PRIME Analytics is a consultancy for pharmaceutical companies, research organizations, and data vendors. We design and run studies on claims and health records data, from protocol to final tables.
We turn large healthcare datasets into evidence on how treatments are used and what happens to patients who take them.
Study protocols, data quality assessment, cohort design, and statistical analysis of claims and electronic health records data, covering safety, effectiveness, and disease burden.
How patients start, stay on, switch, and stop therapy. We use methods such as group-based trajectory modeling to find patterns that averages hide.
Health care use, spending, and clinical outcomes, analyzed to support value, access, and reimbursement discussions.
Prediction models and newer methods, including reinforcement learning and large language models, applied where they make the evidence stronger.
Short courses and conference sessions on machine learning, trajectory modeling, and study design for research and analytics teams.
Every engagement starts with a research question and ends with results your team can present and publish.
We agree on the outcome, the population, and the decision the analysis needs to inform.
We assemble and clean the datasets, and document every inclusion rule and definition.
We develop the models or study design, then test them on data they have not seen.
You receive tables, figures, and methods write-ups ready for a manuscript, a conference poster, or internal review, plus the code behind them.
Epidemiology, pharmacy, data science, and operations in one small firm.
Co-Founder and Chief Scientific Officer
Pharmacist and epidemiologist with degrees in pharmacy, biostatistics, and epidemiology. Principal investigator on NIH-funded studies of machine learning for overdose prediction, recipient of an ISPOR HEOR Excellence Award in 2023, and a regular instructor of ISPOR short courses on machine learning.
Co-Founder and Chief Operating Officer
Over 15 years in risk management, internal audit, accounting, compliance, and tax. Leads operations, contracting, financial reporting, and client engagement, and keeps project workflows and deliverables on schedule.
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Principal Data Scientist
Ph.D. in electrical and computer engineering with a background in statistical inference, optimization, and machine learning. Builds prediction systems on healthcare datasets and supports medication utilization and health outcomes analyses in Python, R, and SAS.
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Principal Pharmacoepidemiologist
Over a decade of experience analyzing large Medicaid claims data in SAS, Stata, and R. Focuses on medication therapy patterns and the health and economic outcomes that follow, including insulin therapy among Medicaid beneficiaries with diabetes.
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