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AI in pharmaceuticals

Artificial Intelligence will take over our jobs, potentially leading to the destruction of the current social system.


In the words of Elon Musk, A.I. is “potentially more dangerous than nukes” and Stephen Hawking highlighted that it could be “the worst thing ever to happen to humanity”. Or, can Artificial Intelligence, Machine Learning, Blockchain and other recent technological advances contribute to the Life Science industry, specifically the Clinical Trials and Patient Access to medicine? Can it lead to better R&D, better access for patients and an improved in work for humans.

If so, where does recruitment fit into the jigsaw?


Clinical Trials

Nearly 80% of clinical trials fail because they cannot recruit enough patients or cannot retain participants (1). Furthermore, patient enrolment methods have typically relied on doctor referrals or phone-based recruitment services which have not gone far enough to bridge the gap between patient and trial. 6 AI is a company focused on patient recruitment and applies artificial intelligence to scour thousands of medical records to find suitable participants in a much shorter time frame, claiming to be able to find patients in “minutes not months”.


Patient Diagnosis

Within cancer detection, researchers from Germany, France and the US were able to diagnose skin cancer more accurately than dermatologists by using artificial intelligence. An algorithm was shown 100,000 images of malignant melanomas as well as benign moles, accurately detecting cancer in 95% of images of cancerous moles and benign spots, whereas a team of 58 dermatologists was 87% accurate. Given that over 2.5 million people are living with cancer in the UK alone (2) an 8 percent improvement in cancer diagnosis can have the potential to save a substantial amount of people.


Another company making waves in the Life Science AI space is Babylon Health. Ali Para, Co-founder, has claimed that their A.I. is able to diagnose a range of health conditions. When tested against seven experienced doctors to determine its ability to accurately diagnose a wider range of health conditions the algorithm was able to correctly diagnose 80% of the time, compared to a 64% to 94% accuracy for the doctors. This has led the company to make strides within the pharmaceutical industry but also resulted in the company winning several lucrative contracts with the NHS. However, Babylon’s assessment has not been convincing for everyone. The Royal College of General Practitioners rebuked Babylon’s claims as “dubious” and generally incomparable to the responsibilities handled by doctors. Also, their test to date has not been published in any peer review journal.



For all the potential benefits, A.I. is still very much a new technology with a lack of oversight/ testing on accepted improvements for patients. A.I. and Machine Learning has taken huge strides over the past decade, however, the technology is still in its early stages and its benefits on the Life Science industry is still up for debate.

Where does this leave the recruitment sector with Life Science A.I. and Machine Learning? The answer is unknown. As yet, the A.I. piece of the jigsaw puzzles lacks the surrounding pieces to know where it fits in the puzzle. Investment along with stringent testing of the technology in the coming years will, in our, opinion, bring genuine value and improvements to the industry and patients. For career paths, any additional courses teaching the basics of A.I. would be a sensible starting point now for those candidates who want to be positioned to take advantage of the almost certain uptake in the technology.






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