Artificial Intelligence and the Future of the Pharma Drug Trial

The future of the pharma trial start with a mistake from the past. A drug made by Sanofi to treat epilepsy and bipolar disorders that was given to pregnant mothers resulted in up to 4,100 French children being born with major birth defects. During a 50 year time span from 1967 to 2016, between 2,150 and 4,100 children were born with at least one serious congenital disorder after being exposed in the womb to a drug called valproate.

The damage caused by Valproate during this time shows an urgent need to change both how trials are run and how drugs in the market are monitored over time. This and other similar mistakes should act as a wake-up call to the whole industry. The pharmaceutical industry is failing in its mission to create better drugs and improve health, mostly due to the trap of legacy thinking.

Artificial Intelligence and better access to data is the only way to solve this critical problem. Pharma drug trials are currently limited in size, slow to run and limited in scope. This needs to change. The future will rely on a more flexible protocol, as a much bigger audience is needed.

What can be monitored both in terms of scale and accuracy has increased greatly over the past 5 years. The emergence of IoT (internet of things) devices will aid in wider data collection, at a reduced cost. To make sense of this data a new approach is needed. This is where the advantages of AI come into play. Being able to understand data at this scale goes beyond human-level analysis towards machine understanding. Making connections and leaps that we can’t.

Separately, it seems that Sanofi had not been as ‘transparent with health authorities‘ as they claim, but did this extend to meaningful patient communication? This is not to directly blame Sanofi but rather encourage Pharma companies to improve what they share with their clients. And their client should always be thought of as the patient, rather than Doctor, hospital or purchasing board.

Public trust is going to be fundamental when it comes to sharing data. Without trust, widespread data will be kept private and inaccessible. This could impact the future of trials and monitoring for generations to come, harming everyone in the process.

While there is an obvious need for legal a solid legal framework when it comes to pharma drug trials, the current approach is based on outdated thinking. The new reality is that both AI and personal data demand a radical shift in thinking. The work involved will be complex and take time but the end result will be the smarter drug trial and monitoring we all deserve.

It is time for Pharma, Doctors, Lawyers and the public to get together and figure out how AI can take a stronger role in drug trials and monitoring. We must let go of legacy thinking and embrace new systems and approaches.

It is time to start planning for a sophisticated AI future today, so we have better drug trials tomorrow.

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