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Health Intelligence


In recent years, front-runners in the pharmaceutical industry have trusted on data-science to guide   their decision-makers. By integrating the data and applying useful algorithms, sponsors can benefit from the extensive data insights needed to make research projects more responsive and flexible. It is important to heighten these efficiencies using the sophisticated tech-enabled solutions and best in analytics platforms to tweak, analyze and pull large amount of data.

Our statistical experts have vision to exploring and evaluating data; model development and validation; examining research patterns and generating data insights. After all they are the responsible for effective communication of the results in a meaningful way that impacts decisions of the client.

AI/ML problem solving

Artificial intelligence (AI) and machine learning (ML) are rapidly growing disciplines within the life sciences industry. AI/ML has been adopted by those needing access to deeper market insights to craft real-world data (RWD) driven strategies with speed and precision. It provides evidence-based insights that can reveal complex patterns like those found in patient behaviors, health outcomes, and sales, that were previously undetected.

Classical statistics, a subfield of mathematics, almost always starts with a hypothesis and generally assumes that some structural relationship exists in the data. It uses probability theory and underlying distributions. For life sciences companies, understanding the pros and cons of both classical statistics and AI/ML is important when investing in your business. Classical statistics and machine learning need to co-exist.

PHARMA-STATS Subject Matter Experts (SMEs) are known for being well-equipped to handle problems of life science from AI/ML and deep learning. We have deep knowledge of the healthcare industry and regulatory requirements.

Our SMEs are skilled analytic professional statisticians with the clinical domain expertise to understand sponsors’ structured/unstructured data.

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