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'60 Leaders on Artificial Intelligence' brings together unique insights on the topic of Artificial Intelligence - from the latest technical advances to ethical concerns and risks for humanity. The book is organized into 17 chapters - each addressing one question through multiple answers reflecting a variety of backgrounds and standpoints. Learn how AI is changing how businesses operate, how products are built, and how companies should adapt to the new reality. Understand the risks of AI and what should be done to protect individuals and humanity. View the leaders. 

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'60 Leaders on Innovation' is the book that brings together unique insights and ‘practical wisdom’ on innovation. The book is organized into 22 chapters, each presenting one question and multiple answers from 60 global leaders. Learn how innovative companies operate and how to adopt effective innovation strategies. Understand how innovation and experimentation methods blend with agile product development. Get insights from the experts on the role of the C-Suite for innovation. Discover ways that Innovation can help humanity solve big problems like climate change.

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How is AI impacting the way businesses operate?

Raj Madan


Daily, I am reminded of how complex the healthcare industry is and how nascent we still are in terms of transforming our industry. It still takes the industry several years to discover/develop most drugs (although COVID vaccine development was one positive exception) and patient experiences are sub-optimal (often a slow path to diagnostics for several diseases, mismatch of treatment pathways to patient’s determinant of health, etc.).

On the other hand, patient expectations have changed – the consumerization of healthcare is no longer a thing of the past and patients want to take more control of their healthcare needs. The industry is also collecting more and more data from various sources (think smartwatches or remote patient monitoring devices) that, if leveraged effectively, can disrupt the industry and create huge opportunities to improve patient outcomes.

So how can AI bring value to the healthcare industry? While the application of AI in Healthcare continues to grow, here are the top use cases:

- Diagnostics. AI-based image recognition and matching technology has evolved rapidly over the last few years and has created opportunities for specialists (think radiologists) to validate their findings. In parallel, this technology is already starting to put diagnostics in the hands of patients, for instance, to empower them to initially diagnose skin and eye conditions. As an example of where this is being used, as per Google , “2 billion people around the world have skin, hair, and nail conditions” and in response to this need, they recently launched the DermAssist tool which allows you to “find personalized information about your skin concerns after a few questions and three quick photos” and can “identify 288 skin, nail and hair conditions.”

- Drug Discovery and Development. Historically, less than 10% of drug candidates commercialize. The entire process can take about 10-15 years and the costs are normally in the millions (if not billions) of dollars. This is where AI can help reduce lead times and costs by (a) identifying potential drug targets (a molecule in the body, usually a protein, that is intrinsically associated with a particular disease process and that could be addressed by a drug to produce a desired therapeutic effect ) that have a high likelihood of providing positive patient outcomes for a specific disease or therapeutic area and then (b) understanding how patient cohorts will interact and react to that drug target. How do AI models do this? AI models generally parse and search through a vast amount of scientific data sets, look for matches (often by also considering existing drug targets in other therapeutic areas) and analyze/predict their safety and efficacy profiles.

Now, the use of AI doesn’t come with a lack of challenges and risks in the healthcare industry. For starters, the healthcare ecosystem consists of several players – think providers (healthcare systems, doctors, etc.), payers (insurance companies), and then pharma and biotech companies (that often perform drug discovery/development activities and commercialize these products). This means that for AI to deliver value across the entire healthcare value chain, frictionless coordination and integration is necessary, which has often been difficult to date.

Additionally, the healthcare industry is highly regulated, and the use of AI to provide and replace human-based diagnosis, although not impossible to achieve, will continue to be a steep climb and one that will always continue to require human intervention in my opinion - until AI models are 100% error-proof. Lastly, the promise of AI lies in its adoption, and with an increased focus and concern about data privacy and security, organizations deploying AI (especially directly to patients) need to ensure that patients have complete transparency to how their data is used, stored, and controlled.

"For AI to deliver value across the entire healthcare value chain, frictionless coordination and integration is necessary, which has often been difficult to date."

Raj Madan has over 20 years of digital transformation and innovation experience and is currently the CDIO at Arcutis Biotherapeutics. Prior to joining Arcutis, Raj served as the Vice President of Digital, Data/Analytics and Innovation for Consumer Healthcare Technology at GlaxoSmithKline (GSK), where, in partnership with the Chief Digital Officer, he was responsible for driving significant elements of their Digital and Tech transformation globally.


Raj Madan

"AI can help identify potential drug targets with a high likelihood of providing positive patient outcomes."

Chief Digital and Information Technology Officer




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