In this newsletter, four recent papers on drug repositioning are discussed. They collectively represent the areas of focus and the methodologies applied in drug repositioning.
One of the active areas in drug repositioning is the identification of medications for rare and neglected diseases. Since the market value to treat these diseases is not consistent with the bottom line emphasized by most pharmaceutical companies, government agencies and academic institutes have taken the lead in this area. Muthyala  believes that “a substantial percentage of rare diseases if not all 8000 rare diseases might be treatable with drugs in the current pharmacopeia.” He embraces the importance of the differing influence from public and private partnerships, government incentives, patient support groups, and the pharmaceutical industry on efforts to move drug repositioning forward.
Ekins et al.  reviews the data sources and strategies available for in silico drug repositioning for rare and neglected diseases. The authors suggest that combining current in silico technologies with chemical information, biological activities data, and in vitro screening data could improve and enhance repositioning efforts specifically for rare and neglected diseases. They introduce and recommend the Collaborative Drug Discovery (CDD) database which is particularly useful for neglected diseases.
In addition, Blatt et al.  describe a case study of pediatric hematological oncology regarding drug repositioning for orphan drugs. Based on scientific literature, they found that approximately 10% of drugs with primary uses in pediatrics have been repositioned in pediatric hematological oncology or other pediatrics uses. They suggest that there are more undiscovered repurposing opportunities that may be found by integrating the knowledge from observant clinicians, pharmacologists and researchers, as well as by the application of in silico techniques such as structural targeting.
There is a broad application of drug repositioning beyond rare and neglected diseases. For example, the study of marketed drugs might also lead to new medications to replace some unsafe or specialty drugs that pose a tremendous burden to the patients in terms of quality of life and financial acceptance. This requires a better strategy to translate innovative technologies and scientific discoveries to repositioning opportunities. The article by Liu et al. titled "In Silico Drug Repositioning – What We Need to Know”  summarizes existing resources and methodologies for drug repurposing. Most importantly, they propose three essential steps to guide any repurposing study – repurposing with a purpose, repurposing with a strategy, and repurposing with confidence. This article provides researchers with a conceptual pipeline for repositioning with a particular focus on the Drugs of New Indication database, which contains information from successful repositioned drugs to improve the accuracy of in silico based drug repositioning.
Drug repurposing is at a key transitional point. The development of new resources, strategies, and techniques will expand the number of successful repositioning opportunities identified, which in turn will benefit patients by offering more effective and safer treatments.
Disclaimer: The views presented in this article do not necessarily reflect current or future opinion or policy of the US Food and Drug Administration. Any mention of commercial products is for clarification and not intended as an endorsement.
Weida Tong is Director of Division of Bioinformatics and Biostatistics at FDA’s National Center for Toxicological Research (NCTR/FDA). He received his Ph.D. in Polymer Chemistry from Fudan University (Shanghai, China) in 1989 and he joined NCTR/FDA in 1996 after finishing his postdoctoral fellowship in Computational Chemistry at University of Missouri-St. Louis. He also holds several adjunct positions at various universities. His division at FDA is to develop bioinformatic methodologies and standards to support FDA research and regulation and to advance regulatory science and personalized medicine. His most visible projects consist of (1) development of the FDA bioinformatics system, ArrayTrackTM suite, to support FDA review and research on pharmacogenomics; (2) leading the effort on the Microarray Quality Control (MAQC) consortium to develop standards for translational science and personalized medicine; (3) development of liver toxicity knowledge base (LTKB) for drug safety; and (4) drug repositioning with bioinformatics. In addition, his group also specializes in molecular modeling and QSARs with specific interest in estrogen, androgen, and endocrine disruptor.
 Muthyala, R. (2011) Orphan/rare drug discovery through drug repositioning. Drug Discov Today 8, 71–76
 Liu, Z. (2013) In Silico Drug Repositioning – What We Need to Know. Drug Discov. Today