Despite the growing interest in biodiversity as a source of valuable new products and biochemical information, there have been very few systematic efforts to estimate the value of preserving biological resources for this purpose. Drugs of Natural Origin gives you a detailed model of the value of wild biological resources for pharmaceutical research and development. Author Anthony Artuso presents several decision models and analytical techniques that you can use to assess the economics of biochemical prospecting efforts whether you’re part of a private corporation, nonprofit research institute, developing country government, or international organization.

Drugs of Natural Origin explores the policy options available to developing countries and international organizations to tap into the emerging market for biological resources in such a way as to provide both incentives for conservation of biodiversity and new opportunities for economic development. You’ll find evaluations of a range of proactive strategies that can be used to protect and enhance developing countries’biological resources. In addition, you’ll learn about a bioeconomic model that incorporates the potential biochemical and genetic value of a diverse ecosystem into land use planning and development.

Developing country and international policymakers will find Drugs of Natural Origin a useful tool for determining how best to conserve biodiversity, while sustainably developing biological resources. This book outlines a comprehensive and integrated set of policy measures, research and development initiatives, and financing arrangements that could increase biochemical research activity while providing incentives for conservation of biodiversity and a potential path for sustainable development.

Managers of pharmaceutical R&D programs will use the decision models developed in Drugs of Natural Origin to plan, evaluate, and continually refine their R&D programs. The book’s theoretic framework provides you with an analytical tool for systematically evaluating critical decisions at each stage of the R&D process. Thus, you learn to incorporate both subjective assessments and quantitative data into a comprehensive framework for R&D decisionmaking.