Drug development is a complex and time taking process coated with uncertainty; whether the drug will be successful or not? In the end, it is a gamble that might pay off or all the effort might go to waste. So pharmaceutical companies like Wheeler Bio have to face many challenges and take many calculated risks during the whole process of discovery and development.
Unknown Biological Markers and Mechanisms:
Many central nervous system diseases are poorly understood. One principal challenge is the unknown biomarkers and mechanisms behind such diseases. The better understanding there is of the disease mechanisms themselves, the better interventions can be created to manage and treat the disease. When the mechanisms are poorly understood, it becomes difficult for the researchers to find out the targets where a drug should act to be useful, and hence, drug development becomes cumbersome. To overcome this problem, one way is to start at the molecular level, but it does not always prove fruitful.
Shortcomings of Animal Models:
The animal models are not always adequate to predict the efficacy and therapeutic index of a drug which creates more challenges. The inadequacy is due to the inability of animal models to mimic the diseases completely as proved by a study on mice. A mismatch between clinical and pre-clinical endpoints is also another reason for the failure of animal models. There have been incidences where the drug efficacy and toxicity has been completely different in human in clinical trials. Some of it relates to unknown mechanisms as well; if the mechanism of disease is not known, how will effective animal models be created?
Lack of Phenotyping:
Clinical phenotyping is essential for successful clinical trials. The heterogeneity of patients during clinical trials is an obvious cause of failure. For example, people with bipolar or depressive disorder are highly heterogeneous. Segregating the patients into groups based on phenotyping can help optimize the clinical trials. Patient stratification through phenotyping produces better chances of a successful clinical trial as well as more information on potential therapeutic agents.
Dubious Published Data:
Relying on published data and processing that data from one lab into another is a crucial part of the discovery research process. Success can not be reached independently and one has to rely on work done by others to reach one’s discovery. The reliability of any research depends upon the p-value. The lower the p-value the more reliable the results are. The research sometimes is not reliable due to different types of bias. So drug discovery researchers have a hard time finding the ones that are appropriate to build upon.
The Pipeline Challenges:
Several pipeline problems are making drug development difficult for pharmaceutical companies. In recent years, companies have increased their expenditure on drug development but drug approval has reduced. So before investing in a drug, the company must the following question:
- Has the drug target been identified?
- Has the target been validated?
- Are the biochemical interactions of the drug known?
- Is the dose dependence on animal models known?
- Can the drug cross the blood-brain barrier?
- Is the drug safe?
- Is the therapeutic window sufficient?