Forecasting for the Pharmaceutical Industry: Models for New Product And In-market Forecasting And How to Use Them

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In virtually every decision, a pharmaceutical executive considers some type of forecast. This process of predicting the future is crucial to many aspects of the company - from next month's production schedule, to market estimates for drugs in the next decade. The pharmaceutical forecaster needs to strike a delicate balance between over-engineering the forecast - including rafts of data and complex 'black box' equations that few stakeholders understand and even fewer buy into - and an overly simplistic approach that relies too heavily on anecdotal information and opinion. Art Cook's highly pragmatic guide explains the basis of a successful balanced forecast for products in development as well as currently marketed products. The author explores the pharmaceutical forecasting process; the varied tools and methods for new product and in-market forecasting; how they can be used to communicate market dynamics to the various stakeholders; and the strengths and weaknesses of different forecast approaches. The text is liberally illustrated with tables, diagrams and examples. The final extended case study provides the reader with an opportunity to test out their knowledge. "Forecasting for the Pharmaceutical Industry" is a definitive guide for forecasters as well as the multitude of decision makers and executives who rely on forecasts in their decision making.

Author(s): Arthur G., Ph.D. Cook
Edition: 1
Year: 2006

Language: English
Pages: 141

Contents......Page 6
List of Figures......Page 8
List of Tables......Page 12
List of Abbreviations......Page 14
Acknowledgements......Page 16
Foreword......Page 18
The Inaccuracy of Forecasting......Page 20
Forecasting in the Pharmaceutical Industry......Page 22
The Current State: Influences Across Functions......Page 24
The Time Horizon for the Forecast......Page 27
In Summary......Page 28
Define the Forecast......Page 30
Select a Forecast Method......Page 33
Enable Analytic Insights......Page 39
Present the Results......Page 50
Final Considerations......Page 52
New Product Forecast Algorithm......Page 54
Modelling the Market......Page 55
Forecasting the Product......Page 68
Converting Patients to Revenue......Page 84
Final Considerations......Page 88
In-Market Product Forecast Algorithm......Page 90
Trending Historical Data......Page 91
Applying the Effects of Ex-Trend Events......Page 97
Converting Trended Data into Forecast Outputs......Page 110
Final Considerations......Page 119
Era of Revitalisation......Page 120
Create Stories, Not Spreadsheets......Page 121
Holistic Forecasting......Page 123
6 PHARMACO – A FORECASTING CASE STUDY......Page 126
Suggested Answers......Page 140
Appendix: Forecast Techniques......Page 150
References and Further Reading......Page 154
F......Page 158
S......Page 159
W......Page 160