Using analogue data to substantiate long-term durability of gene therapies: a narrative review
| Autor: | Michaela Sharpe, Laura Beswick, Panos Kefalas |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Regenerative Medicine. 17:767-782 |
| ISSN: | 1746-076X 1746-0751 |
| DOI: | 10.2217/rme-2021-0159 |
| Popis: | The number of gene therapies in clinical trials and moving toward licensure is increasing. Most gene therapies are designed to achieve long-term effects, but at licensure the data to support claims of long-term durability are often limited, as long-term monitoring studies are often part of post-approval commitments by companies. Health technology assessors must therefore assess the potential for the long-term durability of a product and the potential cost-effectiveness based on the data available. The authors explored the benefit of strengthening the ability to infer durability of effect using analogue category data. Different analogue categories were assessed for the potential to substantiate claims of sustainability of effect for gene therapies by leveraging biological plausibility arguments. The authors propose a pathway for identifying potential analogues. Such a pathway should help establish plausible or theoretical long-term outcomes that can be considered in value assessments of gene therapies.Many diseases, affecting all parts of the body, can be treated with gene therapy. Gene therapies make changes to a person's genes by either replacing or inactivating a gene that is causing disease or by adding new genes that can fight diseases such as cancers. These therapies have the potential to cure patients of the disease for their lifetime. When decisions are being made over whether gene therapies are safe and work well in patients, it can be difficult to understand if they will maintain their benefits to a person over a lifetime, as they have only been studied in clinical trials for a much shorter amount of time. In this paper, the authors explore whether information around the benefits of therapies that work in a similar way, or target similar diseases, can be used to strengthen an understanding of how well newer therapies work over a long period of time. The authors propose a pathway that can be followed to identify the suitability of a comparison between different therapies and how the evidence of benefit over time can be interpreted. This information will be useful for developers of gene therapies who are trying to generate evidence of long-term benefit to patients, as well as for decision makers who need to understand how well these gene therapies will work over a patient's lifetime. |
| Databáze: | OpenAIRE |
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