From code to client: Lea’s journey at idalab

Lea Helmers joined idalab as a data scientist in early 2016. With degrees in Mathematics, Computer Science and Linguistics, she was destined to specialize in Natural Language Processing (NLP). Her three-year journey at idalab has been a powerful testament of the data scientist’s potential to maximize value for clients by combining data science tools with strategic and conceptual thinking. We asked Lea about how this evolution took place, and how she’s coped with it on a personal level.

“Data is a small part of the story”: a glimpse into the life of a data scientist

Hagen Hoferichter is a data scientist, but not just any data scientist. He specializes in the intersection of Machine Learning and embedded devices in the IoT world. Instead of being an obstacle, Hagen’s background as an Electrical Engineer gives him a unique edge when it comes to creating innovative data-gathering devices together with clients. Based on extensive experience working with clients from the healthcare sector, Hagen categorically emphasizes that data science work is more than just programming or number crunching. The most crucial part of his work consists of explaining data science to clients and exchanging expertise to ultimately enable him to create groundbreaking solutions. We met up with Hagen to find out about the most essential ingredients that allows a data scientist to solve intractable client problems.

Structuring, connecting and discovering knowledge: Our biotech NLP platform helps to identify therapeutic targets from millions of scientific papers

In biomedicine, much of the information generated is made publicly available by and to the scientific community. These open data resources are attracting significant attention, as the pharmaceutical industry finds itself continuously under pressure to speed up the costly process of drug discovery.

idalab seminar #12: The data-privacy dilemma: How full homomorphic encryption could bring healthcare into the digital era

Imagine this: The key to better cancer treatments is within reach, based on patterns from data that is scattered across various locations all over the world. This data could be digitalised, labelled, collected, stored and interpreted. However, this data belongs to a countless number of individuals – and their right to data privacy weighs just as much as the dream of curing a lethal disease.

The Data behind Altered States of Consciousness: Interview with Timo Torsten Schmidt

When we want to grasp the subjective experiences of others, we count on their verbal accounts. Limited to language, quantifying how something feels for an individual is very hard. It is even more arduous for altered states of consciousness where descriptions become somewhat metaphorical.

idalab seminar #10: Precision Medicine – How to Identify Biomarkers that Help Patients Choose Their Best Treatment Option

In idalab seminar #10, we turn to the field of Precision Medicine. Dr. Nicole Krämer from Staburo GmbH will give a talk on how Data Science can help physicians to predict a patient’s reaction to a certain treatment in advance.

idalab seminar #9: When you’re Sick, Please Stay at Home – Making Sense of Spreading Phenomena using Human Contact Data

The next idalab seminar will take place on Friday April 27th at 5pm, as always in our office at Potsdamer Straße 68. We will host a talk by Benjamin F. Maier, PhD student at the Robert Koch Institute and freelance data scientist.

Data Science for Pharma – A Short Case Study

Open data in biomedicine is a gold mine that can strengthen innovation in pharmaceutical R&D. In combination with the right analytics, public data helps identify therapeutic targets and ligands, enhance clinical development, and boost portfolio management efficiency. The challenge is to purposefully integrate abundant and heterogeneous data scattered across data sources.

Navigating the Biomedical Data Landscape – Part II

Data science is revolutionizing pharmaceutical R&D; and knowing how to navigate the open data landscape is key to the revolution.