ER Andrinopoulou

Biography

I am currently a Statistics & Mathematical Modelling Director at GSK, where I focus on refining statistical methodologies and implementing predictive modelling to optimize disease strategy and healthcare outcomes.

Previously, I was an Assistant Professor in Biostatistics at Erasmus MC, where I taught fundamental statistical methods, provided statistical consulting to clinical collaborators, and developed innovative methodologies for analyzing complex data.

My research centers on developing cutting-edge statistical methods to dynamically predict and analyze large-scale data by integrating diverse sources, including environmental factors, community characteristics, imaging, and registry data, to generate novel insights.

I am passionate about bridging the gap between statistics and healthcare innovation, and I welcome opportunities for collaboration.

Interests

Longitudinal analysis
Joint models of multivariate longitudinal and survival data
Dynamic predictions
Bayesian Methods
Data integration
Environmental data
Multi-model

Education

PhD in Biostatistics, 2014

Erasmus University Medical Center, Rotterdam, the Netherlands
BSc in Statistics, 2010

Athens University of Economics and Bussines

The increasing availability of clinical measures (e.g., electronic medical records) leads to collecting different types of information. …

Eleni-Rosalina Andrinopoulou

Statistics Director

GSK

Biography

Interests

Education

Selected Publications

A joint model for (un)bounded longitudinal markers, competing risks, and recurrent events using patient registry data.

Efficiently analyzing large patient registries with Bayesian joint models for longitudinal and time-to-event data.

Lung Function Decline in Cystic Fibrosis. Impact of Data Availability and Modeling Strategies on Clinical Interpretations

Association between changes in pulmonary function and in patient reported outcomes during enzyme therapy of adult patients with late-onset Pompe disease

Statistical primer - an introduction to the application of linear mixed-effects models in cardiothoracic surgery outcomes research. A case study using homograft pulmonary valve replacement data.

Computerised patient-specific prediction of the recovery profile of upper limb capacity within stroke services. The next step.

Reflections on modern methods. Dynamic prediction using joint models of longitudinal and time-to-event data.

A Bayesian joint model for zero-inflated integers and left-truncated event times with a time-varying association. Applications to senior health care.

Individualized Dynamic Prediction Model for Patient-Reported Voice Quality in Early-Stage Glottic Cancer.

Multivariate joint modeling to identify markers of growth and lung function decline that predict cystic fibrosis pulmonary exacerbation onset Outcomes.

Integrating Latent Classes in the Bayesian Shared Parameter Joint Model of Longitudinal and Survival Outcomes.

Improved dynamic predictions from joint models of longitudinal and survival data with time-varying effects using P-splines.

Bayesian shrinkage approach for a joint model of longitudinal and survival outcomes assuming different association structures.

Combined dynamic predictions using joint models of two longitudinal outcomes and competing risk data.

Joint modeling of two longitudinal outcomes and competing risk data.

An introduction to mixed models and joint modeling: analysis of valve function over time.

Projects

Investigate the natural progression and assessing the treatment effectiveness on lung function decline with the US Cystic Fibrosis Foundation Patient Registry

Unveiling the Impact of Social and Environmental Determinants of Health on Lung Function Decline in Cystic Fibrosis through Data Integration using the US Registry

Personalised dynamic prediction of the recovery profile of upper limb capacity within stroke services

Recent & Upcoming Talks

Joint Modeling of (Un)bounded Longitudinal Markers, Competing Risks, and Recurrent Events in Cystic Fibrosis Data

Unveiling the Impact of Social and Environmental Determinants of Health on Lung Function Decline in Cystic Fibrosis through Data Integration using the US Registry

Linking US registry data with geomarker data. Longitudinal associations between environmental factors and lung function decline

Challenges and opportunities in the analysis of clinical data

Estimating Cystic Fibrosis Lung Function Decline: An Empirical Study

PhD students

Teaching

CV

Contact