For centuries, medical professionals have experimented with different techniques to cure various illnesses; observing, sharing, and improving upon health outcomes. Most of these medical treatments have used the one-size-fits-all approach and they have largely been reactive in nature, with patients having to wait for the onset of symptoms before being treated or cured. Lately, scientists and physicians are working hard to provide proactive, precise, and personalized medicine with the help of electronic health records, population health, genetic testing, big data analytics, and supercomputing.
Precision medicine, also addressed by the term, "personalized medicine" is an emerging science in which disease prevention and treatment methods are tailored to an individual’s health requirement, after careful consideration of their genetic makeup, environment, and way of life. It is all about providing preventative and precise treatment to individuals before it is too late. So far, this targeted medicine has enabled the medical community to tackle diseases that were far beyond the scope of treatment only a few years ago, such as Cancer, neurodegenerative diseases, and other rare genetic conditions. Using precision medicine, medical professionals are able to collect specific information about a person’s tumor which will help them make the right diagnosis, come up with an accurate plan of action, keep tabs on the effectiveness of the treatment, and so on.
The United States Centers for Disease Control and Prevention (CDC), in one of its statistics stated that cancer was the 2nd leading cause of death in the year 2019 and 2020, recording 146.2 and 144.1 deaths per 100,000 U.S. standard population respectively (see Figure 1). On the other hand, studies show that cancer results in losses of nearly USD 75 billion every year. Neurological diseases such as Alzheimer’s disease, produce similar consequences. Alzheimer’s is one of the 10 main causes of death in the United States, and the Alzheimer’s Association estimates that there will be about 15.5 million people living with this condition by 2050, impacting the economy with trillion dollars of losses.
Currently, the diagnosis of these diseases relies on clinical symptoms and standard biomarkers, and the tests conducted are often limited in nature, inaccurate, and done late during the progression of the disease. Precision medicine uses advanced technologies such as Artificial Intelligence, machine learning, genetic testing, molecular diagnostics and imaging, next-generation sequencing, and others to effectively diagnose diseases and tailor treatments accordingly.
In 2015, former American President Barack Obama launched the Precision Medicine Initiative (PMI) during the State of the Union address. It was introduced to spur research and development in the field of precision medicine across the public and private sectors. It was also a call to patients and their families to get actively involved in the initiative by sharing data and participating in clinical trials.
Genetic testing is a quick, effective, and affordable method that allows researchers to collect large volumes of genomic data from a diverse patient pool. By studying genomic data from different populations, researchers and scientists can better understand how genetic variations contribute to various diseases. Having family members with certain chronic conditions such as diabetes, heart disease, or cancer, can mean that there is more likelihood of getting that disease. A combination of genomic data along with historical, socioeconomic, and clinical information is then subjected to analytics, where patterns are observed to judge the effectiveness of particular treatments. Clinical trials can then be undertaken to test and validate these theories and help support future best practices. With the help of pharmacogenomics, a person’s genetics can be studied to choose the right medication and dosage to treat a disease. It also helps avoid medications that may cause harmful side effects. Moreover, growing emphasis on genomics for cancer care also provides greater scope for the development of precision drugs. Next Generation Sequencing (NGS) Tests are used to sequence large sections of an individual’s genome to identify genetic variants that hold the key to various diseases.
The large amount of data generated by this technique raises FDA regulatory concerns. Currently, the FDA focuses on conventional diagnostics that detect a single disease or condition, but NGS tests are like conducting millions of tests in one go. Hence, the FDA is collaborating with the healthcare sector, laboratories, academia, and patients to develop a flexible regulatory approach to make precision medicine technology mainstream (see Figure 2).
CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is part of an organism’s bacterial defense system, helping cells identify and destroy foreign objects. The gene editing technology of CRISPR-Cas9 allows researchers to target specific fragments of genetic code and alter the DNA within them to correct mutations and disease susceptibilities. Remote Monitoring and Wearable Technology are being widely used since the pandemic. Biosensors, CGMs (Continuous Glucose Monitoring), oximeters, and wearable technology such as smart watches can help monitor a person’s health on a regular basis. Data from these devices can be sent to the cloud for real-time analysis and gain insight into patients’ conditions to design accurate bespoke treatments.
Predictive Analytics uses machine learning algorithms and data mining to study historical data and predict reliable future outcomes. This data is collected from various sources such as electronic health records (EHRs), remote patient monitoring devices, and wearable devices. Technology can streamline this data transfer, thereby improving the operations of hospitals and clinics globally. AI can help reduce physician burnout by making their work easy. It can foster trust between patients and providers, and make healthcare affordable. AstraZeneca is partnering with Benevolent AI to create knowledge graphs that can quickly analyze large volumes of data to glean important information on the interaction between genes and diseases. Social media can help public health workers track disease outbreaks and communicate important health information to a large population base. Newborn screenings which include blood tests and hearing loss and heart disease screening in babies can help identify medical conditions early on to prevent complications later in life.
Scientists are trying to harness the potential of precision medicine using novel technologies. They are digging deep into the world of chronic diseases to extract new diagnostics and therapies that can help detect these diseases and intervene early, halt their progression, prevent their return, and enable patients to live healthier lives around the world.
Integrating precision medicine into healthcare is going to be complicated and laborious. For starters, healthcare centers need to be equipped with superior technology that will help them make sense of the enormous amount of data that comes in. Artificial Intelligence can come in handy here, but this technology poses its own set of challenges.
Precision medicine has opened a world of opportunities that can shape the future of healthcare. While it is currently mostly deployed in the treatment of cancer, precision medicine is being explored to treat a whole gamut of diseases from rare and genetic disorders to COVID-19. However, for precision medicine to truly add value to patients and broaden the scope of healthcare, the industry must overcome the challenges and limitations associated with infrastructure, inequities, and information gaps. The future of precision medicine depends upon how we leverage technology to push the boundaries of personalized treatment and transform the way we treat diseases. Here is a glimpse of the markets associated with precision medicine (see Figure 3).