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David Lorenz is a Manager in the Life Sciences Practice. He specializes in analyzing large, complex data sets in the life sciences industry. Mr. Lorenz has extensive experience applying machine learning, data visualization, and big data processing techniques to extract insights. He has substantial experience supporting counsel and testifying experts with statistical and economic analyses. His work largely focuses on economic analysis of damages for False Claims Act (FCA) matters involving pharmaceutical and medical device manufacturers.


MS, Business Analytics, University of Virginia

BS, Economics, Schreyer Honors College, Penn State University

Selected Work

Selected Experience

  • In New Jersey Primary Care Association, Inc. v. State of New Jersey Department of Human Services, et al., supported the expert in advising the plaintiff regarding the allocation of settlement proceeds among Federally Qualified Health Centers.
  • In In re National Prescription Opiate Litigation, supported testifying experts and counsel with data analysis of marketing and prescribing data to evaluate causation and damages on behalf of a manufacturer defendant concerning allegations of inappropriate marketing of prescription opioids.
  • In United States v. Novartis Pharmaceuticals Corp., supported Dr. Eric Gaier and counsel with analysis of marketing, prescribing, and claims data to assess causation and damages on behalf of Novartis in connection with alleged FCA violations associated with alleged kickbacks concerning Novartis’s promotional events for ten self-administered drugs indicated for hypertension or type 2 diabetes.
  • Supported Dr. Eric Gaier in United States v. Novartis Pharmaceuticals Corp. and BioScrip, Inc. with analysis of causation, damages, and drug adherence on behalf of Novartis.
  • Provided medical device manufacturer facing a government investigation of a diagnostic testing product with statistical analyses. Supported manufacturer in its interactions with the Food and Drug Administration regarding the diagnostic performance of the product.

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