A recent review, published in the Journal of Pharmacy and Pharmacology, provides an overview of drug repositioning and the new tools that aim to make this process more efficient.
Drug repositioning
Drug repositioning (also referred to as drug repurposing) is the use of a drug in an indication that differs to the one for which it was initially marketed. The definition now includes active substances that fail clinical phase and those withdrawn from market. However, it excludes any structural modification of a drug.
It is a growing trend, helping to overcome the attrition currently experienced in the field of new drug discovery. Previous examples of repositioning drugs happened purely through serendipity. Now, experts have developed new methods, based largely on data mining to identify new candidates for drug repositioning.
Drug repositioning relies on two main scientific bases. Firstly, the discovery that some diseases share common biological targets. Secondly, the concept of pleiotropic drugs.
Our ability to describe diseases based on their molecular profile and to use computational methods to determine the degree of similarity between diseases has been critical. The existence of common protein targets in several diseases means that a given drug may be effective against different conditions. In addition, scientists now characterise most drugs phenotypically, in terms of their therapeutic effects and side effects. These effects are the result of pleiotropic interactions between the drug and several biological targets.
As a result, a drug has the ability to have efficacy against a disease other than the one it was initially for. Like diseases, researchers can evaluate drugs for phenotypic similarity, irrespective of their therapeutic indication. If two drugs have a high similarity score, they may be effective in both indications.
Advantages and Challenges
Repurposing a drug simplifies regulatory procedures as regulators take into account previously acquired data. This makes the initial phases of drug development faster and cheaper. However, the adverse effects of a drug will be proportionately less acceptable when repositioned for a disease that is less serious or severe than its original indication. Any changes in formulation, dosage or route of administration will require re-examination.
The main challenge is found in the relatively weak intellectual property protection given to such medicinal products. As the drug is patented as a new chemical entity, subsequent medicines that contain the same entity can only be protected by a new application patent.
Examples of repositioned drugs
In 2014, estimates indicated that repositioned drugs generated $250 billion in sales worldwide.
Aspirin
Aspirin is the oldest example of drug repositioning. Initially marketed by Bayer in 1899 as an analgesic, aspirin was subsequently repurposed in the 1980s at low doses (<300mg/day) as an antiplatelet aggregation drug. Researchers may also reposition it again in oncology. Evidence has shown that daily administration of aspirin for at least five years can prevent the development of many cancers, in particular colorectal cancer.
Thalidomide
In 1962, the World Health Organisation banned thalidomide due to its teratogenicity. It impacted thousands of people worldwide and continues to affect a second generation due to its use as an antiemetic for pregnant women. However, in 1998 Celgene repositioned this drug as an orphan drug for complications of leprosy. Its use however is accompanied with strict measures to prevent exposure to the drug during pregnancy. In 2006, FDA approved the use of thalidomide as a first-line treatment for multiple myeloma due to its antiangiogenic activity.
Sildenafil
Sildenafil is an example of a drug that was repurposed before it reached the market. In 1985, Pfizer initially investigated this substance as a potential antihypertensive drug. They found it produced vasodilation and inhibited platelet aggregation. As a result, the focus shifted onto its potential as a treatment for angina. However, during clinical trials, researchers observed an unexpected side effect in the form of penile erections. Therefore, in 1998, Pfizer marketed sildenafil as a drug for erectile dysfunction. Pfizer repurposed the drug for a second time in 2005 to treat pulmonary arterial hypertension. Interestingly, sildenafil acts on the same target to treat both these conditions, just at different doses.
Dimethyl fumarate
Dimethyl fumarate was originally known as a mould inhibitor to protect leather and also a cause of allergies. This led to a ban on its use in this capacity in Europe in 2009. Nevertheless, in 1994, Swiss company Fumapharm (now acquired by Biogen Idec) marketed it as a drug. In Germany, doctors commonly use it to treat psoriasis due to its anti-inflammatory activity. In 2013, Biogen marketed the drug again for use in multiple sclerosis patients.
Drug pipeline for Alzheimer’s disease
Attrition in the introduction of new drugs is particularly evident in Alzheimer’s disease. This is because no new drugs have been marketed for Alzheimer’s disease since 2000. As a result, researchers have undertaken many drug repositioning trials, albeit unsuccessfully to date. In 2017, over 100 drugs were undergoing clinical trials for this disease. Out of these drugs, pharmaceutical companies have already marketed one-quarter of them. Therefore, researchers are now investigating them for potential repositioning. The high proportion of existing drugs within the Alzheimer’s disease pipeline is a key illustration of a field that relies on the concept of drug repositioning.
Concluding comments
Repositioning of drugs is a growing trend to combat attrition and rising costs. The recent trials of chloroquine and hydroxychloroquine for COVID-19 have clearly demonstrated the usefulness of drug repositioning. While the first examples of repurposed drugs came largely through serendipity, methods such as data mining have helped facilitate identification of candidate drugs for repositioning. The team believe that researchers could use these technologies to establish drug-disease pairs and construct models to predict new pairs. This in turn will yield new candidates for repositioning.
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