ENBIS-25 Conference

Session

Statistics in Pharma and Health Care

17 Sept 2025, 10:05

Amphitheater 002 (Ground floor)

Conveners

Statistics in Pharma and Health Care: 1

• Sotiris Bersimis (University of Piraeus, Greece)

Statistics in Pharma and Health Care: 2

• Marco P. Seabra dos Reis (Department of Chemical Engineering, University of Coimbra)

11. Utilizing Finite Mixture Models to identify machine reading errors in the context of Continuous Manufacturing

Chellafe Ensoy-Musoro (Johnson & Johnson)

17/09/2025, 10:05

Statistics in Pharma and Health Care

Continuous manufacturing (CM) in the pharmaceutical sector integrates the various discrete stages of traditional batch production into a continuous process, significantly decreasing drug product manufacturing time. In CM, where all process units are directly linked, it is crucial to continuously monitor the current process state and maintain consistent product quality throughout...

52. Quality by Design challenges in Pharma 4.0

Daniel V. Batista (University of Coimbra, CERES, Department of Chemical Engineering, Coimbra, Portugal), Marco P. Seabra dos Reis (Department of Chemical Engineering, University of Coimbra)

17/09/2025, 10:25

Statistics in Pharma and Health Care

The landscape of the pharmaceutical industry is evolving. From what was (and still is) a science-centered discipline, more awareness exists nowadays of the opportunities arising from exploring data-driven methodologies to conduct various key activities. In this regard, Chemometrics has been an old-standing ally of the pharmaceutical industry, allowing for real-time assessment of raw materials,...

109. Adaptive EWMA and CUSUM Control Charts for Monitoring Disease Prevalence in Meta-Analytic Studies

Athanasios Sachlas (University of Thessaly)

17/09/2025, 10:45

Statistics in Pharma and Health Care

Monitoring disease prevalence over time is critical for timely public health response and evidence-based decision-making. In many cases, prevalence estimates are obtained from a sequence of independent studies with varying sample sizes, as commonly encountered in systematic reviews and meta-analyses. Traditional control charts such as the EWMA and CUSUM have been widely used in industrial...

26. Shiny-for-Python Multivariate Outlier Detection App

Charles Tothill (Johnson & Johnson)

17/09/2025, 14:00

Statistics in Pharma and Health Care

In pharmaceutical statistics, traditional outlier detection often focuses on univariate methods. However, a multivariate approach is essential for analysing complex datasets representing critical quality attributes, such as assay, dissolution, and disintegration time.
The Shiny-for-Python application described here employs advanced machine learning techniques, specifically Principal...

105. Methods for meta-analysis of EC50/IC50 curves: a valuable tool for decision making in pharmaceutical research

Mrs Elisavet Andronidou (University of Thessaly)

17/09/2025, 14:20

Statistics in Pharma and Health Care

An important parameter in pharmacological research is the half-maximal inhibitory concentration (IC50/EC50), which quantifies the potency of a drug by measuring the concentration required to inhibit a biological process by 50%. The 4-parameter logistic (4PL) model is widely employed for estimating IC50/EC50 values, as it provides a flexible sigmoidal fit. Meta-analysis on the other hand, has...