Refinement and validation of an exposure model for the pharmaceutical industry

Abstract

Objectives: Assessment of worker's exposure is becoming increasingly critical in the pharmaceutical industry as drugs of higher potency are being manufactured. The batch nature of operations often makes it difficult to obtain sufficient numbers of exposure measurements and occupational exposure models may be useful tools in the exposure assessment process. This paper aims to describe further refinement and validation of an existing deterministic occupational exposure model to predict airborne exposure of workers in this industry. Methods: Workplace exposure assessment data (n = 381) containing all the contextual information required for the exposure model were collated from a multinational pharmaceutical company. The measured exposure levels ranged from 5 x 10(-7) to 200 mg m(-3) for largely task based samples, and included a range of handling activities, local control measures and abnormal operating conditions. Model input parameters for local control measures and handling activities were refined to reflect pharmaceutical situations. Results: The refined exposure model resulted in good correlations between the log-transformed model predictions and the actual measured data for the overall dataset (r(s) = 0.61, n = 381, p 0.1 mg m(-3)) (r(s) = 0.59, bias = -4.9, n = 33, p