Electron transfer plays a vital role in drug metabolism and underlying toxicity mechanisms. Currently, pharmaceutical research relies on pharmacokinetics (PK) and absorption, distribution, metabolism, elimination and toxicity (ADMET) measurements to understand and predict drug reactions in the body. Metabolic stability (and toxicity) prediction in the early phases of the drug discovery and development process is key in identifying a suitable lead compound for optimisation. Voltammetric methods have the potential to overcome the significant barrier of new drug failure rates, by giving insight into phase I metabolism events which can have a direct bearing on the stability and toxicity of the parent drug being dosed. Herein, we report for the first time a data-mining investigation into the voltammetric behaviour of reported drug molecules and their correlation with metabolic stability (indirectly measured via t½), as a potential predictor of drug stability/toxicity in vivo. We observed an inverse relationship between oxidation potential and drug stability. Furthermore, we selected and prepared short- (<10 min) and longer-circulation (>2 h) drug molecules to prospectively survey the relationship between oxidation potential and stability.

A library of 17 nanoparticles made of acrylate and methacrylate copolymers is prepared, characterized, and screened against six epitopes of adeno‐associated viruses (AAV)‐neutralizing antibodies to assess their affinity and specificity. Peptide epitopes are immobilized onto the surface of glass beads, packed in filtration microplates, and incubated with fluorescein‐labelled nanoparticles. Following intense washing, the affinity of nanoparticles to immobilized epitopes is assessed by measuring the fluorescence of captured nanoparticles. The results show that polar monomers, acrylic acid in particular, have a positive impact on polymer affinity towards all peptides used in this study. The presence of hydrophobic monomers, on other hand, has a negative impact on polymer binding. The composition of peptides used in this study has no noticeable impact on the affinity of synthesized nanoparticles. The affinity of nanoparticles with the highest affinity to peptide targets does not exceed millimolar level. Overall, it is found that the synthesized library showed modest affinity but lacked specificity, which should be further “tuned,” for example, by using molecular imprinting to achieve an acceptable level of affinity and specificity for practical application.