precautionary implements new layers of patient-centered safety analysis for phase 1 dose-escalation trials, adding diagnostics to examine the safety characteristics of these designs in light of expected inter-individual variation in pharmacokinetics and pharmacodynamics. See Norris (2020b), “Retrospective analysis of a fatal dose-finding trial” arXiv:2004.12755 and (2020c) “What Were They Thinking? Pharmacologic priors implicit in a choice of 3+3 dose-escalation design” arXiv:2012.05301.


Releases starting with 0.2.3 incorporate fast numerics implemented in Rust, a modern programming language that emphasizes performance and reliability—attributes crucial to applications such as the analysis of clinical trials.

These innovations have delayed review and acceptance by CRAN, pending which the newest features of precautionary will be available only here on GitHub.

# Install release version from GitHub

# Install obsolete version from CRAN (where review of new Rust library remains pending)

To date, those features of precautionary which depend on the Prolog code in exec/prolog/ have been prebuilt into the package, for example as the arrays T[,,,] written into R/sysdata.rda by exec/make_sysdata_TUb.R. Methodologists who wish to examine, recompute and verify these arrays are advised to install Scryer Prolog.

It is a near-term goal for precautionary to reveal more transparently Prolog’s special contributions to its analysis of dose-escalation designs.


Please see the vignettes under the Articles tab above.


The precautionary package is the pointy end of the spear in a larger DTAT research programme, of which the following are key outputs. Several of these citations have accompanying online resources such as web applications. For the key references, lay explanations are available.

  1. Norris DC. Dose Titration Algorithm Tuning (DTAT) should supersede ‘the’ Maximum Tolerated Dose (MTD) in oncology dose-finding trials. F1000Research. 2017;6:112. doi:10.12688/f1000research.10624.3. [lay explanation]
  2. –––––. Dose Titration Algorithm Tuning (DTAT) should supplant ‘the’ MTD. May 2017. [podium presentation] Symposium on Dose Selection for Cancer Treatment Drugs, Stanford Center for Innovative Study Design (CISD) May 12, 2017. doi:10.7490/f1000research.1114209.1.
  3. –––––. Costing ‘the’ MTD. bioRxiv. August 2017:150821. doi:10.1101/150821. [lay explanation]
  4. –––––. Costing ‘the’ MTD: What Is the Economic and Human Cost of 1-Size-Fits-All Dose Finding in Oncology? [poster] Presented at 8th American Conference on Pharmacometrics (ACoP8), October 16, 2017. doi:10.7490/f1000research.1114988.1.
  5. –––––. One-size-fits-all dosing in oncology wastes money, innovation and lives. Drug Discovery Today. 2018;23(1):4-6. doi:10.1016/j.drudis.2017.11.008. [Shiny app]
  6. –––––. Precautionary Coherence Unravels Dose Escalation Designs. bioRxiv. December 2017:240846. doi:10.1101/240846. [lay explanation] [D3 app]
  7. –––––. Costing ‘the’ MTD … in 2-D. bioRxiv. July 2018:370817. doi:10.1101/370817 [lay explanation]
  8. –––––. Ethical Review and Methodologic Innovation in Phase 1 Cancer Trials. JAMA Pediatrics. April 2019. doi:10.1001/jamapediatrics.2019.0811 [2-minute video]
  9. –––––. Impeachment of One-Size-Fits-All Dosing for Obstruction of Synergism. [working paper] December 4, 2019. doi:10.17605/OSF.IO/S7XDU. [2-minute video]
  10. –––––. Comment on Wages et al., Coherence principles in interval-based dose finding. Pharmaceutical Statistics 2019, DOI: 10.1002/pst.1974. Pharmaceutical Statistics. March 2020. doi:10.1002/pst.2016 [additional background]
  11. –––––. Retrospective analysis of a fatal dose-finding trial. arXiv:2004.12755 [stat, q-bio]. April 2020. [Tweetorial]
  12. Norris DC, Sen S, Groisberg R, Subbiah V. Patient-Centered, Physician-Investigator Friendly Pragmatic Phase I/II Trial Designs—The 4P Model. Mayo Clinic Proceedings. 2020;95(11):2566-2568. doi:10.1016/j.mayocp.2020.09.009
  13. Norris DC. What Were They Thinking? Pharmacologic priors implicit in a choice of 3+3 dose-escalation design. arXiv:2012.05301 [stat, q-bio]. December 9, 2020. [Tweetorial]