Assessing the Landscape for Personalized Medicine
SummaryIn complex therapeutic areas such as oncology, thought leaders have long sought improvements to lengthy trials, hit-or-miss treatments and soaring research costs.
In complex therapeutic areas such as oncology, thought leaders have long sought improvements to lengthy trials, hit-or-miss treatments and soaring research costs. While there is still much to be resolved, the rise of personalized medicine has set its sights on these and other obstacles in the pursuit of more targeted and efficient therapies.
The one-size-fits-all approach that has dominated clinical drug development has been the most appropriate route when costs are considered, but this strategy has failed to meet the needs of the patient. Guesswork has dominated drug development for far too long, leading to a push to make drugs mechanistic through molecular target validation, biomarker identification and other techniques.
Researchers are only now beginning to make headway into the importance of gene variation, which highlights the importance of close analysis of individual patients in the pursuit of the right type of patient-oriented therapy needed. Scientists are also making important breakthroughs in the understanding of variables such as genetic changes and drug sensitivity, which have dramatic implications for determining how effective specific medications might be for unique individuals. The promise of smaller, faster studies that could allow for the testing of a much higher volume of treatments is becoming more and more difficult to ignore.
However, a host of obstacles have stood in the way of a more personalized approach:
- What is the price of progress toward personalized medicine?
- How can these targeted therapies be made more affordable, scalable and feasible?
- How can the costs of individual patient screening be reduced?
- What can be done to merge tests in an effort to test for multiple molecular abnormalities at once, which can drive personalized therapies?
- What is the best way to target the right patient base in an effort to identify those who are most likely to have a favorable response to specific therapies?
The questions listed above are not the only challenges that threaten a more widespread adoption of personalized medicine. A move toward personalized therapies will necessitate an overhaul of the way research is considered and executed, including the conduct of clinical studies. Study administrators will have to acknowledge and work around long timeframes for reaching trial endpoints.
Overcoming the entrenched risk aversion that is part of the culture of regulatory and statistical mindsets is also necessary. In an industry that is leery of any element of risk, it will be a challenge to accept and embrace the risk that is inherent within personalized medicine.
Adoption of New Technology, Better Collaboration is Needed
In the face of many obstacles, there is still optimism surrounding the path forward for personalized medicine. Some researchers feel nanotechnology could offer access to data that can help narrow the focus of personalized treatments, and others hold high hopes for sequencing and translational bioinformatics.
Of course, in order to capitalize on the possibilities of personalized medicine, strides must be made in key areas. Advocates are calling for the FDA to deliver more clarity surrounding personalized therapies, while others feel that collaboration among a host of healthcare disciplines is needed in order to reach the customization and individualization that could mark successful personalized treatments.
While the road ahead may be rocky and the task may seem daunting, industry observers not only recognize the immense promise of personalized medicine, but feel that it is a necessary evolution in clinical research and drug development.
“Despite its unfulfilled promises,” wrote Paul Thomas of Pharma QbD, “personalized medicine still provides the greatest hope for change and for Big Pharma to rediscover success.”
And it is that hope that drives those who seek to overcome all obstacles in the pursuit of the latent potential of personalized medicine.
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