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Forecasting branded and generic pharmaceuticals

journal contribution
posted on 2023-06-09, 02:40 authored by Konstantinos Nikolopoulos, Samantha Buxton, Marv Khammash, Philip Stern
We forecast UK pharmaceutical time series before and after the time of patent expiry. This is a critical point in the lifecycle, as a generic form of the product is then introduced into the market, while the branded form is still available for prescription. Forecasting the numbers of units of branded and generic forms of pharmaceuticals dispensed is becoming increasingly important, due to their huge market value and the limited number of new ‘blockbuster’ branded drugs, as well as the imposed cost for national healthcare systems like the NHS. In this paper, eleven methods are used to forecast drug time series, including diffusion models (Bass model & RPDM), ARIMA, exponential smoothing (Simple and Holt), nai¨ve and regression methods. ARIMA and Holt produce accurate short term (annual) forecasts for branded and generic drugs respectively, while for the more strategic horizons of 2–5 years ahead, nai¨ve with drift provides the most accurate forecasts.

History

Publication status

  • Published

File Version

  • Published version

Journal

International Journal of Forecasting

ISSN

0169-2070

Publisher

Elsevier

Issue

2

Volume

32

Page range

344-357

Department affiliated with

  • Business and Management Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2016-08-30

First Compliant Deposit (FCD) Date

2016-08-29

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