Development of a non-radioactive mass spectrometry-based binding assay at the µ-opioid receptor and its application for the determination of the binding affinities of 17 opiates/opioids as well as of the designer opioid isotonitazene and five further 2-benzylbenzimidazoles.

Radioactive ligand binding assays are the most commonly applied method for the determination of binding affinities of compounds at a particular receptor. While they are highly sensitive and high-throughput capable they come with major disadvantages due to the radioactive ligands utilized. Here we present the development of a mass-spectrometry-based binding assay for the determination of binding affinities at the human µ-opioid receptor using non-labelled DAMGO ([D-Ala2, N-MePhe4, Gly5-ol]-enkephalin). The runtime of the LC-MS/MS method was 5.5 min per data point and allowed for the highly sensitive detection of 38.5 fg DAMGO on column. The assay shows low non-specific binding and the equilibrium dissociation constant of DAMGO was 0.57 nM. The assay was applied to determine the Ki values of 17 opiates/opioids and the results were in good agreement with the data from radioactive receptor binding assays published in the literature. Additionally, the Ki value of six 2-benzylbenzimidazoles, including the widely abused designer opioid isotonitazene, were determined ranging from 0.654 to 72.9 nM. Consequently, the developed assay provides a suitable alternative to radioactive binding assays as it allows for a reliable and rapid determination of receptor binding affinities of e.g. newly emerging designer opioids.

Supporting Medical Staff from Psycho-Oncology with Smart Mobile Devices: Insights into the Development Process and First Results.

Cancer is a very distressing disease, not only for the patients themselves, but also for their family members and relatives. Therefore, patients are regularly monitored to decide whether psychological treatment is necessary and applicable. However, such monitoring processes are costly in terms of required staff and time. Mobile data collection is an emerging trend in various domains. The medical and psychological field benefits from such an approach, which enables experts to quickly collect a large amount of individual health data. Mobile data collection applications enable a more holistic view of patients and assist psychologists in taking proper actions. We developed a mobile application, FeelBack, which is designed to support data collection that is based on well-known and approved psychological instruments. A controlled pilot evaluation with 60 participants provides insights into the feasibility of the developed platform and it shows the initial results. 31 of these participants received paper-based questionnaire and 29 followed the digital approach. The results reveal an increase of the overall acceptance by 58.5% in the mean when using a digital screening as compared to the paper-based. We believe that such a platform may significantly improve cancer patients' and relatives' psychological treatment, as available data can be used to optimize treatment.