Skip to main content

Optimal Biological Dose and Phase I/II Trials

  • Chapter
  • First Online:
Bayesian Adaptive Design for Immunotherapy and Targeted Therapy
  • 309 Accesses

Abstract

The conventional phase I trial design paradigm is based on the more-is-better assumption, which may not be true for immunotherapies and targeted therapies. For these novel therapies, efficacy may plateau or even decrease at high doses, and dose limiting toxicity may be rare. In this case, it is more appropriate to identify the optimal biological dose (OBD) that optimizes the risk-benefit tradeoff of the treatment, rather than the maximum tolerated dose (MTD). This chapter reviews basic concepts of the OBD and the phase I/II design paradigm to find the OBD.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Fraisse, J., Dinart, D., Tosi, D., Bellera, C., & Mollevi, C. (2021). Optimal biological dose: A systematic review in cancer phase I clinical trials. BMC Cancer, 21(1), 1–10.

    Article  Google Scholar 

  • Guo, B., & Yuan, Y. (2017). Bayesian phase I/II biomarker-based dose finding for precision medicine with molecularly targeted agents. Journal of the American Statistical Association, 112(518), 508–520.

    Google Scholar 

  • Houede, N., Thall, P. F., Nguyen, H., Paoletti, X., & Kramar, A. (2010). Utility-based optimization of combination therapy using ordinal toxicity and efficacy in phase I/II trials. Biometrics, 66(2), 532–540.

    Google Scholar 

  • Iasonos, A., & O’Quigley, J. (2013). Design considerations for dose-expansion cohorts in phase I trials. Journal of Clinical Oncology, 31(31), 4014.

    Google Scholar 

  • Jin, I. H., Liu, S., Thall, P. F., & Yuan, Y. (2014). Using data augmentation to facilitate conduct of phase I-II clinical trials with delayed outcomes. Journal of the American Statistical Association, 109(506), 525–536.

    Google Scholar 

  • Lin, R., Zhou, Y., Yan, F., Li, D., & Yuan, Y. (2020). BOIN12: Bayesian optimal interval phase I/II trial design for utility-based dose finding in immunotherapy and targeted therapies. JCO Precision oncology, 4, 1393–1402.

    Google Scholar 

  • Liu, S., Guo, B., & Yuan, Y. (2018). A Bayesian phase I/II trial design for immunotherapy. Journal of the American Statistical Association, 113(523), 1016–1027.

    Google Scholar 

  • Liu, S., & Johnson, V. E. (2016). A robust Bayesian dose-finding design for phase I/II clinical trials. Biostatistics, 17(2), 249–263.

    Google Scholar 

  • Reynolds, A. R. (2010). Potential relevance of bell-shaped and u-shaped dose-responses for the therapeutic targeting of angiogenesis in cancer. Dose-response, 8(3), dose-response.

    Google Scholar 

  • Rossoni, C., Bardet, A., Geoerger, B., & Paoletti, X. (2019). Sequential or combined designs for Phase I/II clinical trials? A simulation study. Clinical Trials, 16(6), 635–644.

    Article  Google Scholar 

  • Thall, P. F., & Cook, J. D. (2004). Dose-finding based on efficacy—toxicity trade-offs. Biometrics, 60(3), 684–693.

    Google Scholar 

  • Thall, P. F., & Russell, K. E. (1998). A strategy for dose-finding and safety monitoring based on efficacy and adverse outcomes in phase I/II clinical trials. Biometrics, 251–264.

    Google Scholar 

  • Yan, F., Thall, P. F., Lu, K. H., Gilbert, M. R., & Yuan, Y. (2018). Phase I-II clinical trial design: A state-of-the-art paradigm for dose finding. Annals of Oncology, 29(3), 694–699.

    Article  Google Scholar 

  • Yeung, W. Y., Reigner, B., Beyer, U., Diack, C., Sabanés bové, D., Palermo, G., & Jaki, T. (2017). Bayesian adaptive dose-escalation designs for simultaneously estimating the optimal and maximum safe dose based on safety and efficacy. Pharmaceutical Statistics, 16(6), 396–413.

    Google Scholar 

  • Yin, G., Li, Y., & Ji, Y. (2006). Bayesian dose-finding in phase I/II clinical trials using toxicity and efficacy odds ratios. Biometrics, 62(3), 777–787.

    Google Scholar 

  • Yuan, Y., Nguyen, H. Q., & Thall, P. F. (2016). Bayesian designs for phase I-II clinical trials. New York: Chapman & Hall/CRC.

    Google Scholar 

  • Yuan, Y., & Yin, G. (2011). Bayesian phase I/II adaptively randomized oncology trials with combined drugs. The Annals of Applied Statistics, 5(2A), 924.

    Google Scholar 

  • Zang, Y., Lee, J. J., & Yuan, Y. (2014). Adaptive designs for identifying optimal biological dose for molecularly targeted agents. Clinical Trials, 11(3), 319–327.

    Google Scholar 

  • Zhang, W., Sargent, D. J., & Mandrekar, S. (2006). An adaptive dose-finding design incorporating both toxicity and efficacy. Statistics in Medicine, 25(14), 2365–2383.

    Google Scholar 

  • Zhou, Y., Lee, J. J., & Yuan, Y. (2019). A utility-based Bayesian optimal interval (U-BOIN) phase I/II design to identify the optimal biological dose for targeted and immune therapies. Statistics in Medicine, 38(28), S5299–S5316.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Haitao Pan .

Rights and permissions

Reprints and permissions

Copyright information

© 2023 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Pan, H., Yuan, Y. (2023). Optimal Biological Dose and Phase I/II Trials. In: Bayesian Adaptive Design for Immunotherapy and Targeted Therapy. Springer, Singapore. https://doi.org/10.1007/978-981-19-8176-0_3

Download citation

Publish with us

Policies and ethics