Department of Drug Design and Pharmacology

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.

Main focus

The PharmaDS 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, PharmaDS will:

Synergise strong drug-related research with strengthening of big data science.
Establish infrastructure and support for swift integration of big datasets from Pharma DS, 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 in the Pharma DS team
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

Data science research groups

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.

Courses that include Data science

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 Biostructural Chemistry	AI in Drug Discovery, training and evaluating classifiers	Michael Gajhede
MSc	10-20	Big Data, Artificial Intelligence and Machine Learning in Drug Safety	Big Data/AI/ML in Drug Safety	Morten Andersen & Maurizio Sessa
MSc	30-40	Structure-based Drug Research	Predictive modelling, Naive Bayes, regression, evaluation metrics for predictive models	Albert J. Kooistra & Annette E. Langkilde & Karla A. Frydenvang
PhD	20-30	Personalised Medicine	Data analysis and visualization, variant effect prediction	José Moreira & Alexander S. Hauser
PhD	20-30	Register-based research: Pharmaco-epidemiology - drug use and safety	Pharmaco- epidemiology	Morten Andersen
PhD (ULLA consortium)	60	Artificial intelligence in Drug Discovery	Data handling, supervised/ unsupervised ML, dimensionality reduction, PCM modeling, image processing and analysis, and more	Albert J .Kooistra (KU) & Gerard J.P. van Westen (Leiden University) & Ola Spjuth (Uppsala University)

Publications

HeaDS lists additional data science groups, courses and resources at the Faculty of Health and Medical Sciences.

Data science team leader

Albert J. Kooistra
Associate Professor

Phone +45 35 32 83 05
albert.kooistra@sund.ku.dk

Data science team members

The data science team combines data science research groups and course managers to facilitates data science across research and teaching.

Name	Title	Image
Albert Jelke Kooistra	Associate Professor
Alexander Sebastian Hauser	Associate Professor
David E. Gloriam	Professor
Karla Andrea Frydenvang	Associate Professor
Maurizio Sessa	Associate Professor
Morten Andersen	Professor
Tommy Nørskov Johansen	Associate professor, Head of Studies
Trine Meldgaard Lund	Associate Professor