David Di Valentino

David Di Valentino,

CTT Data Scientist

David Di Valentino applies his expertise in data science and data analysis to help clinical trial sponsors maximize the analytical value of their data, while meeting global standards for patient privacy.

Before joining Privacy Analytics, David had an extensive academic research career in particle physics. He published a number of papers, and gained expertise in software development, machine learning and data analysis.

When he decided to move to the private sector, the appeal of applying his skills in machine learning to protecting patient privacy drew David to Privacy Analytics. He is motivated by the fact that his efforts on behalf of trial sponsors ultimately provides members of the public with security and peace of mind when it comes to the safe handling of their personal data.

Working at the intersection of big data analytics, machine learning and regulatory compliance, David has a rare skill set that is ideal for solving the unique problems of our Clinical Trial Transparency (CTT) clients.

In one example, David assisted a client challenged by the requirements for high-volume, high-throughput processing of dozens of studies a month. This included long-form documentation with unstructured data, as well as large volumes of structured data. He took a cross-functional approach with our software engineering teams and CTT methodology experts to simplify and standardize anonymization processes and rigorously test the results.

Not only did this enable the client to meet its throughput requirements, David’s improvements also allowed for monthly capacity to scale even further.

David has also applied machine learning and rules-based approaches to develop automated tools for detecting and classifying personal information in structured clinical data. This has improved the efficiency, accuracy and capacity of our anonymization services offerings for structured clinical data.

“The acquisition and sharing of data for secondary purposes is growing exponentially, particularly in the context of healthcare, and it’s becoming more critical that we develop standards and take steps to ensure privacy,” David says. “Privacy Analytics is in the vanguard of that.”

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