Drug development failure rate

These plans envision composition-of-matter patents on drug molecules for which development timelines and market potentials can be estimated. Product stories are the clearest, most rational plans because profitable sales can be projected and rNPVs calculated. On the other hand, investors usually perceive higher risks because the rNPVs tend to be dominated by single product candidates for which historical failure rates are high. Examples of product stories include Amgen s development of Epogen and Amylin s development of Symlin. 

Pharmaceutical firms have to reexamine their strategies to devise means to increase their drug pipelines for continuous streams of products. The high failure rates of Investigational New Drugs during clinical trials (see Exhibit 5.8) necessitate the development of better assay systems and animal models that correlate closely with human pharmacodynamics and pharmacokinetics. The study of pharmacogenomics will be crucial to address this issue. 

As things stand today, there are no shortcuts in drug development, regarding neither the overall development time—typically 12-15 years—nor the early identification of dropouts. The pharmaceutical industry will continue to have to contend with failure rates and timelines to bring products to market exceeding industry standards by far. 

The cost of drug development continues to spiral upward. Inflation and increased regulatory requirements, however, only account for a small portion of this increase. At this time, productivity is a major issue. A review of 198 new drug candidates that reached phase I clinical studies indicates a 60% failure rate due to poor pharmacokinetic properties or toxicity [23]. On the average, less than 2% of the drug failures could be attributed to drug interactions that resulted in adverse reactions [24], In elderly patients, however, drug interactions could contribute... 

The number of new chemical entities (NCEs) approved by the U.S. FDA has dropped in the last decade (41) and the average success rate, from the first-in-human studies to registration, is only 11% (42). The lack of drug efficacy and safety account for around 30% of the failures in the clinic (42). Thus, the ability to determine drug safety and efficacy early in the discovery process should help in reducing the failure rate during the costly development studies, and in the end it would produce better and safer drugs (43). 

The principal issue in the drug discovery process is the high failure rate in the clinical trials, mainly due to liabilities related to poor pharmacokinetics (PK), poor efficacy, and high toxicity. The earlier lead optimization (LO) phase then represents a crucial step in the drug discovery process, since it involves the preparation and the selection of suitable drug candidates. In view of the increasing need for speed in the preclinical research and development, the determination of activity and selectivity is performed simultaneously with the evaluation of pharmacokinetic and toxicity properties. This multiparametric approach allows the early selection of the compounds with the best overall balanced druglike profile [1]. 

From these techniques, very detailed information is obtained for a few compounds per iteration. This level of detail is generally unnecessary early in the drug development process and, as the number of compounds is limited, the information gained is not widely applicable to prediction of properties of diverse compounds. The information is useful when, for example, considering how a specihc disease state would affect the pharmacokinetics of a compound. PBPK models use information relating to the functioning of the tissues and the rate at which blood presents compounds to that tissue. For example, predictions could be made as to how the pharmacokinetics of a compound would be affected when administered to a patient suffering from renal or hepatic failure etc. 

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