Recycling side-effects into clinical markers for drug repositioning

Abstract

Side-effects are the unintended consequence of therapeutic treatments, but they can also be seen as valuable read-outs of drug effects in humans; these effects are difficult to infer or predict from pre-clinical models. Indeed, some studies suggest that drugs with similar side-effect profiles may also share therapeutic properties through related mechanisms of action. A recent publication exploits this concept to systematically investigate new indications for already marketed drugs, and presents a strategy to get the most out of the tiny portion of chemicals that have proved to be effective and safe.

Figure 1

Bridging the levels of biological complexity. The left half of the scheme represents the association between drugs and their therapeutic effects measured with different assays. Captured biological complexity increases radially and, in principle, inner knowledge can be gained indirectly. Side-effects are on the outer level and constitute a signal of similar complexity to the therapeutic effect. Pre-clinical experiments such as disease-gene associations or gene-expression profiles provide biomolecular rationale for a disease, but the underlying mechanism of action (MoA) upon treatment can only be proposed as a complement. Finally, a structure-activity relationship (SAR) does not embrace biological understanding because the therapeutic outcome is ciphered within the molecular structure alone. All this information is used in the right half to guide drug repositioning, where candidates are screened correspondingly. Arrows crossing biological complexity levels imply functional inferences not necessarily supported by the assay design.