AI is the Next Wave of Innovation For Life Sciences and Pharma

AI is the Next Wave of Innovation For Life Sciences and Pharma

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Innovation doesn’t always happen at a steady pace. Most often, technological revolutions happen all at once, with rapid change and disruption, often followed by a lull as people get used to the new normal. Noted futurist from the mid 19th century, Alvin Toffler, once expressed this concept as a series of ‘waves’. In his example, each wave of innovative technology washes over the previous one. This means that with each new technological development, the old is washed away and a new era ensues.

 

We believe that we are at the start of a new wave of technological innovation, one that will completely disrupt the way we view medicine, research, and our own health. This wave is being powered by advances in AI and machine learning that are making it possible for researchers to develop cures faster, doctors to deliver more effective care, and healthcare companies to reduce costs while increasing access to care.

 

Imagine a world in which better data analytics mean a cure takes months to develop instead of years. Or a future in which a doctor in a rural area has access to the same data resources that the biggest metropolitan hospitals use. By adapting machine learning technologies to the field, this future could be a reality sooner than one might predict.

 

Lifesciences, pharma, and healthcare are no strangers to rapid disruption like this. In the 1970’s, developments in molecular biology rocked the field and changed the way scientists approached medicine. The human genome project was the next wave of innovation that hit in the 1990’s, changing the way we view ourselves and life as we know it.

 

Data and intelligence are powering a new age of research and discovery that will help us develop treatments faster and reduce the high costs associated with work in the life sciences. In doing so, they will help make a more fair and accessible healthcare system, while increasing the health and happiness of everyone.

 

Additionally, with the volume of medical research growing rapidly around the world, new opportunities for the development of advanced treatment options are on the rise. Breakthroughs will rely on researchers’ ability to access key data sets, faster, and more efficiently than previously possible. By deploying sophisticated AI tools, we can help researchers turn troves of unstructured data into actionable insights that lead to treatments in a fraction of the time it usually takes to develop them.

 

The need to accurately and rapidly identify data that may be relevant has been challenging for life sciences professionals because a good deal of this data has been housed in information sources that aren’t readily searchable. Research PDFs, diagrams, and visual data sources all need to be a part of complex search algorithms.

 

The good news is, data-as-a-service companies, and life sciences firms can partner to help make this data more accessible for researchers, which could result in new drugs and cures delivered faster.

 

Speeding Up Innovation

 

As these parties work together to advance the state of the field, interdisciplinary approaches are being developed. By creating more holistic research tactics, founded in better data, companies can make better decisions regarding the development of treatments, and invest in efforts that impact a lot of people, while remaining profitable. Keeping these companies profitable, is critical for the healthcare industry because it will help fuel continued research and development.

 

Big Data, IT, and the life sciences need to come together to help speed up the pace of innovation, and they can do that by increasing the exchange of ideas and information and removing barriers to collaboration. The best way to do this is by rethinking the way organizations access and make the most of their data.

 

They must also integrate the latest in mathematics, artificial intelligence, and machine learning, to help identify trends, while improving search functions for researchers. If we’re able to do these things, we can expect a whole host of benefits, not only for industry leaders improving their business but also for end users and patients.

 

The outcomes we seek are ambitious. Faster development of life-improving or life-saving drugs, better treatment across all regions and socioeconomic backgrounds, and companies that develop drugs rapidly at a lower cost for themselves and the end user. With the use of the latest in AI and machine learning technologies, we can work together to help make those goals a reality, building better industries and making people healthier.

 

About the author: 

 

Gunjan Bhardwaj is the founder and CEO of Innoplexus, a leader in AI and analytics as a service for life science industries. With a background at Boston Consulting Group and Ernst & Young, he bridges the worlds of AI, consulting, and life science to drive innovation.

Author

Gunjan Bhardwaj

Gunjan Bhardwaj is the founder and CEO of Innoplexus, a leader in AI and analytics as a service for life science industries. With a background at Boston Consulting Group and Ernst & Young, he bridges the worlds of AI, consulting, and life science to drive innovation.

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