How Machine Learning Will Transform Biomedical Research

Technological advancements have made our world different in a good sense. It has impacted different areas of our life, even the medicine, and pharma sector. We are now living in an era where technology is influencing the way medical facilities and medicines are administered to people. All this requires a lot of research and development. Machine learning is playing a key role in this. Today machine learning experts are using their skills to make some outstanding developments in the field of biomedical research, and we will be exploring the same in this blog.

As per the reports of McKinsey, big data and machine learning generate a value of up to $100 billion in the field of pharma and medicine. This is based on enhanced decision making, improving the efficiency of research and clinical trials, and creating new tools. In the pharma and medical field, the burgeoning applications of machine learning in the pharma and biomedical sciences show the glimmering scope of ML.

Here is how Machine learning is impacting biomedical research

  • Identification Of Disease– one of the biggest uses of machine learning is identifying diseases. As per the report of Pharmaceutical Research and Manufacturers of America (2015), more than 800 medicine and vaccines are in trial. These medicines are used for treating cancer. Many large pharma companies are making use of machine learning methodologies that are eventually enhancing the work process. Since this technology focuses on better assessment of data and finding out a solution. IBM Watson Health announced IBM Watson Genomics that aims to make developments in making medicines more effective by integrating cognitive computing and genomic tumor sequencing.
  • Personalized Treatment– Another area of application of ML is in administering personalized treatment. This medicine is developed by administering the personal health of an individual. Personalized medicine is a more effective treatment based on individual data paired with predictive analytics. This will help in better assessment of disease. IBM Watson Oncology is a leading name working in this domain and is making use of a patient’s personal information and history to optimize the treatment option. Although this research is at the initial stage, it holds a lot of prospects in the future. With the use of data about patients, it will be easier for medical practitioners to render the right kind of medicine to individuals.
  • Drug Discovery– The use of machine learning in drug discovery is at the nascent stage. But, it surely has the potential to make some significant changes, starting from the initial screening of drugs to predict the success rate of medicine based on the patient’s personal medical information. It used R&D technologies like next-generation sequencing. Another point that we would like to mention here is precision medicine, which involves identifying medicines for diseases and finding alternative therapy paths. Much of this involves unsupervised learning.
  • Clinical Trial Research– ML has a lot of potential to shape and direct clinical trial research. Using predictive analytics to identify candidates for clinical trials can draw a much wider range of data than the technologies we are using today. This information includes genetic information, doctor’s visit, etc.

Besides, ML can also be used for monitoring, and real-time data access to enhance safety. For example, screening the biological and other signals of harm.

As per the report of McKinsey, many ML applications will help in increasing clinical trial efficiency, like finding the best sample size to enhance the efficiency of medical procedures.

These are just a few of the many use cases of machine learning in the field of pharma and biomedical research. Various developments are going on in this field.

Many companies are now employing machine learning experts or looking for individuals who have machine learning certification. Machine learning uses a wide range of algorithms and methodologies, which can eventually enhance medical research.

What’s Next?

Owing to huge development and demand in ML, it has emerged as a popular career option. Nowadays, many individuals are seeking this as a career option. Global Tech Council is providing an online machine learning certification program. This machine learning training incorporated complete learning about machine learning and allowed concepts. You will also learn about the information and the role of AI in healthcare. Both these are going to increase in the times to come. If you are also willing to become a machine learning expert, you must go for a machine learning certification program.

The Future-

Machine learning is a game-changer in the field of technology. It is paving the way for a lot of development, which is eventually going to benefit the pharma and medical field. Leveraging ML in pharma and medical has become a prime interest for many big names in the industry. ML has triggered the medical revolution by improving it and making it more efficient and flawless.