Precision medicine is an approach that considers a person’s genetics, lifestyle, treatment history, etc. to identify the best possible treatment options. The short term vision of precision medicine is to tap into oncology, understand genetic markers and find the most effective treatment option. The long term vision is to improve therapeutic tools in all the fields of medicine.
Big data on healthcare has a vast amount of data generated from patient health records, diagnosis, treatments history, medical research, smart wearable devices and many other reliable sources. These data are huge in volume and highly variable as it is from multiple data sources. As healthcare data grows big, data analytics and data science have emerged as a promising sector in healthcare. These data have the potential to transform the healthcare industry to do better-informed decision making in the coming days.
Key Steps in Precision Medicine
There are multiple factors which affect a patient’s health, and these factors can change through the course of treatment. A single diagnosis will limit the doctor’s ability to make a decision and take proper after treatment services precisely.
Key Steps in Precision Medicine Ecosystem
There are multiple factors which affect the patient’s health. And, these factors change through the course of treatment. Making just a single or static diagnosis can limit doctors’ ability to identify and make treatment precisely. Longitudinal patient health records help in tracking the real-time data of individual patients. These data are captured from clinical notes, lab records, scans, cells, tissues, blood, organs, fluids, environment, population, geography, demography, inherited factors, acquired factors, etc. When you successfully integrate all these multiple data, you get Precision medicine.
Data algorithms, computational methods, analytics etc. are applied to extract useful clinical information from these multiple data sets. Machine Learning, Artificial Intelligence, Deep Learning, Data Mining etc. are also used in the process. Latest and modern technologies used to structure clinical data, identify a pattern in patients, identify mutations in large sets, automate workflows, segregate data, and finally help doctors make informed decisions in real-time.
This health data also requires secure servers to store the data. Technologies like Blockchain can help in sharing and storing these data across platforms.
All the stakeholders in precision medicine can utilize these data effectively, like – healthcare providers can improve their treatments, patients can get educated, patients can collaborate with other healthcare providers, researchers can improve study, improve data platforms, decision-makers can maximize the health benefits and improve healthcare across masses.
Challenges with Utilization of EHRs and Genomic Data in India
EHRs are currently scattered and stored in multiple data sources. All the stakeholders use different semantics, terminologies, coding and classification systems to fetch data from EHRs. But analyzing and integrating these data from multiple systems is challenging. It can end up being incomplete, inaccurate or even inconsistent.
In India, due to limited research and development, the amount of genomic data collected is insufficient. India has around 18% of the world’s population but only has less than 1% of genetic data. Most research on drugs and treatments are on the Caucasian population, and the studies on the Indian population are very limited. Several startups in India are exploring this area and creating applications which can build up data in the Indian population.
Government organizations are working on creating proper guidelines to ensure that the data is reliable, efficient and secured. Ministry of health and family welfare is planning to digitize medical records in India. There is the latest publication on the National Digital Health Blueprint Report which invites feedback from various stakeholders to streamline the usage of digital technologies in health. They also released EHR standards in 2016 which introduced a uniform system to maintain EHR in India.
By the end of this year, India is also set to launch its first human genome mapping project. The department of biotechnology of India initiated this project. It plans to capture and analyse data of 10000 Indians.
Asia-Pacific Market for Precision Medicine
Asia Pacific region is one of the fastest-growing markets in precision medicine. The ageing population and chronic diseases have increased the burden on the healthcare market in the APAC region. Countries like China and Japan are also investing heavily in genomics and healthcare technologies. The rise of disposable income and economic growth will boost this market in the coming days.
According to MarketWatch, precision medicine market in the APAC region will reach $21 billion by 2023 with the annual compound growth rate of 16.6%. This market has three segments,
- Ecosystem: pharmaceutical and biotechnology companies, clinical labs and diagnostic companies.
- Therapeutics: oncology, cardiovascular, psychiatric disorder, central nervous system, and infectious diseases.
- Technology: big data analytics, bioinformatics, gene sequencing, pharmacogenomics, and companion diagnostics.
To diagnose better and treat the disease, it is important to understand the relationship between individual components in the larger system. The interrelations are often overlooked when these components are individually analysed. The objective of the process is to leverage technology to enable learning from each patient and generate more data for better-informed decisions.
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