How Big Data Is Used in Biotech

A group of technicians running tests in a laboratory.The roots of modern biotechnology date back to 8,000 B.C., when humans learned to cultivate crops and domesticate animals, enabling the advancement of civilization. Emerging discoveries in the areas of cells and genetics in the 17th century further advanced the discipline.

Today, biotechnology is at the vanguard of modern science. It can be utilized to leverage advancements in the pure biological sciences, such as molecular biology, genetics and embryology, to solve the problems facing humanity, making it a key component in the search for solutions to 21st-century challenges such as hunger, the need for alternative energy sources and disease.

Biotechnology is also at the forefront of the big data movement that’s permeating the healthcare industry, as technological innovation makes it increasingly possible to glean information from an eclectic range of sources. When used properly, big data can be a vital tool to help maximize the impact biotech advances can have on society at many levels, from the global community at large to a select local community and its residents.

A Healthcare Master of Business Administration degree can provide graduates with the skills and knowledge to optimize big data in biotech to bring about advancements in the healthcare field.

How Big Data Improves Biotech and Healthcare

Perhaps no other field has benefited more from advances in biotech than healthcare; oncology, neurology, immunology, infectious diseases and regenerative medicines are among the main drivers of biotech research and development. Current biotech developments such as the CRISPR-Cas9 system for gene editing and long-term biotech-related endeavors like the Precision Medicine Initiative demonstrate how biotech’s innovative processes can lead to game-changing breakthroughs in how various health conditions can be treated.

The amount of gathered data can correspond to the potential of these biotech innovations. A vast amount of data can make it easier to find and analyze variables that may not be present within a small data set. This could lead to the development of systems or processes that encompass a wider range of probabilities, which could result in more successful outcomes.

This could carry positive ramifications in various aspects of healthcare and health in general. Gathering a wider swath of data can lead to the creation of genomics projects that are more commercially accessible and cost-effective. Big data could also help pharmaceutical companies develop drugs at a lower cost and with a higher success rate through tools like predictive analytics. Ultimately, big data can play a key role in the development of healthcare innovations that could improve patients’ health and wellness.

The Future of Big Data in Biotech

The increased presence of big data in biotech means its impact will continue to grow. As it stands now, it’s already making impressive strides. For instance, the Human Genome Project continues to push the boundaries of biotech research and development, leading to huge advancements in cancer research. It is now possible to gene-sequence a tumor and identify the best treatment course; the era of “personalized” cancer drugs is on the horizon.

The other biotech advances being fueled by big data can have an equally impactful effect. Integrated big data tools like electronic health records (EHR) can make it easy for healthcare professionals to obtain a comprehensive patient health record, even if information regarding their health originated from scattered sources.

Other advances in genetic research backed by big data could lead to dramatic progress in the fight against single-gene disorders, such as sickle cell disease, cystic fibrosis and hemophilia. This type of research can also be used to develop improved treatments and prevention strategies for complex conditions like mental illness and heart disease.

Big Data Can Lead to Better Decisions in Healthcare

Businesses and healthcare facilities that collect large amounts of data can use it to personalize their approaches to patients and customers. As more facilities strive to implement value-based healthcare models, for example, big data can play a part in achieving the model’s goals of improved patient satisfaction and reduced costs.

Big data can afford healthcare professionals the opportunities to closely monitor the effectiveness of their care strategies including drug usage. Big data concepts like predictive analytics can be used to predict the outcomes of medical interventions.

Ultimately, using big data in biotech can help healthcare facilities provide smarter care strategies while minimizing wastefulness and inefficient processes. This could create an effective path to improving patient outcomes.

Examining Big Data and Decision-Making in Action

Many healthcare facilities already use big data to make critical decisions. According to information gathered by Datapine, 94% of hospitals in the U.S. use EHRs. Many healthcare facilities are also turning to predictive analytics to determine the effectiveness of opioid treatment programs, a tactic that can help facilities combat the ongoing opioid epidemic. During the COVID-19 pandemic, big data played a key role in tracking the virus’s spread and impact, using tools such as predictive analytics and contact tracing.

Although big data can provide the building blocks for advancing healthcare concepts through biotech and other tech-driven care delivery strategies, highly skilled individuals are required to analyze and interpret the large swaths of data. George Washington University’s online Healthcare Master of Business Administration program can help you gain the knowledge and skills needed to navigate this dynamic tech-driven process in a healthcare setting.

Discover more about how a Healthcare MBA can help you advance toward professional success today.

Recommended Readings

Digital Health Transformation — Building Core Competencies

Opportunities for Entrepreneurs in Healthcare

What Is Preventive Healthcare?


Academic Medicine, “Defining and Implementing Value-Based Health Care: A Strategic Framework”

Biotechnology Journal, “Biotechnology, Big Data and Artificial Intelligence”

Centers for Disease Control and Prevention, Viral Hepatitis

Datapine, “18 Examples of Big Data Analytics in Healthcare That Can Save People”

Forbes, “How Big Data Empowers Organizations to Work Smarter, Not Harder”, What Is an Electronic Health Record (EHR)?

HealthTech, “How Predictive Modeling in Healthcare Boosts Patient Care”

International Journal of Environmental Research and Public Health, “Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models Towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing”

MedlinePlus, What Are Genome Editing and CRISPR-Cas9?

MedlinePlus, What Is the Precision Medicine Initiative?

National Human Genome Research Institute, The Human Genome Research Project

Nature Reviews Genetics, “The Human Genome Project Changed Everything”

Oracle, Oracle DataFox Data Management

Proceedings: IEEE International Conference on Big Data, “Empowering Personalized Medicine with Big Data and Semantic Web Technology: Promises, Challenges, and Use Cases”

Studies in Health Technology and Informatics, “Using Big Data to Predict Outcomes of Opioid Treatment Programs”