Mathias Goeschl – Molecular Health GmbH

Vice President Digital Content

Mathias Goeschl – Molecular Health GmbH

Dr. Goeschl has been active in life science information technology for the past 20 years.  He pioneered industry applications in a number of areas, including early computational genomics and systems biology applications, consumer applications in clinical IT, and eventually the application of big data analysis to precision medicine.

Mathias holds a PhD in Physics from Grenoble University (France) and joined LION bioscience AG in 1997.  He made significant contributions in the development of LION’s genome analysts platform and led global teams in R&D and product marketing.

Before joining Molecular Health in 2007, Dr Goeschl worked with InterComponentWare AG on the definition and introduction of consumer-facing electronic health records and tele-medicine applications within Germany’s national eHealth initiative. 

As Vice President of Digital Content at Molecular Health, Dr. Goeschl is leading the company’s efforts towards knowledge discovery and content production on an industrial scale, overseeing the market and technical requirements for the entire range of Molecular Health precision medicine solutions.

Content development technology & strategy for ‘smart’ applications in regulated and exploratory medical environments

Session Full Description

The dynamic increase in the availability of personalized genomic information and the large amount of research published in this field offer strong opportunities in engineering a broad range of semantically rich digital knowledge from text sources. Centered on genetic variants, this comprehends details of clinical phenotype, drug treatment and observed clinical outcome. Fundamentally, such information supports the entire value chain of medication: From pre-clinical research to clinical trials and eventually to treatment decisions made in the clinical practice. In this market, to support the seamless use of IT applications to deliver the right piece of information in response to a specific expert question, we generally identified the need for a canonical knowledge repository and reference system. The use of this repository is illustrated on both its ‘input’ (content engineering) and ‘output’ (application) side. In an industrial setup, content engineering needs to balance manual data curation vs. automated content extraction, and data quality vs. data coverage. We will therefore demonstrate the use of text-analytics AI and a collaborative data-curation platform in support of content production. Furthermore, commercial applications will be portrayed, ranging from a ‘medical device’ certified for evidence-based treatment decision support to an AI system to predict and analyse the likelihood of success of clinical trials.

Actionable Takeaway #1

get insights into content development for a complex clinical application

Actionable Takeaway #2

leverage expert data curation together with AI-driven information extraction

Actionable Takeaway #3

share a vision on how medicine will evolve in a data & AI-driven environment