HeaDS lists additional data science groups, courses and resources at the Faculty of Health and Medical Sciences.
Data Science
Pharmaceutical sciences have traditionally been driven by experimental observations. However, the recent development within data science has enabled totally new ways to understand drug related research data. Pharma DS is leveraging big data challenges within multiple research areas ranging from drug effects at a receptor level and biological effects of the drug, to design of medicinal products and observational patient data.
Data science at ILF is made up by a team of data scientists and course managers that will strengthen the data science as an element across research and teaching. Specifically, we will:
- Synergise strong drug-related research with strengthening of big data science.
- Establish infrastructure and support for swift integration of big datasets, large scale research infrastructures and other public resources.
- Tailor big data into existing and new courses to fill an educational need of the life science industries.
- Increase the accessibility of data science expertise and resources to scientists.
- Profile our research data, e.g. via online research hubs developed.
- Complete the integration of databases with person-sensitive information and allow linkage in secure environments, e.g. Statistics Denmark and the Danish Health Data Authority
- Facilitate the access to larger data science infrastructures, e.g. Computerome and other European computer clusters
Computational Receptor Biology; Professor Gloriam, David E.
Manufacturing and Materials, Professor Jukka Rantanen
Pharmacometrics; Associate professor Trine Meldgaard Lund
Pharmacovigilance Research Center; Professor Andersen, Morten
Data Science for Drug Design; Associate Professor Kooistra, Albert J.
Drug-related Data Science; Associate Professor Hauser, Alexander S.
| Level | No. stud | Title | Data Science element | Course leader |
| BSc | >200 | Cellular and Molecular Biology |
Python, Jupyter notebooks, simulation of cellular processes |
Osman Asghar |
| BSc, MSc |
50 | Pharmaceutical Modelling | Machine learning and multivariate data analysis |
Anders Ø. Madsen |
| MSc | 25 | Pharmaco- epidemiology and Pharma- covigilance |
Pharmaco- epidemiology |
Morten Andersen & Maurizio Sessa |
| MSc | 20-30 | Advanced Manufacturing of Pharmaceuticals |
Exploratory data sciences and data mining |
Jukka Rantanen |
|
MSc |
>200 |
Medicinal and |
AI in Drug Discovery, training |
Michael Gajhede |
|
MSc |
10-20 |
Big Data, |
Big Data/AI/ML |
Morten Andersen & Maurizio Sessa |
|
MSc |
30-40 |
Structure-based |
Predictive modelling, |
Albert J. Kooistra & Annette E. Langkilde & Karla A. Frydenvang |
|
PhD |
20-30 |
Personalised |
Data analysis and |
José Moreira & Alexander S. Hauser |
|
PhD |
20-30 |
Register-based research: |
Pharmaco- |
Morten Andersen |
|
PhD |
60 |
Artificial intelligence |
Data handling, |
Albert J .Kooistra (KU) & Gerard J.P. van Westen (Leiden University) & Ola Spjuth (Uppsala University) |