Article: Hasta la vista, maybe? Terminating the Hollywood view of AI in pharma

Published in PME Magazine

Rumours that robots will eventually wipe out humans are the futuristic stuff of Hollywood blockbusters. The real-world story arc is much more uplifting but no less dramatic. When a homeless man in central England was crushed to death by a compaction unit as he slept in the dustbin in 2013, it triggered a response from the UK waste management industry that now sees many refuse trucks fitted with senor technology to detect people in bins.

It's an early example of how AI can literally save lives. Fast forward six years and we've now got 'robot doctors' detecting cancers, smart remote monitoring systems managing patients miles from their homes and algorithm-led technologies predicting long-term health based on individuals' DNA. The application of AI in health isn't science fiction, it's happening fast - and it’s positively disrupting patient care. 

Global investment in healthcare AI is predicted to reach $6.6bn by 2021, with Accenture forecasting its use will drive annual savings of $150bn by 2026. McKinsey aims even higher, suggesting the value AI creates could save global healthcare an eye-watering $269.4bn a year. Major health providers are investing in IoT, machine learning and predictive analytics to replace the ageing cost structures and processes that obstruct efficient care. The range of innovation is dizzying; robot-assisted surgery, virtual consultations and diagnostic algorithms that trigger and escalate care are the tip of the iceberg. Technology giants are partnering with specialist health providers to deep mine data, interpret scans and reduce the workload on HCPs. AI is also being used to create virtual nursing assistants, improve administrative workflow and reducing dosing errors. Developers are even working on technology that provides 3D holographic representations of patients’ anatomies for people that cannot be present with a doctor, and combines it with their physiological data and full medical history to inform an accurate diagnosis. The wider goal is to transfer time-consuming tasks from human to machines, accelerating pathways, freeing resource and helping clinicians make faster, more accurate decisions that enhance patient care. Far from replacing humans, it’s helping us do more and do better.

But what of pharma? How is the industry using AI to improve processes and transform the treatment of disease? There are signs of advancement right across the product lifecycle...