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Optimized scaling o...
Optimized scaling of translational factors in oncology: from xenografts to RECIST
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- Baaz, Marcus, 1993 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences,Chalmers tekniska högskola,Chalmers University of Technology,Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik (FCC),Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC)
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- Cardilin, Tim, 1989 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences,Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik (FCC),Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC)
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Lignet, F. (författare)
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- Jirstrand, Mats, 1968 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences,Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik (FCC),Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC)
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(creator_code:org_t)
- 2022-08-03
- 2022
- Engelska.
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Ingår i: Cancer Chemotherapy and Pharmacology. - : Springer Science and Business Media LLC. - 0344-5704 .- 1432-0843. ; 90:3, s. 239-250
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Abstract
Ämnesord
Stäng
- Purpose Tumor growth inhibition (TGI) models are regularly used to quantify the PK-PD relationship between drug concentration and in vivo efficacy in oncology. These models are typically calibrated with data from xenograft mice and before being used for clinical predictions, translational methods have to be applied. Currently, such methods are commonly based on replacing model components or scaling of model parameters. However, difficulties remain in how to accurately account for inter-species differences. Therefore, more research must be done before xenograft data can fully be utilized to predict clinical response. Method To contribute to this research, we have calibrated TGI models to xenograft data for three drug combinations using the nonlinear mixed effects framework. The models were translated by replacing mice exposure with human exposure and used to make predictions of clinical response. Furthermore, in search of a better way of translating these models, we estimated an optimal way of scaling model parameters given the available clinical data. Results The predictions were compared with clinical data and we found that clinical efficacy was overestimated. The estimated optimal scaling factors were similar to a standard allometric scaling exponent of - 0.25. Conclusions We believe that given more data, our methodology could contribute to increasing the translational capabilities of TGI models. More specifically, an appropriate translational method could be developed for drugs with the same mechanism of action, which would allow for all preclinical data to be leveraged for new drugs of the same class. This would ensure that fewer clinically inefficacious drugs are tested in clinical trials.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Farmaceutiska vetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Pharmaceutical Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
- NATURVETENSKAP -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
Nyckelord
- Translational research
- Combination therapy
- Oncology
- Mathematical
- modeling
- Nonlinear mixed effects
- plasma-protein binding
- volumetric measurement
- tumor xenografts
- cancer-patients
- drug-treatment
- open-label
- models
- combination
- survival
- efficacy
- Oncology
- Pharmacology & Pharmacy
- Oncology
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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