Literature DB >> 32757299

Strategies and Recommendations for Using a Data-Driven and Risk-Based Approach in the Selection of First-in-Human Starting Dose: An International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) Assessment.

Michael W Leach1, David O Clarke2, Sherri Dudal3, Chao Han4, Chunze Li5, Zheng Yang6, Frank R Brennan7, Wendy J Bailey8, Yingxue Chen9, Antoine Deslandes10, Lise I Loberg11, Kapil Mayawala12, Mark C Rogge13, Marque Todd14, Nagendra V Chemuturi15.   

Abstract

Various approaches to first-in-human (FIH) starting dose selection for new molecular entities (NMEs) are designed to minimize risk to trial subjects. One approach uses the minimum anticipated biological effect level (MABEL), which is a conservative method intended to maximize subject safety and designed primarily for NMEs having high perceived safety risks. However, there is concern that the MABEL approach is being inappropriately used for lower risk molecules with negative impacts on drug development and time to patient access. In addition, ambiguity exists in how MABEL is defined and the methods used to determine it. The International Consortium for Innovation and Quality in Pharmaceutical Development convened a working group to understand current use of MABEL and its impact on FIH starting dose selection, and to make recommendations for FIH dose selection going forward. An industry-wide survey suggested the achieved or estimated maximum tolerated dose, efficacious dose, or recommended phase II dose was > 100-fold higher than the MABEL-based starting dose for approximately one third of NMEs, including trials in patients. A decision tree and key risk factor table were developed to provide a consistent, data driven-based, and risk-based approach for selecting FIH starting doses.
© 2020 The Authors Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.

Entities:  

Year:  2020        PMID: 32757299     DOI: 10.1002/cpt.2009

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  2 in total

1.  Translational Modeling Predicts Efficacious Therapeutic Dosing Range of Teclistamab for Multiple Myeloma.

Authors:  Suzette Girgis; Shun Xin Wang Lin; Kodandaram Pillarisetti; Arnob Banerjee; Tara Stephenson; Xuewen Ma; Shoba Shetty; Tong-Yuan Yang; Brandi W Hilder; Qun Jiao; Brett Hanna; Homer C Adams; Yu-Nien Sun; Amarnath Sharma; Jennifer Smit; Jeffrey R Infante; Jenna D Goldberg; Yusri Elsayed
Journal:  Target Oncol       Date:  2022-06-24       Impact factor: 4.864

2.  De-risking Clinical Trials: The BIAL Phase I Trial in Foresight.

Authors:  Adam F Cohen; Jeroen van Smeden; David J Webb
Journal:  Clin Pharmacol Ther       Date:  2021-12-28       Impact factor: 6.903

  2 in total

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