Cargando…

An Informatics Bridge to Improve the Design and Efficiency of Phase I Clinical Trials for Anticancer Drug Combinations

In this study, we summarized critical databases of drug combination toxicity and pharmacokinetics. We further conducted a feasibility and utility study that demonstrates how different data sources can contribute to and assist phase I trial designs. Single-drug and drug combination toxicity and pharm...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Lei, Wei, Lai, Zhang, Shijun, Cheng, Lijun, Shendre, Aditi, Carson, Williams, Chen, James L., Owen, Dwight, Gregory, Megan, Li, Lang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10010310/
https://www.ncbi.nlm.nih.gov/pubmed/36922938
http://dx.doi.org/10.1158/2767-9764.CRC-22-0160
_version_ 1784906160332079104
author Wang, Lei
Wei, Lai
Zhang, Shijun
Cheng, Lijun
Shendre, Aditi
Carson, Williams
Chen, James L.
Owen, Dwight
Gregory, Megan
Li, Lang
author_facet Wang, Lei
Wei, Lai
Zhang, Shijun
Cheng, Lijun
Shendre, Aditi
Carson, Williams
Chen, James L.
Owen, Dwight
Gregory, Megan
Li, Lang
author_sort Wang, Lei
collection PubMed
description In this study, we summarized critical databases of drug combination toxicity and pharmacokinetics. We further conducted a feasibility and utility study that demonstrates how different data sources can contribute to and assist phase I trial designs. Single-drug and drug combination toxicity and pharmacokinetic data were primarily reviewed from several databases. We focused on the MTD, dose-limiting toxicity (DLT), toxicity, and pharmacokinetic profiles. To demonstrate the feasibility and utility of these data sources in improving trial designs, phase I studies reported in ClincalTrials.gov from January 1, 2018 to December 31, 2018 were used as examples. We evaluated whether and how these studies could have been designed differently given toxicity and pharmacokinetic data. None of the existing pharmacokinetic and toxicity databases contain either MTD or DLT. Among 268 candidate trials, four drug combinations were studied in other phase I trials before 2018; 185 combinations had complete or partial information on drug interactions or overlapping toxicity, and 79 combinations did not have available information. Two drug combination trials were selected as case studies. The nivolumab-axitinib trial could have been designed as a dose deescalating study, and the vinorelbine-trastuzumab emtansine trial could have been designed with a lower dose of either drug. Public data sources contain significant knowledge of the drug combination phase I trial design. Some important data (MTD and DLT) are not available in existing databases but in the literature. Some phase I studies could have been designed more efficiently with additional preliminary data. SIGNIFICANCE: Prior preclinical and clinical knowledge is critical for designing effective and efficient cancer drug combinatory trials. We reported results on the feasibility and utility of different informatics resources for contributing to and assisting phase I trial designs based on our designed classification approach. We also found that public data sources contained significant knowledge for drug combination phase I trial design, but some critical data elements (MTD and DLT) were missing.
format Online
Article
Text
id pubmed-10010310
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher American Association for Cancer Research
record_format MEDLINE/PubMed
spelling pubmed-100103102023-03-14 An Informatics Bridge to Improve the Design and Efficiency of Phase I Clinical Trials for Anticancer Drug Combinations Wang, Lei Wei, Lai Zhang, Shijun Cheng, Lijun Shendre, Aditi Carson, Williams Chen, James L. Owen, Dwight Gregory, Megan Li, Lang Cancer Res Commun Research Article In this study, we summarized critical databases of drug combination toxicity and pharmacokinetics. We further conducted a feasibility and utility study that demonstrates how different data sources can contribute to and assist phase I trial designs. Single-drug and drug combination toxicity and pharmacokinetic data were primarily reviewed from several databases. We focused on the MTD, dose-limiting toxicity (DLT), toxicity, and pharmacokinetic profiles. To demonstrate the feasibility and utility of these data sources in improving trial designs, phase I studies reported in ClincalTrials.gov from January 1, 2018 to December 31, 2018 were used as examples. We evaluated whether and how these studies could have been designed differently given toxicity and pharmacokinetic data. None of the existing pharmacokinetic and toxicity databases contain either MTD or DLT. Among 268 candidate trials, four drug combinations were studied in other phase I trials before 2018; 185 combinations had complete or partial information on drug interactions or overlapping toxicity, and 79 combinations did not have available information. Two drug combination trials were selected as case studies. The nivolumab-axitinib trial could have been designed as a dose deescalating study, and the vinorelbine-trastuzumab emtansine trial could have been designed with a lower dose of either drug. Public data sources contain significant knowledge of the drug combination phase I trial design. Some important data (MTD and DLT) are not available in existing databases but in the literature. Some phase I studies could have been designed more efficiently with additional preliminary data. SIGNIFICANCE: Prior preclinical and clinical knowledge is critical for designing effective and efficient cancer drug combinatory trials. We reported results on the feasibility and utility of different informatics resources for contributing to and assisting phase I trial designs based on our designed classification approach. We also found that public data sources contained significant knowledge for drug combination phase I trial design, but some critical data elements (MTD and DLT) were missing. American Association for Cancer Research 2022-09-06 /pmc/articles/PMC10010310/ /pubmed/36922938 http://dx.doi.org/10.1158/2767-9764.CRC-22-0160 Text en © 2022 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by/4.0/This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
spellingShingle Research Article
Wang, Lei
Wei, Lai
Zhang, Shijun
Cheng, Lijun
Shendre, Aditi
Carson, Williams
Chen, James L.
Owen, Dwight
Gregory, Megan
Li, Lang
An Informatics Bridge to Improve the Design and Efficiency of Phase I Clinical Trials for Anticancer Drug Combinations
title An Informatics Bridge to Improve the Design and Efficiency of Phase I Clinical Trials for Anticancer Drug Combinations
title_full An Informatics Bridge to Improve the Design and Efficiency of Phase I Clinical Trials for Anticancer Drug Combinations
title_fullStr An Informatics Bridge to Improve the Design and Efficiency of Phase I Clinical Trials for Anticancer Drug Combinations
title_full_unstemmed An Informatics Bridge to Improve the Design and Efficiency of Phase I Clinical Trials for Anticancer Drug Combinations
title_short An Informatics Bridge to Improve the Design and Efficiency of Phase I Clinical Trials for Anticancer Drug Combinations
title_sort informatics bridge to improve the design and efficiency of phase i clinical trials for anticancer drug combinations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10010310/
https://www.ncbi.nlm.nih.gov/pubmed/36922938
http://dx.doi.org/10.1158/2767-9764.CRC-22-0160
work_keys_str_mv AT wanglei aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT weilai aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT zhangshijun aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT chenglijun aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT shendreaditi aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT carsonwilliams aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT chenjamesl aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT owendwight aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT gregorymegan aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT lilang aninformaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT wanglei informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT weilai informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT zhangshijun informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT chenglijun informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT shendreaditi informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT carsonwilliams informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT chenjamesl informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT owendwight informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT gregorymegan informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations
AT lilang informaticsbridgetoimprovethedesignandefficiencyofphaseiclinicaltrialsforanticancerdrugcombinations