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

Andreina Francisco new Postdoc in the group

20 Jul, 2020. We welcome Andreina who recently started a 2-year postdoc position in our group in the project AI methods for decision making in automated biological laboratories. The position is part of the strategic research area effort eSSENCE´s PostDo ...

New project for profiling coronavirus-infected cells funded by SciLifeLab and KAW!

6 May, 2020. Our recent grant application Multi-level profiling of Coronavirus-infected cells by combining Viral Entry Assays, Cell Painting, and DrugSEQ was awarded 500 KSEK by SciLifeLab and Knut och Alice Wallenbergs Stiftelse in a joint effort with ...

Postdoc position available: AI methods for large-scale microscopy imaging

20 Mar, 2020. We are currently looking for an ambitious, highly motivated Postdoc with a good background in AI and imaging to join our research group where we have built up a robotized cell profiling system with high-content microscopy imaging as primar ...

NeIC Glenna project visits our group

10 Mar, 2020. The NeIC project Glenna (https://neic.no/glenna/) had its final meeting in Uppsala on March 10, 2020. Our group’s involvement has been in the project towards establishing a Nordic AI collaboration, and in particular on: 1) Evaluating ...

Attending the conference: Phenotypic Screening, High-Content Analysis and AI: Overcoming the Challenges

2 Mar, 2020. 5 people of our group visited the conference: Phenotypic Screening, High-Content Analysis and AI: Overcoming the Challenges that was held March 2-3rd at AstraZeneca, Gothenburg, Sweden. Ola Spjuth shared the session AI and Machine Learning ...

Postdoc position available: AI methods for decision making in automated biological laboratories

20 Feb, 2020. We are currently looking for an ambitious, highly motivated Postdoc with a good background in AI and an interest in automation with robotics in the field of life science, to join the research group of Assoc. Prof. Ola Spjuth (group website ...

Ola Spjuth presenting at SciLifeLab Chemical Biology Seminar Series

6 Feb, 2020. On Feb 6th 2020, Ola Spjuth held a presentation at Karolinska Institutet, Stockholm in the SciLifeLab Chemical Biology Seminar Series. Approx 50 people attended to this event organized primarily by Jordi Carreras Puigvert. The title of the ...

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Latest publications

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 Early access: (2020)

Using Predicted Bioactivity Profiles to Improve Predictive Modelling Norinder U, Spjuth O, Svensson F. Journal of Chemical Information and Modeling 60:6 (2020)

Towards reproducible computational drug discovery Schaduangrat N, Lampa S, Simeon S, Gleeson MP, Spjuth O, Nantasenamat C. Journal of Cheminformatics 12:9 (2020)

On-demand virtual research environments using microservices Capuccini M, Larsson A, Carone M, Novella JA, Sadawi N, Gao J, Toor S, Spjuth O. PeerJ Computer Science 5:e232 (2019)

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Latest presentations

Towards automated phenotypic cell profiling with high-content imaging
Chemical Biology Seminar Series, Stockholm. Feb 2020
Towards Automated AI-guided Drug Discovery Labs
Swedish e-Science Academy 2019, Lund. Oct 2019
Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets
8th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2019), Varna. Sep 2019
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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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