Evaluating Various Predictors Suspected of Influencing Biosimilar Market Share in the U.S.

OBJECTIVES: Following the assessment of variables influencing originator market share, we sought to examine predictors of individual biosimilar market share.

METHODS: A multivariate linear regression analysis included 26 commercially available biosimilars and their 10 respective originators. Variables included biosimilar market share relative to molecule volume, number of biosimilar competitors, duration of biosimilar competition, price differentials to the originator, and payer management. An analysis of 15 health plans’ formulary documents as of 12/1/23 was conducted to identify step therapy requirements for each product. Market share and model inputs were captured from FDA, NORD, Drugs.com, and other publicly available sources. The significance level was α=0.05.

RESULTS: The 5-variable model including all 26 products was statistically significant with an R² of 0.524 (p=0.003). After adjusting for all variables in the model, duration of biosimilar duration and payer management were the only statistically significant predictors of market share (p=0.011 for each). These results suggest a 1% increase in market share was associated with an aggregate of ~3 fewer steps and an increase in duration of biosimilar competition by 0.06 days. The R² for this model indicates that over 52% of the variability in biosimilar market share was accounted for by the combination of other predictor variables included.

CONCLUSIONS: Only duration of competition and payer management are significant individual predictors of biosimilar market share. The lack of significance of price differential as a major predictor of uptake may be explained by the use of list price rather than net price, which is likely a stronger predictor of access and subsequent uptake since it includes discounts and rebates to payers. Inclusion of net price within the model is likely to improve the accuracy of predicting biosimilar market share.