SMARTdrugs_Supramolecular agents as radiotheranostic drugs

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From diagnostic applications in the quantification and characterisation of biomarker expression in cancer patients, through to molecularly targeted radionuclide therapy, radiopharmaceuticals are at the frontline of modern personalised medicine. The radical long-term vision of SMARTdrugs is to harness the untapped potential of supramolecular chemistry to create a new class of therapies - radiotheranostics - which combine both diagnostic and therapeutic radionuclides in one compound. By using the self-assembly of host-guest supramolecular coordination complexes and molecularly interlocked molecules as scaffolds for creating supramolecular radiotheranostic drugs, new methodsfor radiotheranostic synthesisthat break away from conventional medicinal chemistry concept will be introduced. SMARTdrugs will establish a proof-of-concept demonstrating the utility of non-covalent systems in the design of multifunctional radiotheranostic agents with tailored pharmacokinetics, and their application in challenging drug-delivery scenarios including targeted delivery to cancers of the lung and brain. Our 3 main objectives: Objective 1 – Develop new chemical landscapes using non-covalent bonding to create functionalised supramolecular compounds for cancer-specific theranostics Objective 2 – Elucidate the key relationships between supramolecular radiotheranostics and the complex tumour microenvironment that determine drug efficacy in vivo Objective 3 – Perform head-to-head studies to establish a proof-of-principle that supramolecular chemistry is a viable alternative to classical radiopharmaceutical design The long-term goal is to establish a new chemical landscape for radiotheranostic design, and to facilitate clinical translation of this new technology. Successful experiments will lay the foundations for exploiting supramolecular chemistry in the wider context of drug delivery and theranostics, and for studying biological interactions at the cellular to whole-organism levels.