Exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside
Cell therapies are emerging as promising treatments for a range of liver diseases but translational bottlenecks still remain including: securing and assessing the safe and effective delivery of cells to the disease site; ensuring successful cell engraftment and function; and preventing immunogenic r...
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| Format: | Journal article |
| Language: | English |
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Springer Nature
2024
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| _version_ | 1811140147953008640 |
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| author | Waters, S |
| author_facet | Waters, S |
| author_sort | Waters, S |
| collection | OXFORD |
| description | Cell therapies are emerging as promising treatments for a range of liver diseases but translational
bottlenecks still remain including: securing and assessing the safe and effective delivery of cells to
the disease site; ensuring successful cell engraftment and function; and preventing immunogenic
responses. Here we highlight three therapies, each utilising a different cell type, at different stages in
their clinical translation journey: transplantation of multipotent mesenchymal stromal/signalling
cells, hepatocytes and macrophages. To overcome bottlenecks impeding clinical progression, we
advocate for wider use of mechanistic in silico modelling approaches. We discuss how in silico
approaches, alongside complementary experimental approaches, can enhance our understanding of
the mechanisms underlying successful cell delivery and engraftment. Furthermore, such combined
theoretical-experimental approaches can be exploited to develop novel therapies, address safety
and efficacy challenges, bridge the gap between in vitro and in vivo model systems, and compensate
for the inherent differences between animal model systems and humans. We also highlight how in
silico model development can result in fewer and more targeted in vivo experiments, thereby
reducing preclinical costs and experimental animal numbers and potentially accelerating translation
to the clinic. The development of biologically-accurate in silico models that capture the mechanisms
underpinning the behaviour of these complex systems must be reinforced by quantitative methods
to assess cell survival post-transplant, and we argue that non-invasive in vivo imaging strategies
should be routinely integrated into transplant studies. |
| first_indexed | 2024-04-09T03:56:55Z |
| format | Journal article |
| id | oxford-uuid:84e7e094-5664-47b0-b15b-77ff15bdef98 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:17:22Z |
| publishDate | 2024 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | oxford-uuid:84e7e094-5664-47b0-b15b-77ff15bdef982024-07-20T15:44:00ZExploiting in silico modelling to enhance translation of liver cell therapies from bench to bedsideJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:84e7e094-5664-47b0-b15b-77ff15bdef98EnglishSymplectic ElementsSpringer Nature2024Waters, SCell therapies are emerging as promising treatments for a range of liver diseases but translational bottlenecks still remain including: securing and assessing the safe and effective delivery of cells to the disease site; ensuring successful cell engraftment and function; and preventing immunogenic responses. Here we highlight three therapies, each utilising a different cell type, at different stages in their clinical translation journey: transplantation of multipotent mesenchymal stromal/signalling cells, hepatocytes and macrophages. To overcome bottlenecks impeding clinical progression, we advocate for wider use of mechanistic in silico modelling approaches. We discuss how in silico approaches, alongside complementary experimental approaches, can enhance our understanding of the mechanisms underlying successful cell delivery and engraftment. Furthermore, such combined theoretical-experimental approaches can be exploited to develop novel therapies, address safety and efficacy challenges, bridge the gap between in vitro and in vivo model systems, and compensate for the inherent differences between animal model systems and humans. We also highlight how in silico model development can result in fewer and more targeted in vivo experiments, thereby reducing preclinical costs and experimental animal numbers and potentially accelerating translation to the clinic. The development of biologically-accurate in silico models that capture the mechanisms underpinning the behaviour of these complex systems must be reinforced by quantitative methods to assess cell survival post-transplant, and we argue that non-invasive in vivo imaging strategies should be routinely integrated into transplant studies. |
| spellingShingle | Waters, S Exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside |
| title | Exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside |
| title_full | Exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside |
| title_fullStr | Exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside |
| title_full_unstemmed | Exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside |
| title_short | Exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside |
| title_sort | exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside |
| work_keys_str_mv | AT waterss exploitinginsilicomodellingtoenhancetranslationoflivercelltherapiesfrombenchtobedside |