How translational modeling in oncology needs to get the mechanism just right
Abstract Translational model‐based approaches have played a role in increasing success in the development of novel anticancer treatments. However, despite this, significant translational uncertainty remains from animal models to patients. Optimization of dose and scheduling (regimen) of drugs to max...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-03-01
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| Series: | Clinical and Translational Science |
| Online Access: | https://doi.org/10.1111/cts.13183 |
| _version_ | 1818287979794268160 |
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| author | James W. T. Yates David A Fairman |
| author_facet | James W. T. Yates David A Fairman |
| author_sort | James W. T. Yates |
| collection | DOAJ |
| description | Abstract Translational model‐based approaches have played a role in increasing success in the development of novel anticancer treatments. However, despite this, significant translational uncertainty remains from animal models to patients. Optimization of dose and scheduling (regimen) of drugs to maximize the therapeutic utility (maximize efficacy while avoiding limiting toxicities) is still predominately driven by clinical investigations. Here, we argue that utilizing pragmatic mechanism‐based translational modeling of nonclinical data can further inform this optimization. Consequently, a prototype model is demonstrated that addresses the required fundamental mechanisms. |
| first_indexed | 2024-12-13T01:49:06Z |
| format | Article |
| id | doaj.art-81fc557ca8994fe9985f407ffa399e2f |
| institution | Directory Open Access Journal |
| issn | 1752-8054 1752-8062 |
| language | English |
| last_indexed | 2024-12-13T01:49:06Z |
| publishDate | 2022-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Clinical and Translational Science |
| spelling | doaj.art-81fc557ca8994fe9985f407ffa399e2f2022-12-22T00:03:35ZengWileyClinical and Translational Science1752-80541752-80622022-03-0115358860010.1111/cts.13183How translational modeling in oncology needs to get the mechanism just rightJames W. T. Yates0David A Fairman1DMPK In Vitro In Vivo Translation GSK Stevenage UKClinical Pharmacology, Modelling and Simulation GSK Stevenage UKAbstract Translational model‐based approaches have played a role in increasing success in the development of novel anticancer treatments. However, despite this, significant translational uncertainty remains from animal models to patients. Optimization of dose and scheduling (regimen) of drugs to maximize the therapeutic utility (maximize efficacy while avoiding limiting toxicities) is still predominately driven by clinical investigations. Here, we argue that utilizing pragmatic mechanism‐based translational modeling of nonclinical data can further inform this optimization. Consequently, a prototype model is demonstrated that addresses the required fundamental mechanisms.https://doi.org/10.1111/cts.13183 |
| spellingShingle | James W. T. Yates David A Fairman How translational modeling in oncology needs to get the mechanism just right Clinical and Translational Science |
| title | How translational modeling in oncology needs to get the mechanism just right |
| title_full | How translational modeling in oncology needs to get the mechanism just right |
| title_fullStr | How translational modeling in oncology needs to get the mechanism just right |
| title_full_unstemmed | How translational modeling in oncology needs to get the mechanism just right |
| title_short | How translational modeling in oncology needs to get the mechanism just right |
| title_sort | how translational modeling in oncology needs to get the mechanism just right |
| url | https://doi.org/10.1111/cts.13183 |
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