Precision Medicine – How to Identify Biomarkers that Help Patients Choose Their Best Treatment Option

Dr. Nicole Krämer

Principal Statistician
Staburo GmbH

How could Data Science help physicians to predict a patient’s reaction to a certain treatment in advance?

Precision medicine aims at delivering the right treatment at the right time to the right person. This goes hand in hand with a deeper genetic understanding of a patient’s disease. An important milestone is the recent approval of an anti-cancer drug, that was granted by the FDA based solely on a tumor’s biomarker and not on where in the body the tumor started. How can statistics and machine learning help to identify a patient’s best treatment option? I will walk you through a typical Phase II clinical trial in order to discuss the challenge it poses to predict a patient’s response to a treatment that she has not yet received, demonstrate the opportunity of analysing a large set of biomarkers in a clinical trial with relatively few patients, as well as to point out the need to define concrete patient subgroups.

The event took place on May 18th, 2018.

Find Nicole’s slides on SlideShare.

Dr. Nicole Krämer
Principal Statistician
Staburo GmbH

Dr. Nicole Krämer is the project leader Translational Medicine and Biomarkers and a principal statistician at Staburo GmbH. She is responsible for statistical and biomarker analyses in clinical drug development. She works across multiple indications with a focus in oncology and central nervous systems. Dr. Nicole Krämer received her Ph.D. in Statistics and Machine Learning from the Technische Universität Berlin in 2006, and her Diploma Degree in Mathematics from the Universität zu Köln in 2001.