New product development processes need to be compliant to regulatory requirements, and this chapter highlights the salient processes and quality systems to put into place to achieve success. Project management is made simple with specific tools provided here. Customer feedback is channeled into specific product characteristics, and the right tools are shown in this chapter. The biopharma industry has statistics showing less than 10% of starting compounds succeed in reaching market approval, and this chapter explains what causes these failures. The key issues that have repeatedly caused failure during device and diagnostic product development are also pointed out. Ethical decisions have to be made during product development as shown in this chapter. Outsourcing is a real option due to the availability of many contract research and manufacturing organizations, and judicious use of this option is discussed in this chapter. Key milestones that reduce risk and show transition from early stage to preclinical prototype stages are reviewed here. Does the popular concept of minimum viable product in software development apply in biomedicine prototyping? Other similar questions that help the reader understand pitfalls and best practices are answered here.

In this chapter, we introduce the simplex algorithm for solving linear programming problems. We confine the chapter to Phase II pivoting, which is valid for any standard form maximization problem. We handle standard form minimization problems by using duality, since the dual problem of a standard form minimization problem is a standard form maximization problem. Since all linear programming problems that arise in game theory are standard form, the material of this chapter is sufficent to study game theory. Phase I pivoting, which is used for problems with mixed constraints, and integer programming are deferred until a later chapter, after we explore game theory. We end the chapter with a section on using software packages such as Microsoft Excel and Wolfram Mathematica to solve linear programming problems.