The pharmaceutical and life science industry leads in AI adoption,
according to a research, Amplifying Human Potential – Towards
Purposeful AI, conducted by Infosys.
However, this leadership position
was not gained overnight. It was earned over several years, in which
this sector has adopted AI to conduct clinical trials, perform drug
analysis and fast-track product launches.
Besides improving process and operations efficiency, AI is playing a very crucial role – as a life saver.
Take for instance AI applied to identify skin blotches
that could be a melanoma.
By augmenting doctors’ and radiologists’ capabilities, it is detecting
melanomas early and increasing survival rates by as much as 98%. This is
significantly higher than the 16% survival rate when melanomas are
detected before progression to the lymph node.Besides improving process and operations efficiency, AI is playing a very crucial role – as a life saver.
Similarly, complex AI algorithms
are being put to work by the Center for Rare Childhood Disorder to
analyse large amounts of molecular and genetic data to identify medical
conditions and create personalized treatment plans. AI based systems are
doing things differently from human professionals. For starters, they
are able to collect more information. Then, they are able to use this
data to make unbiased decisions about diagnosis and treatment.
Enhancing Human Decision Making
Though
AI systems cannot be allowed to work completely without human
intervention, their analytics based insights can be used to augment
decisions across the organization. In fact, the Infosys research
uncovered that AI is meeting expectations in 40% of organizations in the
life sciences and pharmaceutical industry. Respondents said that big
data and machine learning were the two most promising technologies.
With electronic health and medical records slowly gaining adoption in India, a lot of valuable patient data is being generated. When applied to it, AI can uncover pertinent insights that doctors can use to create more effective treatment plans. This can be quite crucial in areas like personalized treatment and early disease detection that have received relatively less attention.
Until now, the biggest obstacle to AI adoption has been a fear of loss of data and a concern that data can get stuck in silos, even within the organization. But, this obstacle is gradually giving way to the opportunity to leverage AI. What’s the catalyst? Millennial consumers, who believe that if they can trust technology with their money, then they can trust their healthcare data too.
The Future of AI Powered Treatment
Necker Children’s Hospital recently showed the world what AI powered treatment can be like in the coming years, or even months. It has become the first to genetically modify bone marrow with AI in a sickle cell anaemic patient, who was fine more than a year post the procedure. In another instance of AI excellence, CAR-T therapy was used to remove, genetically change and reintroduce T cells in patients – all within just two weeks.
Similar medical marvels are now possible because of the new AI technologies and analytics tools that have the capability to analyse large quantities of patient health and genetic data, and medical image analysis. And all this paves the way for more precise diagnosis, and faster medicine regulatory and compliance approvals. More importantly, it will enable the development of personalized medicine and gene therapy, which will allow us to step out of the “one drug fits all” concept.
Striking a Balance between Progress and Regulations
Concerns around the ethics of AI use in pharmaceuticals, life science and even healthcare, is nothing new. However, it still very much merits attention. And it is to alley these fears and concerns that the industry has been on the lookout for methods to standardize AI solutions and align them with the requirements of regulatory agencies worldwide. Nevertheless, excessive focus on regulations will have a restrictive effort on any progress that AI has made in entering the industry.
This is why we have to be cautious about how much restraint we exercise on AI solutions in this context. If we are too careful it could curb any progress that AI will have to make to cure diseases and ultimately save lives. So, in other words, we need to strike a balance between ensuring that AI is allowed to advance so that it can help treat illnesses more efficiently and keeping it within regulatory parameters to prevent it from having unexpected effect on people – patients and professionals in the healthcare, life sciences and pharmaceutical industries.
While AI has the potential to automate several tasks, especially the repetitive and mundane ones, I believe that it will, much like every other technological predecessor, give rise to new opportunities that professionals can move into. What’s more, it will continue to be a complementary force or an assistant to professionals for a while to come. AI will remain machines that humans can leverage for augmenting decisions and capabilities, and improving their efficiency.
In fact, just recently I witnessed one such incredible use of AI. We were working with a large pharmaceutical company to help develop a digital lab. And it was amazing to see the joy of the lab chemists who got the opportunity to use automation processes that allowed them to prevent mistakes and accomplish a level of near-zero rework that saved hours that they would otherwise have spent trouble-shooting.
