Designs of the clinical trials aiming at evaluating cell and gene therapy products: A critical appraisal from a literature review
Year: 2025
Type: article
Abstract: There is growing interest in advanced therapy medicinal products (ATMPs). However, there is debate about how they should be clinically evaluated. We aimed to assess the heterogeneity of trial designs used for ATMPs, based on a review of the most recently published ATMP trials from 2022 to 2024, and then make recommendations to improve the level of evidence. The 276 selected trials concerned CAR-T cells (28%), other gene therapies (22%), and somatic cell therapy (50%) and targeted different underlying diseases, hematological malignancies for CAR-T cells, genetic or congenital diseases for gene therapy, and other diseases for somatic cells ( p < 0.0001). The most common designs were single-center (48%), early-phase (63%), single-dose (74%) designs; randomization was used in close to one-third of trials, more common in somatic cells (43%). The median sample size was the highest for CAR-T cells therapy trials (26 vs. 15 and 20 for other gene and somatic cells therapy, respectively), and the median follow-up was the highest for other gene therapy (23.5 vs. 15.4 for CAR-T cells and 12.2 months for somatic cells therapy). These results highlight the relatively short-term nature of evaluation of these innovative products. Biard and colleagues reviewed 276 clinical trials evaluating cell and gene therapies. They show the heterogeneity of designs, depending on the type of therapy, country, and sponsor. They highlight the need to improve the level of evidence in the clinical evaluation of these therapies, by improving both design and reporting.
Source: Molecular Therapy Advances
Authors: Lucie Biard, Vincent Lévy, Sylvie Chevret, Annette Künkele, Stefanie Grunwald, Alessandro Aiuti, Bjarne Kuno Møller, Reno Debets, Stephan Mielke, Johan van Eldere, Antonia Müller, Silvia Martin Lluesma, Lorena Consolino, Matt Bolz-Johnson, Stefano Benvenuti, Ulrich Blache, Piret Fischer, Carmen Sanges
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
Award: G2306885538
OpenAlex ID: W7117295157
