Publications by authors named "Otto I Pulkkinen"

Immune checkpoint therapies (ICT) for advanced solid tumors mark a new milestone in cancer therapy. Yet their efficacy is often limited by poor immunogenicity, attributed to inadequate priming and generation of antitumor T cells by dendritic cells (DCs). Identifying biomarkers to enhance DC functions in such tumors is thus crucial.

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Most drug molecules modulate multiple target proteins, leading either to therapeutic effects or unwanted side effects. Such target promiscuity partly contributes to high attrition rates and leads to wasted costs and time in the current drug discovery process, and makes the assessment of compound selectivity an important factor in drug development and repurposing efforts. Traditionally, selectivity of a compound is characterized in terms of its target activity profile (wide or narrow), which can be quantified using various statistical and information theoretic metrics.

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Combinatorial therapies are required to treat patients with advanced cancers that have become resistant to monotherapies through rewiring of redundant pathways. Due to a massive number of potential drug combinations, there is a need for systematic approaches to identify safe and effective combinations for each patient, using cost-effective methods. Here, we developed an exact multiobjective optimization method for identifying pairwise or higher-order combinations that show maximal cancer-selectivity.

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