Comparison of the Benchmark Dose (BMD) approach by four different type software with No Observed Adverse Effect Level (NOAEL) approach for tumorigenicity in rodent bioassays of pesticides in Japan

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  • Yasuhiko Yukuto
    Division of Pharmacology, National Institute of Health Sciences
  • Machino Satoshi
    The First Risk Assessment Division, Food Safety Commission Secretariat, Cabinet Office
  • Fujii Tatsuya
    The First Risk Assessment Division, Food Safety Commission Secretariat, Cabinet Office
  • Ishigami Miwa
    The First Risk Assessment Division, Food Safety Commission Secretariat, Cabinet Office
  • Aoki Masanori
    Environmental Management Bureau, Ministry of the Environment
  • Irie Fumi
    Department of Health Care Administration and Management, Graduate School of Medical Sciences, Kyushu University
  • Yoshida Midori
    Food Safety Commission of Japan
  • Kanda Yasunari
    Division of Pharmacology, National Institute of Health Sciences

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Other Title
  • 4種のソフトウェアを用いた、農薬げっ歯類発がん性試験結果を例とするベンチマークドーズ（BMD）法とNOAEL法の比較

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<p>Benchmark Dose (BMD) approach is the way to calculate the risk at the lower dosage of chemical exposure, applying a mathematical model to the dose-response relationship. Although a number of the guidelines and software have been developed worldwide, the harmonization of BMD application is still undergoing. Before applying in actual risk assessment, it is essential to evaluate whether the BMD and NOAEL approaches give the same range of POD values and how different BMD values the major BMD software would give.</p><p>Here, we calculated the lower limit of BMD confidence interval (BMDL) from 201 tumorigenicity data publicized in the pesticide risk assessment reports by the Food Safety Commission of Japan (FSCJ). We applied three well-known BMD software, PROAST, BMDS, and BBMD, to compare their BMDLs to NOAELs and LOAELs and between the recently implemented methodologies such as model averaging (MA) or Bayesian inference.</p><p>Our result indicates that the BMD approach gives Point of Departure (POD) similar to the NOAEL approach if the data applied show a clear dose-response relationship. However, most of the datasets that resulted in failed calculation or extremely low BMDLs showed unclear dose-response relationships, such as non-monotonous and sporadic responses. We also noted that the Bayesian inference software gave failed calculation or extreme BMDLs less than the frequentist approaches.</p>

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