Forecasting for the Pharmaceutical Industry: Models for New Product and In-Market Forecasting and How to Use Them

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Forecasting for the Pharmaceutical Industry: Models for New Product and In-Market Forecasting and How to Use Them

Forecasting for the Pharmaceutical Industry: Models for New Product and In-Market Forecasting and How to Use Them


Forecasting for the Pharmaceutical Industry: Models for New Product and In-Market Forecasting and How to Use Them


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Forecasting for the Pharmaceutical Industry: Models for New Product and In-Market Forecasting and How to Use Them

Product details

Hardcover: 234 pages

Publisher: Routledge; 2 edition (May 8, 2015)

Language: English

ISBN-10: 9781472460110

ISBN-13: 978-1472460110

ASIN: 1472460111

Product Dimensions:

7 x 1 x 10 inches

Shipping Weight: 1.4 pounds (View shipping rates and policies)

Average Customer Review:

4.1 out of 5 stars

5 customer reviews

Amazon Best Sellers Rank:

#641,898 in Books (See Top 100 in Books)

The structure of the book is well done however, I had several problems in Chapter 3 (New product forecasting) as some charts, especially in pages 60 and 61 are not well documented. By that I mean that you have the equation but the author doesn't give you the meaning of the constants (a, b, c) and how it influences the charts. Methodologically it was a disaster. So I switched to other sources for this part.Apart from that, the book gives you some ideas about algorithms but it may not be sufficient and after the methodology issues I had, I have some doubts about the validity of the whole book.Moreover, the book is quite expensive and be aware that you can find some chapters free on the web only by typing the title of the book and pdf.

Nicely covers the broad areas of forecasting, and thats just what it does. It does not get in to the details. So if you are someone who wants to brush your knowledge then this is for you, but if you are looking to learn new methods then maybe you may want to look at some other options.

If you don't know anything about forecasting this book is a great starting point!

This is a slim book with lots of good information for anybody wanting to get started forecasting their pharmaceutical and biotechnology products, as well as emerging companies with little portfolio management infrastructure looking to strengthen their forecasting process. There is much to be learned and few wasted words. Unlike many books that are used in a classroom setting and are intended primarily as a reference text this book presents forecasting in a practical and concise manner that makes you want to get started. This is a book that can be read cover to cover in three or four hours, so you get the whole picture in one or two bites.Highly recommended as an introductory or refresher text for anybody involved in pharmaceutical or biotechnology product forecasting, and those involved in product development who wants to get a better handle on what their product is capable of achieving in the commercial setting.The book is not inexpensive, but it offers a good payback in terms of price and time invested. If you order from Amazon you have the comfort of knowing that if the book doesn't meet your expectations you can easily return it for a refund less a small shipping charge. Unlike many other generic forecasting books this one addresses the unique characteristics of the pharmaceutical market and stays away from a heavy statistics treatment. Biopharma new product forecasting benefits more from a strong analytical approach than any mathematical treatment.

Art Cook is a guru in pharma forecasting. The depth and detail of this book simply shows it. The book covers all key aspects of pharma forecasting and is very easy to read. It has many explanatory diagrams and charts, and even features a detailed case study. I highly recommend this book to anyone who wants to make a career in new drug forecasting. This book will bring you up to speed very quickly.

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Forecasting for the Pharmaceutical Industry: Models for New Product and In-Market Forecasting and How to Use Them


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