The group is engaged in multidisciplinary projects funded by both academia and industry.
Prediction of chemoresistance for personalised chemotherapy: Label-free Raman spectroscopy and imaging of ovarian cancer cells and tissue

Chemotherapy is a cornerstone of cancer treatment. Chemoresistance, either intrinsic or acquired, is a substantial cause of treatment failure and ultimately patient death. Furthermore, resistance to chemotherapy agents varies substantially between patients and is also affected by prior treatment. Despite such diversity in chemoresistance, chemotherapy treatment is generally based on standardised treatment regimens. Current clinical practice lacks tools to predict patient-specific chemoresistance and thus personally optimise chemotherapy selection prior to treatment. One form of cancer in which chemoresistance is common and a significant contributor to mortality is high-grade serous ovarian cancer (HGSOC).

Raman spectroscopy is a label-free, non-destructive global analysis methods with the potential to provide a molecular and structural fingerprint of cells and tissues, and as such differences between chemoresistant and chemosensitive cells and tissues may potentially be harnessed and detected. It does not rely on identifying or targeting predefined individual biomarkers which together with multiple other advantages makes it a highly potential method for clinical cell and tissue analyses.

In this Academy of Finland funded project we investigate the potential of Raman spectroscopy and imaging for detection of chemoresistance in ovarian cancer in cells and tissues. Our aim is to develop and optimise a Raman-based analytical platform suitable for robust personalised prediction of chemoresistance. The Raman analyses of ovarian cancer cells and tissues will also be supported by advanced mass spectrometry imaging analyses.

People involved in the project are

Global Single Cell Proteomics and Metabolomics

The differences between individuals are based on the cellular heterogeneity. To assess how different the cell phenotypes are, single-cell measurements are necessary as population measurements yield only average values. Metabolomics and proteomics technologies enable the examination and identification of endogenous biochemical reaction products, providing information on the precise metabolic pathways and processes within a living cell. Metabolism is either directly or indirectly involved with every aspect of cell function, and metabolomics and proteomics are thus believed to be a reflection of the phenotype of any cell.

Mass spectrometry (MS) is rapidly becoming one of the most widely used methods for ultrasensitive, label-free, and simultaneous detection of many metabolites and proteins at the single-cell level. However, the current MS based technologies and methods are still limited for single cell analysis in terms of sensitivity and high throughput. In this work we will develop new more efficient and sensitive analytical methods for global single cell metabolomics and proteomics based on mass spectrometry.

AINA Pharma (project completed)

AINAPharma addresses the key unmet industrial need: successful development of dosage forms based on solid dispersions. Amorphous solid dispersions, which combine an active entity with other components (e.g., polymers, sugars) in a non-crystalline manner, represent a key enabling technology to overcome stability and solubility problems that plague the majority of new active entities. However, solid dispersions often suffer clinically unacceptable patient-to-patient variability and consequent clinical failure. This is frequently caused by subtle and currently undetected batch-to-batch solid-state variability during production. AINAPharma will address these issues by synergistically introducing state-of-the-art amorphous solid dispersion production and ultra-sensitive analytical technologies. At the same time, AINAPharma establishes a unique ecosystem to enhance the successful translation of drug candidates into trustworthy and efficacious medicines.