Discover drug targets, mechanisms and biomarkers with cutting-edge omics data analysis.

Molecular measurements based on next-generation sequencing (NGS) and mass-spectrometry (MS) are routinely used throughout the drug development process. RNA-sequencing and proteomics, in particular, reveal a more detailed view of pathways and functions in disease models and patients.
We work with customers developing small molecules and biologics as well as gene, cell and biomaterial therapies. Learn more about the stages in drug development that benefit from high-throughput molecular measurements coupled with state-of-the-art bioinformatics.

Basic research

Basic research into the molecular and cellular biology of a disease is a prerequisite for rational drug discovery.
Much of the work our customers outsource to us falls under this category.

Preclinical development

After a candidate drug has been identified against the target, mechanism-of-action and off-target analyses can be performed,again using in vitro or in vivo models.
Transcriptomics (RNA-seq), proteomics and epigenomics (e.g., ChIP-seq, ATAC-seq) are particularly applicable high-throughput measurements.

Biomarker discovery

Biomarkers, such as as genetic variants, proteins or metabolites, can be instrumental in stratifying patients based on their predicted likelihood of benefitting from the treatment. Candidate biomarkers can be identified already before a clinical trial (from e.g., biobank data) to identify high-risk patients. Molecular measurements during and after a clinical trial, on the other hand, can be used to identify biomarkers for treatment response or side effects (including pharmacogenetic markers).

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Target Discovery

Target-based drug development begins at identifying a protein or
other biomolecule to use as a target for treatment. The wealth of public, semi-public and proprietary data lends itself to data-driven target discovery. Examples include:

• Identifying causative genetic variants in genome-wide association studies or genetic studies of families with a hereditary disease.
• Identifying genes associated to disease progression events from e.g. tumor RNA-sequencing or proteomic data.
• Identifying genes with disease-specific up- or down-regulation using patient samples or animal models of a disease.
• Identifying signaling pathways activated or inhibited in a disease.

Target Validation

A candidate target can be further studied and validated using gene knock-out models, in vitro or in vivo.
Gene expression analysis of such models may reveal both wanted and unwanted downstream effects of a gene knock-out.

Selected publications from our customers

1. Mezheyeuski, A. et al. (2023). An immune score reflecting pro- and anti-tumoural balance of tumour microenvironment has major prognostic impact and predicts immunotherapy response in solid cancers. EBioMedicine, 88, 104452. Advance online publication
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2. Tusup, M. et al. (2022). Epitranscriptomics modifier * indirectly triggers Toll-like receptor 3 and can enhance immune infiltration in tumors. Molecular therapy : the journal of the American Society of Gene Therapy, 30(3), 1163–1170.
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3. Cramer, M. et al. (2022). Transcriptomic Regulation of Macrophages by Matrix-Bound Nanovesicle-Associated Interleukin-33. Tissue engineering. Part A, 28(19-20), 867–878
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4. Ribeiro, R. et al. (2022). Synchronous Epidermodysplasia Verruciformis and Intraepithelial Lesion of the Vulva is Caused by Coinfection with α-HPV and β-HPV Genotypes and Facilitated by Mutations in Cell-Mediated Immunity Genes. Preprint at
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5. Wullt, B. et al. (2021). Immunomodulation-A Molecular Solution to Treating Patients with Severe Bladder Pain Syndrome?. European urology open science, 31, 49–58.
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6. Åvall-Jääskeläinen, S. et al. (2021). Genomic Analysis of Staphylococcus aureus Isolates Associated With Peracute Non-gangrenous or Gangrenous Mastitis and Comparison With Other Mastitis-Associated Staphylococcus aureus Isolates. Frontiers in microbiology, 12, 688819.
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7. Madonna, G. et al. (2021). Clinical Categorization Algorithm (CLICAL) and Machine Learning Approach (SRF-CLICAL) to Predict Clinical Benefit to Immunotherapy in Metastatic Melanoma Patients: Real-World Evidence from the Istituto Nazionale Tumori IRCCS Fondazione Pascale, Napoli, Italy. Cancers, 13(16), 4164.
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8. Gurvich, O. L. et al. (2020). Transcriptomics uncovers substantial variability associated with alterations in manufacturing processes of macrophage cell therapy products. Scientific reports, 10(1), 14049.
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9. Oksanen, M. et al. (2020). NF-E2-related factor 2 activation boosts antioxidant defenses and ameliorates inflammatory and amyloid properties in human Presenilin-1 mutated Alzheimer's disease astrocytes. Glia, 68(3), 589–599.
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