A robust Bayesian meta-analytic approach to incorporate animal data into phase I oncology trials

Haiyan Zheng, Lisa Hampson, Simon Wandel

Research output: Contribution to journalArticlepeer-review

12 Citations (SciVal)
21 Downloads (Pure)


Before a first-in-man trial is conducted, preclinical studies are performed in animals to help characterise the safety profile of the new medicine. We propose a robust Bayesian hierarchical model to synthesise animal and human toxicity data, using scaling factors to translate doses administered to different animal species onto an equivalent human scale. After scaling doses, the parameters of dose-toxicity models intrinsic to different animal species can be interpreted on a common scale. A prior distribution is specified for each translation factor to capture uncertainty about differences between toxicity of the drug in animals and humans. Information from animals can then be leveraged to learn about the relationship between dose and risk of toxicity in a new phase I trial in humans. The model allows human dose-toxicity parameters to be exchangeable with the study-specific parameters of animal species studied so far or non-exchangeable with any of them. This leads to robust inferences, enabling the model to give greatest weight to the animal data with parameters most consistent with human parameters or discount all animal data in the case of non exchangeability. The proposed model is illustrated using a case study and simulations. Numerical results suggest that our proposal improves the precision of estimates of the toxicity rates when animal and human data are consistent, while it discounts animal data in cases of inconsistency.
Original languageEnglish
Pages (from-to)94-110
JournalStatistical Methods in Medical Research
Issue number1
Early online date16 Jan 2019
Publication statusPublished - 10 Jan 2020

Bibliographical note

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 633567. Dr Hampson's contribution to this manuscript was supported by the UK Medical Research Council (grant MR/M013510/1).


  • Bayesian hierarchical model
  • historical data
  • oncology
  • phase I clinical trials
  • robustness


Dive into the research topics of 'A robust Bayesian meta-analytic approach to incorporate animal data into phase I oncology trials'. Together they form a unique fingerprint.

Cite this