Understanding how data science can power biotechnology innovations?

Biotechnology is the use of technology applied in the development of innovative techniques for diagnosing, treating and preventing diseases. It is currently being used in the production of therapeutic proteins and drug development. Recent advances in biotechnology enabled breakthrough products and technologies to tackle diseases, lessen environmental impact, feed the hungry and have safer, cleaner and more efficient industrial manufacturing processes. The field of biotechnology significantly wrestles with big data. When it comes to human microbes, we can find astronomical amounts of data.

Biotechnologists typically apply statistical analyses to the world of molecular biology. They focus on biostatistics that is a specialty within statistics. To maximize their data usage and analytics, the biotech industry is using big data in research and development. Big data analysis makes a significant impact when it comes to the study of living systems and organisms to develop or make products.

Capitalizing on Biotechnology with Data Science

Professionals with data science skills in the biotech industry coalesce the biological sciences with information technology to support biotech researchers in creating databases to store and manage large data sets. They also help build algorithms and statistics to determine relationships among datasets and use these tools to examine and interpret biological data.

Cancer Treatment and Research

Data science in biotechnology can help in cancer treatment and research. Getting aware of a patient's symptoms and prognosis and then comparing it to a people's database with the same symptoms will help medical professionals to determine how they can commence the cancer treatment process. Big data helps in evaluating the massive amount of information available and categorizing data based on age, race and gender so that medical teams will have more detailed information to treat cancer.

According to Alexis Borisy, Warp Drive Bio CEO, the prospect of widespread genetic mapping coupled with the power of Big Data could fundamentally change how biotech does R&D.

Personalized Medicine

Data science has a tremendous impact on personalized medicine, a medical approach where patients are stratified based on their disease subtype, risk, prognosis, or treatment response using specialized diagnostic tests. Personalized medicine these days is strongly linked with genomics. However, genomics and other biological high throughput data such as transcriptomics, epigenomics, proteomics, and metabolomics, are by no means the only source of data employed in the personalized medicine field.

Drug re-positioning company NuMedii and the computer maker Dell have shown that big data is a perfect complement to science and future success in developmental research. Dell is majorly known for its computer manufacturing, but the company has also a long track record for its strides in the healthcare industry. It realizes that big data could be applied to genomics to make a profound impact on the quality of patient life. Today, Dell employs over 13,000 people in the health industry to advance personalized medicine and create faster genomics and other advancements.

Moreover, data scientists can bring major advances in medical biotechnology by using individualized genome sequencing as a factor in predicting the onset of a disease. As the entire biotechnology industry is shifting to a data-centric era, data science can help advance patient care by allowing caregivers to make data-driven decisions.