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requesters a nonexclusive license to certain patented technologies essential for development and commercialization of gene therapy products. The incentive for pharmaceutical rms to ll their drug development pipeline through consolidation can be appreciated by examining how few truly new drugs are released by the top pharmaceutical rms every year. Figure 2.5 illustrates the number of new but not necessarily blockbuster drugs released by the top 10 pharmaceutical rms worldwide during the ve-year period from 1998 through 2002. P zer, the number one pharmaceutical rm in terms of market capitalization, released, on average, one drug per year. The second ranked company, Johnson & Johnson, had no new drugs during the same period. Merck, GlaxoSmithKline, and Novartis each introduced more than one drug per year, on average, during the ve-year period. It s interesting to note that Novar tis, with eight new drugs introduced in 1998 through 2002, achieved its

(9.2.16)

This chapter demonstrates the following techniques:

N(N -1) =

(9.2.17)

(Cn )

(9 2 8) .. 1

Con guring a data source for object binding Using connect-the-dots binding Building a form from a business object Binding to a generic collection Binding to a DataTable De ning business/validation rules in properties Using the ErrorProvider control 357

where angular bracket refers to average over realizations. 2.3 Percus-Yevick Approximation of Pair Distribution Functions

In 8, we have studied three-dimensional pair distribution functions based on the Percus-Yevick approximation. These results are based on the analytic closed form solution for the direct correlation function. However, for the case of two-dimensional problems, there are no closed form analytic solution for the direct correlation function. There are numerical slutions

Pfizer Johnson & Johnson Merck GlaxoSmithKline Novartis Amgen Eli Lilly & Co. AstraZeneca Abbot Laboratories Wyeth

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of Percus-Yevick integral equation for the case of hard disks [Lado, 1968]. There are also approximate analytic expressions for the direct correlation functions of hard disks. We summarize the results Ripoll and Tejero [1995] on the approximate analytic expressions for the two-dimensional case. Let

(9.2.19)

7

where r is the radial distance between the two disks and b is the diameter of the disk. Also, the two-dimensional fractional volume is

(9.2.20)

where a = b/2 is the radius of the disk and no is the number of particles per unit area. Then, under the Percus-Yevick approximation,

(9.2.21)

(~) +S2(J)X]

Object binding is great fun You can accomplish much with object binding by simply creating properties in your business object classes and then using Visual Studio to build forms from those business object classes But to get the most from object binding, you also need to incorporate validation and display of data entry errors to the user This chapter covers all these techniques

(9.2.22)

2 4 6 8

W2(X) =

[cos- X -

(9.2.23) (9.2.24) (9.2.25 )

NOTE: All the information on object binding in this chapter is for Windows forms only Object binding for the Web is significantly different and is not covered in this book

(f) = 3f2 [8(1 - 2p) c(O)

= _ 1 + f + 3pf2 (1 - f)3

=- - 3

(9.2.26)

Before going through the details of how to use object binding, it is important to understand exactly what it is and what it is not Object binding is binding your business object properties to user interface elements Object binding is not database binding in the strict sense of the term It does not directly collect or bind any data from your database When you are using business object classes without object binding, the ow of data from the database to your user interface and back again requires these steps: 1 The business object calls the data access component to get the data from the database and sets the business object properties using that data For example, the Product class calls the data access component, which uses a query or stored procedure to ll a DataTable from the Product table The data access component returns the DataTable to the Product class, which assigns each eld from the table to a property of the object To illustrate, the line of code required to get the ProductName eld from the DataTable and set the ProductName property is as follows:

Given the direct correlation function, we can use the Ornstein-Zernike equation to calculate the pair distribution function g(r)

FIGURE 2.5 Number of new drugs released by the top ten pharmaceutical rms,

h(r) = g(r) - 1

(9.2.27)

where h(r) is the total correlation which is related to c(r) by means of the Ornstein-Zernike equation

myProductProductName = dtRows(0)Item("ProductName")

h(rI2) = c (rI2)

Define the two-dimensional Fourier transforms of h(r) and c(r)

H(P)

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