The number of new drugs approved per dollar spent or pharmaceutical research and development productivity has significantly declined in recent decades [1
]. By conservative estimates, it now takes ~15 years [2
] and $800 million to $1 billion to bring a single drug to market [3
]. There are two major reasons for this decline in the total number of safe and effective new drugs reaching the market. The first is that prevalent drug development strategies within pharmaceutical companies remain conservative, typically oriented on discovery of a new therapeutic target combined with a search for a novel therapeutic compound that modulates the activity of the identified target. This is followed by a slow, costly and risky process of experimental and clinical validation.
The second major reason for reduced productivity is the lack of systematic evaluation of additional indications that each drug can target, both during the drug’s development phase and subsequent to its arrival on the market. Some of the most profitable and successful pharmaceuticals did not begin development for their current indications, but instead were re-purposed or repositioned for new uses [4
]. Accidental discovery, unintended side effects or obvious follow on indications have led to new uses of such drugs. Classic examples include Minoxidil (originally tested for hypertension; now indicated for hair loss), Viagra (originally tested for angina; now indicated for erectile dysfunction and pulmonary hypertension), Avastin (originally indicated for metastatic colon cancer and nonsmall-cell lung cancer; later approved for metastatic breast cancer) and Rituxan (originally indicated for non-Hodgkin’s Lymphoma; later approved for chronic lymphocytic leukemia and rheumatoid arthritis).
Revenues generated by repositioned drugs can exceed billions: sales of thalidomide, repositioned for multiple myeloma, reached US $271 million in 2003 alone [5
]; sildenafil, repositioned for erectile dysfunction, had annual sales of US $1.88 billion in 2003 [4
]. While the revenues generated by repositioned drugs have been substantial, the real incentive for repositioning is the clear benefit for patients. For example, thalidomide’s antiangiogenic properties have provided therapeutic benefits to multiple myeloma patients, who otherwise had few treatment options for their disease, while the central dopamine agonist properties of bromocriptine recent led to its approval in the USA for a new indication of Type 2 diabetes [6
Drug repositioning or repurposing (i.e. finding a new use for an existing drug) can provide solutions to the problems facing pharmaceutical companies. Such efforts have spanned the spectrum from traditionally blind screening methods of chemical libraries against specific cell lines [7
] or cellular organisms [8
], to serial testing of animal models [10
], to the newer data-driven approaches involving computational methods. The latter category typically takes advantage of the fact that a single molecule can act on multiple targets and could be beneficial to indications where the additional targets are relevant (the known compound-new target approach). In fact, there is strong evidence that such off-target interactions, or polypharmacology, are common among many approved drugs compounds [11
]. Additionally, repositioning efforts also leverage the fact that mechanisms and targets are shared between diseases or biological processes enabling drugs that work on a target in one work for the other (known targets in a new indication). Drug repositioning has several advantages compared to a traditional approach to the development of a drug de novo
The drug development cycle for a repositioned drug can be as short as 3–12 years compared to the traditional 10–17 years required to bring a new chemical entity to market [12
]. This is due to the fact that several steps of the drug development pipeline can be eliminated during repurposing efforts. However, the discovery of a new use of a drug for a new condition can be a haphazard process, as illustrated by the examples given above, where new indications were found through side effects, or through exploiting useful properties of these drugs [13
], demonstrated in the utility of arsenic for acute promyelocytic leukemia [14
], amphotericin B for leishmaniasis [15
] and thalidomide for multiple myeloma [16
]. While physicians, pharmaceutical and biotechnology companies have manual methods and prior knowledge that enable repositioning of drugs through clinical trials, these occurrences are often serendipitous and rare. One challenge in drug repositioning, therefore, lies in predicting and choosing new therapeutic indications to prospectively test for a drug of interest. This review will focus on computational approaches for guiding and selecting new indications for drugs.