Robertino Mera-Giler MD PhD

Experienced Data Science Leader - Driving results through advanced methodology which generates Real World Evidence

Raleigh, NC

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About

As a strategy-driven Data Science Leader with a strong and consistent track record of success in helping companies to achieve their goals in the healthcare field, I am a biostatistician, physician, and epidemiologist who possesses deep experience in overseeing teams in data analytics, in building predictive machine learning/ artificial intelligence models, and in multidisciplinary problem-solving. I revel in the challenge of accomplishing goals through novel statistical method development and multidimensional data approaches. During my career, I have successfully overseen the development of production-level enterprise applications. In addition, as a leader, I have managed several employees while earning a reputation as an empowering leader. A few of my recent successes include: ► Presented a statistical model using RWE showing that HIV pre-exposure prophylaxis (PrEP) was the most important factor in the decline of the incidence of HIV cases in the United States from 2012-2017; showcased this model at the largest peer-reviewed HIV meeting (IDWeek) in 2019. ► Demonstrated that using an appropriate data model in a semi-automated approach can yield the efficient and rapid evaluation of safety signals. ► Described a complex statistical model for antimicrobial resistance based on mathematical models of bacterial transmission; this model provided a novel explanation of current and future trends.

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Biostatistics, Epidemiology, Computer Science, Medicine, Oncology, Infectious Diseases, Virology
Aetion
Work experience
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Feb 2012 - Dec 2020

Gilead Sciences

Executive Director of Real World Evidence / Machine Learning

In this role, I created an RWE group that utilized a data warehouse and a Hadoop data lake to carry out multiple studies using an innovative statistical methodology. I introduced in-database analytics geared toward large amounts of data, and I also added interpretable machine learning algorithms. I additionally created models that can be applied to adverse events and health outcomes. Furthermore, I developed RWE applications for risk identification and the assessment of outcomes/ efficacy given various exposures. ►One of my major achievements in this role is that I used 30+ global PrEP implementation projects over six years to establish that HIV seroconversion rates in PrEP program conditions are significantly better than those in clinical trials. I presented this result at a peer-reviewed meeting, emphasizing that the implementation of PrEP works well at the program level. ►I also helped to significantly reduce the number of false positives over the course of three years by developing a Bayesian methodology for detecting safety signals in large databases.

Aug 1998 - Jan 2012

GlaxoSmithKline Pharma GmbH

Project Leader and Director, Research Statistics

Led the development of novel methods and software to evaluate safety signals using large observational databases. Created a statistical model for gram-negative antimicrobial resistance that predicted the prevalence of resistance to many antimicrobial classes

Apr 1990 - Apr 1998

Louisiana State University Health Sciences Center

Assistant Professor

Designed a clinical trial and a cohort study for the study of the H. pylori effect on populations at high risk of gastric cancer. Served as the lead biostatistician /epidemiologist for two Research Program Projects National Institutes of Health grants

Education

1990 - 1995

Tulane University

PhD, Biostatistics / Epidemiology

Minor in Computer Science

1987 - 1989

Tulane University

MSc, Public Health, Computer Science

Minor in Computer Science

1979 - 1984

Catholic University

MD, Medicine / Surgery

Infectious Diseases

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