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DTAT (version 0.3-4)

DTAT-package: Dose Titration Algorithm Tuning: a Framework for Dose Individualization in Drug Development

Description

Dose Titration Algorithm Tuning (DTAT) is a methodologic framework allowing dose individualization to be conceived as a continuous learning process that begins in early-phase clinical trials and continues throughout drug development, on into clinical practice. This package includes code that researchers may use to reproduce or extend key results of the DTAT research programme, plus tools for trialists to design and simulate a '3+3/PC' dose-finding study. Please see Norris (2017) tools:::Rd_expr_doi("10.12688/f1000research.10624.3") and Norris (2017) tools:::Rd_expr_doi("10.1101/240846").

Arguments

Author

David C. Norris

References

  1. Norris DC. Dose Titration Algorithm Tuning (DTAT) should supersede ‘the’ Maximum Tolerated Dose (MTD) in oncology dose-finding trials. F1000Research. 2017;6:112. tools:::Rd_expr_doi("10.12688/f1000research.10624.3"). https://f1000research.com/articles/6-112/v3

  2. Norris DC. Costing ‘the’ MTD. bioRxiv. August 2017:150821. tools:::Rd_expr_doi("10.1101/150821"). http://www.biorxiv.org/content/early/2017/08/22/150821

  3. Norris DC. Precautionary Coherence Unravels Dose Escalation Designs. bioRxiv. December 2017:240846. tools:::Rd_expr_doi("10.1101/240846"). https://www.biorxiv.org/content/early/2017/12/29/240846

  4. Norris DC. One-size-fits-all dosing in oncology wastes money, innovation and lives. Drug Discov Today. 2018;23(1):4-6. tools:::Rd_expr_doi("10.1016/j.drudis.2017.11.008"). https://www.sciencedirect.com/science/article/pii/S1359644617303586

  5. Norris DC. Costing ‘the’ MTD ... in 2-D. bioRxiv. July 2018:370817. tools:::Rd_expr_doi("10.1101/370817"). https://www.biorxiv.org/content/early/2018/07/17/370817