Molecular Imaging in Drug Research

Dear Colleagues,

Drug discovery and development (DDD) is a lengthy (10-15 years), expensive (over $1–2 billions) and risky process since only 10–20% of drug candidates reach the market. Four main reasons explain this high attrition rate: (i) lack of clinical efficacy; (ii) unmanageable toxicity; (iii) poor drug-like properties and (4i) lack of commercial needs / poor strategic planning. DDD classically necessitates a rigorous target validation, high-throughput screening of drug candidates, rigorous drug optimization (activity and drug-like properties), preclinical efficacy and toxicity testing, as well as biomarker-guided patient selection and optimal-designed clinical trials. Innovative tools such as multimodal imaging (MI) might benefit in all phases of DDD pipeline. Indeed, due to the combination of high spatial resolution and high sensitivity, MI can provide a large amount of relevant anatomical, functional and molecular informations. MI can decipher pathophysiological mechanisms, contribute to find / validate new targets and to assess pharmocokinetics / pharmacodynamics. Moreover, in the era of artificial intelligence, it is essential to integrate this new paradigm for drug design and MI (e.g. radiomics) to boost drug research. So, this Special Issue aims to gather scientific papers to demonstrate that MI can be a major decision support in the complex DDD process.

Dr. Bertrand Collin
Dr. Alan Courteau
Dr. Cecile Perrio
Guest Editors

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• drug design
• discovery
• development
• multimodal imaging
• molecular imaging
• translational research
• artificial intelligence