Technology has been the primary enabler for modern advances in biotechnology and life sciences. The past century saw groundbreaking innovations such as insect resistant crops and treatments for life threatening disease; this century, even more radical developments are underway—brought on largely by the advent of big data and cloud computing.
In the context of biotechnology and life sciences, the cloud and big data offer benefits known as the 3 Vs: volume, velocity and variety. Traditional storage, processing, and analytical methods are increasingly ineffective for supporting today’s use cases. Additionally, drastic cost and resource savings are made possible through big data processing and cloud enablement, allowing firms to channel more time and energy into curing diseases faster and improving treatments.
The following are 7 different ways that big data and the cloud is being used by biotechnology and life sciences companies to cure diseases.
The vast amount of freely accessible human data brought forth by the Human Genome Project opened many doors for biotechnology companies in the field of genomics. Using big data and the cloud, researchers are better able to analyze and match gene variants with specific diseases as a step towards finding cures.
Advances in genomics has also led to personalized medicine or precision medicine. Personalized medicine combines knowledge of a patient’s genome with big data analytics and processing to observe the effects of a particular medicine on a specific genome.
6. Smart Treatment Through Smart Devices
Connected smart devices have accelerated the diagnosis and treatment of diseases. For example, connected health monitors store and process vital human stats in the cloud and provide a wealth of information for better individual treatment and preventative care. Diagnosis can be provided in real-time to prevent early problematic symptoms and conditions from worsening.
5. Optimal Patient Treatment and Management
By enabling the collection and sharing of millions of patients records, data points can be analyzed and correlated to identify critical trends and patterns. For example, a medicine’s effect on a specific group of patients can be quickly determined. Patient responses from varying geographical areas in regards to the effect of a specific medicine can also be analyzed; this data can in turn be utilized for future patient treatment and global health management initiatives.
4. Drug Discovery
Big data and the cloud have had a drastic effect on how firms discover new drugs or medicines, enabling researchers to pool data together to determine how specific drugs can be used to treat diseases. For example, a drug used for the treatment of one disease can have an equal or greater level of success in treating another disease. A drug that fails to treat a disease for which it was developed in one population may successfully treat the disease in another population. And a combination of drugs may alleviate or aggravate the symptoms of a particular disease. The cloud and big data have drastically transformed how scientists are discovering drugs to cure diseases.
3. Human Microbiome
The human microbiome are the collective microorganisms found in both healthy and diseased humans (i.e., microbial flora). The genetic data of the human microbiome outnumbers the human genome 100 to 1; subsequently, it plays an instrumental role in human biological systems. The cloud and big data have allowed researchers to quickly and comprehensively analyze data gleaned from the human microbiome—a first step in curing a myriad of human gastrointestinal diseases.
Proteomics is the next logical step after genomics: researchers in this field study the vast array of proteins essential to supporting healthy human life. The cloud and big data enable easier and faster protein structure predictions and modeling; this is essential for developing cures for diseases and designing drugs. Quick identification proteins involved in diseases have been made possible by rapid analysis and efficient sharing of information brought on by big data and the cloud.
Crowdsourcing is a cloud-based innovation that has brought many biotechnology companies steps closer to curing diseases. Firms are not only finding funding for their projects on platforms like Kickstarter, but they’re also using the social web to answer the most pressing health science questions of today. Hundreds of thousands of individuals from varying backgrounds can now easily converge in the cloud to assist—all at their convenience.
There’s no arguing that these 7 ways are just the tip of iceberg when it comes to using big data and cloud computing to cure diseases. Humans have already progressed in leaps and bounds within the span of a few decades; the ongoing use of big data and cloud computing will no doubt accelerate advances in biotechnology and life sciences.