Insights with NLP and Anonymization Services
Are you realizing the full value in your organization’s sensitive data?
Extracting the value from unstructured data and addressing privacy concerns are common challenges organizations face when trying to glean insights from data. Advancements in artificial intelligence and machine learning (AIML) have led to natural language processing (NLP) and anonymization capabilities that overcome these challenges and empower organizations to safely innovate with data.
Join IQVIA’s Linguamatics and Privacy Analytics teams as we explore ways in which pharma sponsors have used NLP and statistical anonymization to help:
Jane Reed is Director, Life Sciences, at Linguamatics, an IQVIA company. She is responsible for developing and leading the strategic vision for Linguamatics’ product portfolio and business development for the pharma and biotech market. Jane has 20+ years’ experience in vendor companies supplying data products, data integration and analysis and consultancy to pharma and biotech – with roles at Instem, BioWisdom, Incyte, and Hexagen. Before moving into the life science industry, Jane worked in academia with post-doctoral positions in genetics and genomics research.
Jane Reed, PhD
Director of Life Sciences at Linguamatics, an IQVIA Company
Sarah helps Privacy Analytics’ clients earn trust and execute on their use priorities. Her career has often involved developing and implementing innovative risk assessment methodologies for governments and Fortune 500 companies. She has worked with decision makers at the highest level to identify and address financial, political and/or reputational risk before any harm could be done to the organization. Her previous roles include Partner and National Privacy Services Leader at MNP LLP, COO of A Hundred Answers Inc., and IT Risk Advisory Practice Lead for Ernst & Young Ottawa.
Sarah Lyons
Head of Privacy Analytics
Situation: California’s Consumer Privacy Act inspired Comcast to evolve the way in which they protect the privacy of customers who consent to share personal information with them.
Situation: Integrate.ai’s AI-powered tech helps clients improve their online experience by sharing signals about website visitor intent. They wanted to ensure privacy remained fully protected within the machine learning / AI context that produces these signals.
Situation: Novartis’ digital transformation in drug R&D drives their need to maximize value from vast stores of clinical study data for critical internal research enabled by their data42 platform.
Situation: CancerLinQ™, a subsidiary of American Society of Clinical Oncology, is a rapid learning healthcare system that helps oncologists aggregate and analyze data on cancer patients to improve care. To achieve this goal, they must de-identify patient data provided by subscribing practices across the U.S.
Situation: Needed to ensure the primary market research process was fully compliant with internal policies and regulations such as GDPR.
Situation: Needed to enable AI-driven product innovation with a defensible governance program for the safe and responsible use
of voice-to-text data under Shrems II.
This course runs on the 2nd Wednesday of every month, at 11 a.m. ET (45 mins). Click the button to register and select the date that works best for you.