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The research and development costs of 93 randomly selected new chemical entities (NCEs) were obtained from a survey of 12 U.S.-owned pharmaceutical firms. These data were used to estimate the pre-tax average cost of new drug development. The costs of abandoned NCEs were linked to the-costs of NC& that obtained marketing approval. For base case parameter values, the estimated out-of-pocket cost per approved NCE is $114 million (1987 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a 9% discount rate yielded an average cost estimate of S231 million (1987 dollars).

We compared the sensitivity of different types of visual analog scales and of descriptive pain terms in healthy volunteers and in postoperative patients. One hundred and seven volunteers marked visual analog scales according to their perception of the descriptive pain terms--little, mild, some, moderate, severe, agonizing. Individual variation in values and preferences between the five following five different visual analog scales were analyzed: 10-cm linear horizontal and vertical scales, a curvilinear scale, and graded horizontal and curvilinear scales. Significantly more volunteers preferred the horizontal scale with gradations. Scores for the vertical linear scale had the greatest coefficient of variation and were least normally distributed. The majority of volunteers considered the phrase "agonizing pain" the best term defining the extreme limit of pain (X2(12) = 41.8, P less than 0.001). There were significant changes in the values of pain intensity measured on visual analog scales by patients using the same descriptive pain term on successive observations. However, the patients' values for pain terms in the preoperative pain-free state were not significantly different from those during postoperative pain. We conclude that graded linear horizontal scales are both more reliable and preferred by participants and that visual analog scales give a more sensitive and accurate representation of pain intensity than do descriptive pain scales.

The evaluation of adverse drug reactions in clinical practice is somewhat arbitrary and is characterized by considerable differences of opinion. This report presents a decision table algorithm approach toward the development of an operational system for the identification of adverse drug reactions. The algorithm incorporates an estimate of the certainty of the link between the untoward clinical event and the suspect drug, and examines the underlying causes of the identified drug reactions. Use of such a system is a first step toward reducing ambiguity in the evaluation of adverse drug reactions.

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