Effects of Pharmacogenetic Screening for CYP2D6 Among Elderly Starting Therapy With Nortriptyline or Venlafaxine: A Pragmatic Randomized Controlled Trial (CYSCE Trial)

PURPOSE/BACKGROUND: The duration of untreated depression is a predictor for poor future prognosis, making rapid dose finding essential. Genetic variation of the CYP2D6 isoenzyme can influence the optimal dosage needed for individual patients. The aim of this study was to determine the effectiveness of CYP2D6 pharmacogenetic screening to accelerate drug dosing in older patients with depression initiating nortriptyline or venlafaxine. METHODS/PROCEDURES: In this randomized controlled trial, patients were randomly allocated to one of the study arms. In the intervention arm (DG-I), the specific genotype accompanied by a standardized dosing recommendation based on the patients' genotype and the prescribed drug was directly communicated to the physician of the participant. In both the deviating genotype control arm (DG-C) and the nonrandomized control arm, the physician of the participants was not informed about the genotype and the associated dosing advise. The primary outcome was the time needed to reach adequate drug levels: (1) blood levels within the therapeutic range and (2) no dose adjustments within the previous 3 weeks. FINDINGS/RESULTS: No significant difference was observed in mean time to reach adequate dose or time to adequate dose between DG-I and DG-C. Compared with the nonrandomized control arm group, adequate drug levels were reached significantly faster in the DG-I group (log-rank test; P = 0.004), and there was a similar nonsignificant trend for the DG-C group (log-rank test; P = 0.087). IMPLICATIONS/CONCLUSIONS: The results of this study do not support pharmacogenetic CYP2D6 screening to accelerate dose adjustment for nortriptyline and venlafaxine in older patients with depression

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Data-driven medicinal chemistry in the era of big data

Contains fulltext : 136239.pdf (publisher's version ) (Closed access)Science, and the way we undertake research, is changing. The increasing rate of data generation across all scientific disciplines is providing incredible opportunities for data-driven research, with the potential to transform our current practices. The exploitation of so-called 'big data' will enable us to undertake research projects never previously possible but should also stimulate a re-evaluation of all our data practices. Data-driven medicinal chemistry approaches have the potential to improve decision making in drug discovery projects, providing that all researchers embrace the role of 'data scientist' and uncover the meaningful relationships and patterns in available data

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