How Machine Learning Will Transform Biomedical Research

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• Session 1

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• 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.

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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.
  

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• 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.

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• 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 RD 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.

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• 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.

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• 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.

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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.

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Conclusion

• 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.

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