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AI Across the Pharmaceutical Lifecycle

Since its inception, artificial intelligence has been shaking up the life sciences industry. Such is the assumed potential of intelligent apps that experts believe artificial intelligence-enabled drugs will be on the market in the near future.

Traditionally the variety of data which comes from a variety of sources has meant that the gathering, management and effective use of this data have been time-consuming and often problematic. Artificial intelligence has long been seen as a way to effortlessly use both this structured and unstructured data effectively. It is thought that data analysed by artificial intelligence could become vital in the approval process, improving adoption rates and collecting real-world outcomes.

Additionally, safety and tolerability issues could be identified and resolved long before they have the chance to pose a real problem. There is also a correlation between personalised medicine and artificial intelligence as the information artificial intelligence is able to gather will make it easier to determine what drugs will best suit a patient.

An issue that will become far more significant with the Identification of Medicinal Products (IDMP) standards is that the data for individual products will be created, accumulated and retained by different operations often in different locations. It is hoped that artificial intelligence will make accessing the pertinent pieces of this wide sea of data a simple, streamlined process. The data gathered by artificial intelligence for IDMP can also potentially be fed back to businesses, informing their development, manufacturing and marketing work.

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Away from IDMP artificial intelligence is already working in the supply chain. Zipline, a drone startup, has been using artificial intelligence controlled drones to drop blood products in Rwanda since 2016. This autonomous delivery is likely to become more common across all forms of healthcare delivery. In doing so it is following artificial intelligence models adopted by companies like Amazon.

Meanwhile, pharmaceutical companies are exploring the possibility of using artificial intelligence in a variety of ways. GlaxoSmithKline is at the forefront of artificial intelligence apps that can provide information for patients, teaming up with IBM’s Watson for a Q&A feature for it’s cold and flu medication Theraflu.

Despite all the potential, there are barriers to overcome. Most notably there is a concern at how well the regulatory bodies will be able to keep up with the fast-paced developments made in the world of artificial intelligence. It may take time for the authorities to adopt the guidelines to suit an artificially intelligent world but the potential it brings and the growing popularity of artificial intelligence means that these changes can not be put off forever.

Source Pharmtech

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KC Cheung
KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
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