Abstract 709P
Background
Adaptive design (AD) trials have been developed as an innovative alternative to conventional design (CD) trials with the aim of accelerating innovative medicinal products (InMP) clinical development. Despite AD concept adoption by major competent authorities the use and implementation of AD remains substantially lower than CD. There is an emerging need to better understand the operational characteristics contributing to the challenges and opportunities for wider implementation of AD into oncology InMP development.
Methods
Oncology InMPs approved by the FDA in 2018 were selected for cross-sectional analysis. The ClinicalTrial.gov (CT.gov) platform was used to identify phase III trials conducted with those InMPs between 2010-2021. Analysis was then accomplished by PubMed search for full manuscripts associated with these trials, as additional source to describe trial design and methodology.
Results
Of the 63 indentified phase III trials, 47 (75%) were CD and 16 (25%) were AD. Among the AD, 81% were conducted in solid tumours and 19% in haematological malignancies. AD was associated with several distinct operational characteristics vs CD: i) with comparable number of patients enrolled, median number of sites/trial was higher in AD (203 sites) vs CD (106 sites) leading to substantial differences in median number of patients per individual site observed in CD (35.9 patients) and AD (3.8 patients); ii) AD was clearly associated with higher median number of secondary endpoints (18 endpoints) vs CD (12 endpoints) and substantially shorter median duration of trial (43 months) vs CD (60 months; p=.0129), with potential cost savings of up to 30%; iii) limited details on the AD methodology and decision-making process at the time of interim analysis.
Conclusions
The implementation of AD in oncology InMP development remains low as compared to CD. A degree of AD operational complexity vs CD could have been balanced by assumed stricter patient monitoring and compliance to the study protocol and collection of a larger set of scientific data. With a comparable number of enrolled patients, AD could substantially shorten overall study duration, which in turn leads to trial’s cost savings of up to 30%.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
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