How the Cloud Can Solve Life Science's Data Science Problem
The life science industry has advanced significantly over the past few years. However, the industry has not yet found a way to collect and analyze vast amounts of data and translate that data into relevant scientific conclusions that can impact the field of life science. Industry players are divided between biotech startups, legacy companies, and small businesses. Small businesses often lack the resources to handle giant data dumps. Legacy companies may find it hard to transition from their existing data framework based on older models. Biotech startups that have built their own data storage technology have the most flexibility. The production of bio-engineered foods could also become more widespread with cloud technology.
The Cloud facilitates data compilation and sharing among people in different locations. Researchers can take advantage of specialized experts in foreign countries and connect with them via the Cloud. Cloud software gives researchers a space to store their designs and make them accessible to collaborators. Benchling has become a popular tool for data scientists who use customized cloud software that features design tools for proteins and DNA. The benefit of cloud software is that it can be used on the scale that best fits the researcher's needs, whether that be on the level of individual inquiry or for use by a major pharmaceutical company.
Cloud technology can allow scientists to progress faster from the research stage to running clinical trials. Using cloud software for sample analysis accelerates the production and development of new medicines. As more data is efficiently collected, it could be possible for scientists to make personalized medicines for specific categories of patients.
The Cloud raises the possibility of sharpening and exploiting machines' artificial intelligence to find and create patterns that humans may not be able to see at first glance. Genome sequencing has become cheaper and faster with the advent of more advanced technology. Reliance on high-performance computers to process hundreds of gigabytes of data is exorbitantly expensive for some scientists who lack the backing of a large biotech company. Such computers are costly to maintain and upgrade. Cloud technology lowers the costs of research participation, increasing the diversity of perspectives. Funds can then be diverted from spending on hardware to investment in new life science discoveries.