AI will be of most significance to companies that are open to using it to enhance the capabilities of their existing workforce and leveraging their professionals in other new and more valuable roles. Our research revealed that close to 80% of those tapping into AI today are willing to reskill, retrain and redeploy employees. That said, we should all remember that AI cannot work on its own.
AI cannot find answers to all the problems that a trained professional can. What it can do is help us get a better understanding of diseases. It can help physicians make more informed decisions. It can help reduce the need for experimentation. It can help professionals fix issues faster and get more focused insights. AI can help standardize medicine development and prescription. All-in-all, AI integration will benefit us in the long run.
Enhancing Human Decision Making
Though
AI systems cannot be allowed to work completely without human
intervention, their analytics based insights can be used to augment
decisions across the organization. In fact, the Infosys research
uncovered that AI is meeting expectations in 40% of organizations in the
life sciences and pharmaceutical industry. Respondents said that big
data and machine learning were the two most promising technologies.With electronic health and medical records slowly gaining adoption in India, a lot of valuable patient data is being generated. When applied to it, AI can uncover pertinent insights that doctors can use to create more effective treatment plans. This can be quite crucial in areas like personalized treatment and early disease detection that have received relatively less attention.
Until now, the biggest obstacle to AI adoption has been a fear of loss of data and a concern that data can get stuck in silos, even within the organization. But, this obstacle is gradually giving way to the opportunity to leverage AI. What’s the catalyst? Millennial consumers, who believe that if they can trust technology with their money, then they can trust their healthcare data too.
The Future of AI Powered Treatment
Necker Children’s Hospital recently showed the world what AI powered treatment can be like in the coming years, or even months. It has become the first to genetically modify bone marrow with AI in a sickle cell anaemic patient, who was fine more than a year post the procedure. In another instance of AI excellence, CAR-T therapy was used to remove, genetically change and reintroduce T cells in patients – all within just two weeks.
Similar medical marvels are now possible because of the new AI technologies and analytics tools that have the capability to analyse large quantities of patient health and genetic data, and medical image analysis. And all this paves the way for more precise diagnosis, and faster medicine regulatory and compliance approvals. More importantly, it will enable the development of personalized medicine and gene therapy, which will allow us to step out of the “one drug fits all” concept.
Striking a Balance between Progress and Regulations
Concerns around the ethics of AI use in pharmaceuticals, life science and even healthcare, is nothing new. However, it still very much merits attention. And it is to alley these fears and concerns that the industry has been on the lookout for methods to standardize AI solutions and align them with the requirements of regulatory agencies worldwide. Nevertheless, excessive focus on regulations will have a restrictive effort on any progress that AI has made in entering the industry.
This is why we have to be cautious about how much restraint we exercise on AI solutions in this context. If we are too careful it could curb any progress that AI will have to make to cure diseases and ultimately save lives. So, in other words, we need to strike a balance between ensuring that AI is allowed to advance so that it can help treat illnesses more efficiently and keeping it within regulatory parameters to prevent it from having unexpected effect on people – patients and professionals in the healthcare, life sciences and pharmaceutical industries.
While AI has the potential to automate several tasks, especially the repetitive and mundane ones, I believe that it will, much like every other technological predecessor, give rise to new opportunities that professionals can move into. What’s more, it will continue to be a complementary force or an assistant to professionals for a while to come. AI will remain machines that humans can leverage for augmenting decisions and capabilities, and improving their efficiency.
In fact, just recently I witnessed one such incredible use of AI. We were working with a large pharmaceutical company to help develop a digital lab. And it was amazing to see the joy of the lab chemists who got the opportunity to use automation processes that allowed them to prevent mistakes and accomplish a level of near-zero rework that saved hours that they would otherwise have spent trouble-shooting.
AI will be of most significance to companies that are open to using it to enhance the capabilities of their existing workforce and leveraging their professionals in other new and more valuable roles. Our research revealed that close to 80% of those tapping into AI today are willing to reskill, retrain and redeploy employees. That said, we should all remember that AI cannot work on its own.
AI cannot find answers to all the problems that a trained professional can. What it can do is help us get a better understanding of diseases. It can help physicians make more informed decisions. It can help reduce the need for experimentation. It can help professionals fix issues faster and get more focused insights. AI can help standardize medicine development and prescription. All-in-all, AI integration will benefit us in the long run.
By Subhro Mallik
Vice President, Life Sciences Infosys
Vice President, Life Sciences Infosys
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