title: The impact of assay technology as applied to safety assessment in reducing compound attrition in drug discovery.
abstract: BACKGROUND
  Attrition in the drug industry due to safety findings remains high and requires a shift in the current safety testing paradigm. Many companies are now positioning safety assessment at each stage of the drug development process, including discovery, where an early perspective on potential safety issues is sought, often at chemical scaffold level, using a variety of emerging technologies. Given the lengthy development time frames of drugs in the pharmaceutical industry, the authors believe that the impact of new technologies on attrition is best measured as a function of the quality and timeliness of candidate compounds entering development.
  
  
  METHODS
  The authors provide an overview of in silico and in vitro models, as well as more complex approaches such as 'omics,' and where they are best positioned within the drug discovery process.
  
  
  CONCLUSIONS
  It is important to take away that not all technologies should be applied to all projects. Technologies vary widely in their validation state, throughput and cost. A thoughtful combination of validated and emerging technologies is crucial in identifying the most promising candidates to move to proof-of-concept testing in humans. In spite of the challenges inherent in applying new technologies to drug discovery, the successes and recognition that we cannot continue to rely on safety assessment practices used for decades have led to rather dramatic strategy shifts and fostered partnerships across government agencies and industry. We are optimistic that these efforts will ultimately benefit patients by delivering effective and safe medications in a timely fashion.
authors.affiliation: Lilly Research Labs, A Division of Eli Lilly and Co., Lilly Corporate Center, Indianapolis, IN 46285, USA.
authors.forename: Craig E
authors.initials: CE
authors.lastname: Thomas
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Will
mesh_terms: D000818:Animals; D017076:Computer-Aided Design; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods; D004345:Drug Industry / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000737:chemistry; D055818:Public-Private Sector Partnerships; D013678:Technology, Pharmaceutical / Q000379:methods; D013997:Time Factors
chemical_list: D004364:Pharmaceutical Preparations