TY - JOUR A1 - Lötsch, Jörn A1 - Walter, Carmen A1 - Zunftmeister, Martin A1 - Zinn, Sebastian A1 - Wolters, Miriam A1 - Ferreirós Bouzas, Nerea A1 - Rossmanith, Tanja A1 - Oertel, Bruno Georg A1 - Geisslinger, Gerd T1 - A data science approach to the selection of most informative readouts of the human intradermal capsaicin pain model to assess pregabalin effects T2 - Basic & Clinical Pharmacology & Toxicology N2 - Persistent and, in particular, neuropathic pain is a major healthcare problem with still insufficient pharmacological treatment options. This triggered research activities aimed at finding analgesics with a novel mechanism of action. Results of these efforts will need to pass through the phases of drug development, in which experimental human pain models are established components e.g. implemented as chemical hyperalgesia induced by capsaicin. We aimed at ranking the various readouts of a human capsaicin–based pain model with respect to the most relevant information about the effects of a potential reference analgesic. In a placebo‐controlled, randomized cross‐over study, seven different pain‐related readouts were acquired in 16 healthy individuals before and after oral administration of 300 mg pregabalin. The sizes of the effect on pain induced by intradermal injection of capsaicin were quantified by calculating Cohen's d. While in four of the seven pain‐related parameters, pregabalin provided a small effect judged by values of Cohen's d exceeding 0.2, an item categorization technique implemented as computed ABC analysis identified the pain intensities in the area of secondary hyperalgesia and of allodynia as the most suitable parameters to quantify the analgesic effects of pregabalin. Results of this study provide further support for the ability of the intradermal capsaicin pain model to show analgesic effects of pregabalin. Results can serve as a basis for the designs of studies where the inclusion of this particular pain model and pregabalin is planned. KW - analgesia KW - data science KW - human pain models KW - human pharmacology KW - pain Y1 - 2019 UR - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/57421 UR - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-574216 SN - 1742-7843 VL - 126.2020 IS - 4 SP - 318 EP - 331 PB - Wiley-Blackwell CY - Oxford ER -