Welcome to the Pharmaceutical Bioinformatics research group at Uppsala University

Principal Investigator: Ola Spjuth, Professor.

Research focus: Intelligent systems with AI and machine learning in drug discovery and chemical safety

The Pharmaceutical Bioinformatics research group focuses on mathematical and statistical modeling, informatics and quantitative analysis of pharmacological systems. We develop methods, algorithms and software to study and model pharmaceutical interactions, and a key focus in the group is how artificial intelligence (AI) and machine learning can aid the drug discovery process; e.g. in drug screening and when studying drug toxicity, metabolism and resistance. We combine in silico and in vitro experiments at the cellular level, and have access to a robotized high-content imaging lab connected to a modern IT-infrastructure to manage and analyze large-scale data. We are involved in several national and international consortia and have a tight connection to the pharmaceutical industry, Uppsala University Hospital, and Science for Life Laboratory. See the Projects page for more information on our ongoing research projects.

We are an interdisciplinary team of researchers engaging in data-driven cell biology, aiming to develop autonomous biological laboratories where data drives decisions on what experiments should be done next, and where automation and AI modeling are core methodologies.

Latests Blog Posts

David Holmberg joins the research group as new PhD Student

3 May, 2021. We welcome David Holmberg who recently started as a PhD Student in our group! David will work in the Autonomous Phenomics project. What is your education, and what have you done earlier in your career? Alright, so I am a graduate from Lund ...

Open PhD student position in Applied Mathematics: Autonomous Decision Making in Automated Cell Profiling for Drug Discovery Applications

22 Feb, 2021. There is now an opportunity to apply for a PhD position in Applied Mathematics with a project from our group with the title: “Autonomous Decision Making in Automated Cell Profiling for Drug Discovery Applications”. The PhD stud ...

Open positions for 2 PhD students and 1 PostDoc in our lab

1 Jan, 2021. After being awarded 2 grants from the Swedish Research Council, we are now strengthening our team to work towards autonomous phenomics and precision cancer medicine.For more information about the project and research group, see https://pha ...

Our HASTE team wins the Adipocyte Cell Imaging Challenge organized by AI Sweden and AstraZeneca

23 Nov, 2020. We are very happy to announce that the HASTE team has emerged as the winners to the Adipocyte Cell Imaging Challenge that was organized by AstraZeneca and AI Sweden as a challenge to the AI community to solve the problem of labeling cell i ...

Open position as Data Engineer in our lab

10 Nov, 2020. We are looking for a skilled Data Engineer to join our team! Tasks In collaboration with other researchers, develop, implement and test systems for AI-controlled automated microscopes. The task includes interacting directly with the micros ...

Swedish Research Council will fund our project 'Autonomous Phenotypic Drug Profiling'

29 Oct, 2020. We are very happy to announce that the Swedish Research Council has decided to fund the project Autonomous Phenotypic Drug Profiling under the call Project Grant 2020 for Natural end engineering science (VR-NT 2020) where Prof. Ola Spjuth ...

Ola Spjuth interviewed at the faculty

20 Oct, 2020. Group leader Ola Spjuth was interviewed and presented at the faculty in a post entitled Self-learning machines take the step into drug discovery Link to the full article here. ...

More blog posts ...

Latest publications

Deep learning models for lipid-nanoparticle-based drug delivery Harrison P, Wieslander H, Sabirsh A, Karlsson J, Malmsjö V, Hellander A, Wählby C, Spjuth O. Nanomedicine Ahead of print: (2021)

Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit Blamey B, Toor S, Dahlö M, Wieslander H, Harrison PJ, Sintorn IM, Sabirsh A, Wählby C, Spjuth O, Hellander A. Gigascience 10:3 (2021)

Synergy Conformal Prediction for Regression Gauraha, N. and Spjuth, O.. Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods vol 1: ICPRAM: (2021)

Deep learning with conformal prediction for hierarchical analysis of large-scale whole-slide tissue images Wieslander H., Harrison P, Skogberg G, Jackson S, Fridén M, Karlsson J, Spjuth O, and Wählby C.. IEEE Journal of Biomedical and Health Informatics 25:2 (2021)

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Latest presentations

Synergy Conformal Prediction for Regression
10th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2021), . Feb 2021
A Constraint Programming Approach to Microplate Layout Design
The 19th workshop on Constraint Modelling and Reformulation, Louvain-la-Neuve, Belgium. Sep 2020
Towards automated phenotypic cell profiling with high-content imaging
Chemical Biology Seminar Series, Stockholm. Feb 2020
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Latest posters

Automating Cell Profiling of Drugs with Cell Painting
10th Pharmaceutical Profiling Symposium, Uppsala. Jan 2020
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