News

New statistical model effectively predicts the toxicity of pharmaceutical molecules

A statistical component model can be used to identify associations between chemicals and toxicological effects.
The component model describes statistical links between chemicals and the effect of their molecular toxins. Picture: Juuso Parkkinen, Aalto University.

The joint Aalto University, Karolinska Institute and Institute for Molecular Medicine Finland (FIMM) study included over 1,300 known pharmaceutical molecules, on which there is a wealth of measurement data available.

‘The study uses systematic data-driven analysis to combine toxicity measurements taken on cell lines with gene expression responses describing gene activation. Toxicity includes growth inhibitory and cell killing effects. The method developed in the study makes it possible to more accurately predict the toxicity of new molecules because it makes use of advanced statistical methods and much bigger datasets than before,’ explains Juuso Parkkinen, who completed his doctoral dissertation at Aalto University.

At present, toxicity is primarily measured by means of animal testing. Thanks to this new method, animal testing can be partly replaced in the future by a combination of cell line testing and statistical modelling. This would also result in considerable cost savings for pharmaceutical development.

‘The new prediction method can be applied to new pharmaceutical molecules and other chemicals currently in product development to eliminate possible toxic molecules,’ adds Parkkinen.

Advances in statistical machine learning and artificial intelligence methods have risen to play a crucial role in many application areas in addition to medical research.

‘Juuso Parkkinen is an excellent example of the usefulness of Aalto University's artificial intelligence research and doctoral studies: He wrote his dissertation on medicinal applications in my research group and then transferred to Reaktor to apply data science to a wide range of business needs,’ praises Parkkinen's dissertation adviser, Professor Samuel Kaski.

Pharmaceutical toxicity was studied by Juuso Parkkinen and Samuel Kaski of Aalto University, Pekka Kohonen, Egon Willighagen, Rebecca Ceder and Roland Grafström of Karoliska Institute and Krister Wennerberg of the Institute for Molecular Medicine Finland (FIMM).

Further information:                                         

Juuso Parkkinen
AI Designer and Senior Data Scientist
Reaktor
[email protected]
tel. +358 50 356 3916

Samuel Kaski
Professor
Aalto University
[email protected]
tel. +358 50 305 8694

Journal article in Nature Communications: A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury

  • Published:
  • Updated:
Share
URL copied!

Read more news

Doctoral student Aini Putkonen
Research & Art, Studies Published:

Aini Putkonen: 'The life of a doctoral student is very versatile'

Doctoral student Aini Putkonen thinks that the doctoral degree prepares students well for both academia and industry.
Ayse Pekdiker - blog post image 1
Studies, University Published:

My experience at Aalto University as an international student and an employee

After one month of work, our Program Assistant Ayse at Aalto University Summer School shares her experiences.
Sähköauto Zoe
Campus Published:

Prices for charging electric cars will change at the Otaniemi campus and Aalto Töölö

The pricing for electric car charging is adjusted, beginning from 14.7.2022. The overall increase in electricity prices affects the charging expenses as well.
Elderly people spending time outdoors in the yard and garden, a student work Outdoors by Luiza Sevele
Research & Art, Studies Published:

Flexibility and community support for people with memory problems

What are the future housing solutions for people with memory decline, and what should they be?