Improving early phase oncology clinical trial design: The case for finding the optimal biological dose
Authors: Phillips, A. and Mondal, S.
Journal: Pharmaceutical Statistics
Volume: 22
Issue: 4
Pages: 739-747
eISSN: 1539-1612
ISSN: 1539-1604
DOI: 10.1002/pst.2291
Abstract:Historically early phase oncology drug development programmes have been based on the belief that “more is better”. Furthermore, rule-based study designs such as the “3 + 3” design are still often used to identify the MTD. Phillips and Clark argue that newer Bayesian model-assisted designs such as the BOIN design should become the go to designs for statisticians for MTD finding. This short communication goes one stage further and argues that Bayesian model-assisted designs such as the BOIN12 which balances risk-benefit should be included as one of the go to designs for early phase oncology trials, depending on the study objectives. Identifying the optimal biological dose for future research for many modern targeted drugs, immunotherapies, cell therapies and vaccine therapies can save significant time and resources.
Source: Scopus
Improving early phase oncology clinical trial design: The case for finding the optimal biological dose.
Authors: Phillips, A. and Mondal, S.
Journal: Pharm Stat
Volume: 22
Issue: 4
Pages: 739-747
eISSN: 1539-1612
DOI: 10.1002/pst.2291
Abstract:Historically early phase oncology drug development programmes have been based on the belief that "more is better". Furthermore, rule-based study designs such as the "3 + 3" design are still often used to identify the MTD. Phillips and Clark argue that newer Bayesian model-assisted designs such as the BOIN design should become the go to designs for statisticians for MTD finding. This short communication goes one stage further and argues that Bayesian model-assisted designs such as the BOIN12 which balances risk-benefit should be included as one of the go to designs for early phase oncology trials, depending on the study objectives. Identifying the optimal biological dose for future research for many modern targeted drugs, immunotherapies, cell therapies and vaccine therapies can save significant time and resources.
Source: PubMed
Improving early phase oncology clinical trial design: The case for finding the optimal biological dose
Authors: Phillips, A. and Mondal, S.
Journal: PHARMACEUTICAL STATISTICS
Volume: 22
Issue: 4
Pages: 739-747
eISSN: 1539-1612
ISSN: 1539-1604
DOI: 10.1002/pst.2291
Source: Web of Science (Lite)
Improving early phase oncology clinical trial design: The case for finding the optimal biological dose.
Authors: Phillips, A. and Mondal, S.
Journal: Pharmaceutical statistics
Volume: 22
Issue: 4
Pages: 739-747
eISSN: 1539-1612
ISSN: 1539-1604
DOI: 10.1002/pst.2291
Abstract:Historically early phase oncology drug development programmes have been based on the belief that "more is better". Furthermore, rule-based study designs such as the "3 + 3" design are still often used to identify the MTD. Phillips and Clark argue that newer Bayesian model-assisted designs such as the BOIN design should become the go to designs for statisticians for MTD finding. This short communication goes one stage further and argues that Bayesian model-assisted designs such as the BOIN12 which balances risk-benefit should be included as one of the go to designs for early phase oncology trials, depending on the study objectives. Identifying the optimal biological dose for future research for many modern targeted drugs, immunotherapies, cell therapies and vaccine therapies can save significant time and resources.
Source: Europe PubMed Central