Back

Ethical and human subject burdens of trials conducted to evaluate biosimilars

Ohn, J. A.; Atteberry, P. J.; Trusheim, M. R.; Bach, P. B.

2021-03-09 health policy
10.1101/2021.03.05.21252938 medRxiv
Show abstract

Background/AimsWith a policy goal of introducing price competition into the market for biologic drugs after their period of market monopoly is over (called loss of exclusivity), policymakers created a pathway for companies to make copies of those treatments and termed them biosimilars. But unlike generic drugs, biosimilar drug copies must be studied in human trials to assure they have the same clinical effect as the original biologic products. The burden that this places on human subject participants, and the opportunity cost on the clinical trial system generally, have not been considered in detail. MethodsFor all biosimilar drugs in development, approved, or that failed to obtain approval in the US, we abstracted from clinicaltrials.gov registry the number of subjects enrolled at each phase of development. ResultsWe identified 105 clinical trials for approved or withdrawn biosimilars and another 20 studies that are either planned, ongoing or completed for biosimilars in development. These studies collectively enrolled (or plan to enroll) 38,169 human subjects. Most (28,130) are enrolled in phase 3 studies. The mean number of human subject participants per approval is 1,045, about 25% of the number required for a new drug approval on average. ConclusionsA consequential number of human subjects are required for the testing of biosimilar drugs prior to approval. The explicit and sole purpose of biosimilars is to induce competition in order to lower prices of biologic drugs after loss of exclusivity. The burden the biosimilar approval trials place on human subjects with no direct clinical benefits but definite risks, and the possibility that they rob subjects from trials that are of more scientific importance, are ones policymakers might consider. Price regulation of biologic drugs after loss of exclusivity could achieve lower prices as well, without the burdens of the current approach. Funding SourceArnold Ventures (Grant to support Drug Pricing Lab at Memorial Sloan Kettering Cancer Center)

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.