White Paper

How An AI/ML Data Strategy For Life Sciences Can Deliver Better Business Outcomes

Source: IQVIA Technologies

By Gary Shorter, Head of Artificial Intelligence and Data Science, IQVIA Technologies


There is a definitive and unmet need in clinical trials to “re-imagine” the clinical data environment with an aim to verify data integrity and quality while improving productivity, efficiency, and transparency. This need stems from the tidal wave of data that has been created by the exponential growth in data sources and data collection technology in the life sciences and healthcare industry. Patients, physicians, insurers, technology companies, and the public are generating reams of healthcare data every day.

What has been clear across the pharmaceutical industry is the need to adapt and evolve with the ever-changing environment of life science data. A new data strategy that includes data science will require:

  • Technology to support rapid and automatic ingestion of data
  • Compliant and collaborative data science tools
  • Data science expertise with life sciences domain knowledge

Data science and Artificial Intelligence / Machine Learning (AI/ML) driven predictive and prescriptive insights can help research teams cut the time and cost of clinical trials while accelerating new drugs to market. But the only way to uncover insights is by rethinking how data management and research gets done.

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