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Analytics has a long history of existence in different forms and practice. From the beginning, people predicted things about the future—predicting rain for the afternoon based on seeing clouds in the sky was perhaps one of the earliest forms of predicting. While computing and digitally capturing of data occurred later in history, we can easily assume that human brains were doing analytics and decision-making in everyday living throughout the history of mankind. The question has always been how much and how accurately into the future one can predict.
Analytics has the capability to not just tell us what is happening, but more importantly, why it is happening and whether it is likely to happen again. We can certainly agree that analytics is a phenomenon at scale today, which is applied in every aspect of life and business with the ability to digitize data and the democratization of computing. Almost all business decisions being made today are driven by some underlying analytics so that individuals can make decisions and hypotheses based on data rather than just human intuition. When you can truly rely on data that requires less human involvement, the analytics are highly predictable and reliable.
The fusion of computation and biology is indeed the new frontier of analytics/machine learning and is being pursued by almost all cutting-edge research in life science and healthcare. Today, we have the ability to digitize human genome at scale. Think about the possibility of looking into more than 3 billion base pairs of genetic codes of millions/billions of people! It is certainly an exciting possibility for analytics/machine learning and discovery. We are at the beginnings of personalized care in the world of healthcare by simply being able to unravel the mystery of the genetic codes, which dictate every aspect and characteristic of each of us and, until recently, have been an unknowable mystery of nature. The market is witnessing many instances of joining hands between tech companies and life science/Pharma companies to pursue the fusion of biology and computing.
Molecular biology is a science focused on learning the complexities of nature and cell using computing, and analytics has helped tremendously on this journey.
The fusion of computation and biology is indeed the new frontier of analytics/ machine learning and is being pursued by almost all cutting-edge research in life science and healthcare
The future for life science and healthcare is indeed very fascinating and promising with the fusion of computing at scale, machine learning/artificial intelligence with algorithmic maturity, and techniques and opportunity to digitize molecular biology and proteomics. We will continue to see transformational progress in the coming decades, especially in the following three areas in life science and healthcare:
1. Generative chemistry powered by artificial intelligence/ machine learning will enable finding molecules with certain potential therapeutic characteristics to cure or treat more diseases.
2. Ability to perfect the manufacturing and delivery of the evolving cell and gene therapy with digitization of molecular biology and proteomics.
3. A world of connected humans with biosensors with non-intrusive form factors that continuously read vitals or life sustaining functions abstracted as signals and do edge computing and analytics to predict what is required to maintain good health, just like preventive maintenance for machines.
While we may never be able to unlock all the secrets of nature, we are indeed gearing up for an era with the potential ability to fight the worst diseases of nature, which too often lead to premature death for too many.