Artificial intelligence (AI) is a growing technology that is finding applications in all aspects of life and industry: within the smart assistants found within the latest smartphones, and in the smart factories that use AI to enhance their efficiency. Likewise, the pharmaceutical industry is finding new and innovative ways to use this powerful technology to help solve some of the biggest problems facing pharma today.

As discussed in GlobalData’s recent report ‘Artificial Intelligence in Healthcare,’ there are numerous areas within the pharmaceutical industry that can benefit from the use of AI. Key among these is drug development. Currently, drug development is in decline and has been for many years; this trend has led to the creation of ‘Eroom’s Law,’ which is the reverse of the ‘Moore’s Law’ concept in computing. It states that the number of drugs being approved decreases year on year while the costs increase. The problem behind this decline is the fact that nine out of every 10 drugs being developed fail to make it to pre-registration due to poor efficacy or poor absorption, distribution, metabolism, or excretion (ADME).

AI is being looked to for help with alleviating this decline through the use of innovative techniques such as in silico (on a computer) drug design,  which allows for the mapping of drug structures and targets, allowing for the development of more successful drugs without the costly scientific development. Companies such as Merck have led this movement into AI with an early partnership with the AI company Numerate in 2012 to generate predictive models to design novel small molecular leads.

Another novel technique being used to break this development deadlock is big data analytics, which utilizes the vast amount of scientific data generated by drug development to develop systems that can help guide and focus drug development by predicting the properties of new drug candidates.

Novartis is paying especial attention to this, developing their own advanced analytics platform with which they will be able to predict study risks and their drivers to enable preventive maintenance and remediation of the drugs. With AI being able to offer new opportunities to develop and produce drugs while minimizing the risks inherent in their discovery, the pharmaceutical industry is set to continue an ever closer relationship with AI.

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