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Selecting an appropriate biomonitoring strategy to evaluate dermal exposure to opioid narcotic analgesics in pharmaceutical production workers
  1. Nadine F J Van Nimmen,
  2. Katrien L C Poels,
  3. Mario Severi,
  4. Lode Godderis*,
  5. Hendrik A F Veulemans
  1. 1 Katholieke Universiteit Leuven, Belgium
  1. Correspondence to: Lode Godderis, Occupational, Environmental and Insurance Med, K.U.Leuven, Kapucijnenvoer 35/5, Leuven, 3000, Belgium; lode.godderis{at}


Objectives: In follow-up of a previous study, in which exposure pathways for opioid narcotic analgesics were identified in pharmaceutical workers involved in drug synthesis, the current study focused on the selection of an appropriate biomonitoring strategy.

Methods: Six opioid narcotic production workers were intensively monitored during a (one week) fentanyl production campaign. A systematic sampling scheme was followed that provided information about hand contamination and biomarker levels at multiple points in time.

Results: Linear mixed-effects models, incorporating half-shift and end-of-shift hand contamination levels, showed a positive and significant correlation with fentanyl urinary excretion occurring at numerous of the different 4h period investigated time lags (4 to 28h). Optimum model characteristics, including both minimal between- and within-worker variability were obtained at a lag time of 24h and 20h respectively, implicating a pre-shift urine sampling strategy on the following working day. For these lag-times also the portion of the variability explained by the model was maximal. Furthermore, using a distributed lag model, it was demonstrated that urinary fentanyl levels were positively correlated with hand contamination levels of the preceding four 8h-period time lags (8 to 32h), although statistical significance was only shown for a lag time of 24h.

Conclusion: Fentanyl levels in pre-shift urine samples reflect the compound’s dermal exposure during the previous day. Thus, in the specific working environment investigated, a biological monitoring protocol evaluating pre-shift urinary fentanyl levels could provide an adequate risk estimate in individual workers.

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