The precision medicine model is shifting the paradigm in healthcare delivery and changing the way research and development is conducted. Currently, 20 percent of pharmaceutical research and development is gene-based, and the number of personalised medicines available has increased by 62 percent since 2012. Furthermore, greater than 70 percent of cancer drugs currently in development are precision medicines.
Despite its benefits, the approach has been coupled with overwhelming cost challenges for payers, patients and physicians. Here we discuss these cost challenges and the strategies that can be employed to overcome them, drawing on research from our recently published white paper, ‘Looking Ahead: The Future of Device Developers in Precision Medicine’.
Cost challenges
Currently, R&D of precision medicines are more expensive than traditional medicines because they require companion diagnostics and genetic testing. Companion diagnostics often require testing on biomarkers and marker-negative patients, resulting in a need for larger patient pools and elevated costs.
Additionally, the need to generate evidence for precision medicine calls for collection of real-world data and non-clinical data. Unfortunately, current medical privacy and research rules have not evolved to allow collection of vast amounts of data on large patient populations and private healthcare systems do not have the infrastructure to perform data collection on a mass scale: the costs are elevated further. In the end, patients suffer because they bear a larger share of medical expenses in the form of increased out-of-pocket charges.
As a result, there is less integration of precision medicine. Only 40 percent of patients are aware of precision medicine, and a mere 11 percent of patients reported that their doctor discussed precision medicine with them as a treatment option.
However, the relative effectiveness of precision drugs versus traditional approaches have the potential to reduce costs in the long term.
Mitigating costs
While there are concerns regarding the cost of precision medicine, strategic approaches can be employed to reduce costs.
Traditional therapies for genetically-linked conditions are effective in less than 60 percent of patients. Additionally, patients without a genetic diagnosis have 38 percent adherence to their treatment programme after two years compared to 86 percent for those who do. This lack of effectiveness, in addition to shorter treatment plans, result in billions of wasted dollars long term.
Conversely, according to the National Academy of Medicine, a precision medicine treatment that can accurately identify at-risk patients could generate hundreds of billions of dollars in value in the form of longer, healthier lives enjoyed by patients.
Because the upfront cost of precision medicine can be offset by the long-term benefits to patients, the solution is two-fold: implementation of technologies which will enhance treatment efficacy, and the optimisation of value-based payment models.
1. Companion diagnostic devices
In precision medicine, pharmaceutical companies create targeted therapeutics, and device manufacturers design companion diagnostic devices to be paired with a specific drug.
These companion diagnostic devices are then used to best determine the selection and dosage of a drug tailored to a patient, which can lower costs of the treatment as a whole. As an example, next-generation sequencing as a companion diagnostic technology enables the distinction of potentially significant mutations and biomarkers from those that are less likely to be important at an early stage of disease development. This companion diagnostic test can identify which patients will best benefit from the treatment, leading to the development of better tailored treatments.
Companion diagnostics can enhance treatment efficacy, and thus reduce long-term expenses by allowing patients to be treated correctly on the first try.
2. mHealth and wearable devices
Harnessing technological advancements have resulted in increased emergence of innovative wearable and sensor devices. Novel technologies allow for richer data collection in clinical trials to better understand treatment effects and health status, improving treatment efficacy. Furthermore, mHealth technologies enable more frequent measurement of outcomes without significantly adding cost.
Increased capability and implementation of mHealth devices in clinical trials help to ensure that studies have the best possible chance of success, facilitating accurate go/no-go decision-making. By identifying what treatments work for which populations, mHealth devices (and the data they produce) can identify opportunities for cost reduction.
3. Value-based payment models
Value-based healthcare (VBHC) financial models can be employed to account for the high initial costs of testing and treatment. VBHC is a healthcare delivery model where payments are linked to the clinical and cost outcomes of treating a defined patient need, condition or episode of care.
With more data to guide payers, providers and patients towards lower-cost and more effective treatment plans, value-based care contracts for personalised medicine will likely become a more widely adopted approach for controlling costs and fostering better patient outcomes.
It is critical that manufacturers and pharma companies seek guidance to properly navigate growing value-based environments to reduce costs and get ahead of competition.
As evidence of their effectiveness grows, precision medicine tests, technologies and therapeutics are increasingly being adopted into clinical practice in place of the traditional “one-size-fits-all” model.
Precision medicine has immense impact for patient outcomes, but must be navigated strategically to overcome cost challenges and harness the full range of benefits.
Vicki Anastasi is vice president and global head, medical device and diagnostics research, at ICON
