Alright, let’s get into this. AI is the new kid on the block, already shaking things up in the pharma and biotech industries, promising to make operations smoother, drug development more efficient, and life easier for the workforce. It’s not a shy wallflower either. It’s standing up to be noticed, with a few adventurous biotech companies already putting AI-developed drugs through the human testing mill.
Picture the scene. Digital health companies, healthcare providers, insurers, they’re all scratching their heads, figuring out how to use technologies like ChatGPT to streamline their tasks. We’re talking patient assessments, the completion of medical notes, all while keeping a firm grip on patient safety and privacy.
Leading the charge in this AI revolution is David Ricks, CEO of pharmaceutical heavyweight Eli Lilly. This isn’t just a passing interest for them. They’ve got skin in the game. Developing a plethora of drugs through clinical trials, they’re predicting a not-too-shabby $30 billion in revenue this year. Ricks seems pretty jazzed about AI, calling it “one of the most exciting technological moves” he’s seen in his lifetime, putting it right up there with the unveiling of the iPhone and the birth of the internet.
Eli Lilly, valued at a whopping $420 billion and known for their blockbuster diabetes and cancer treatments, is throwing its weight behind a string of AI projects. They’re working on AI and machine learning in areas such as drug discovery, natural language generation, robotic process automation, and chatbots. All this is part of their grand plan to expand what they call their “digital worker-equivalent workforce”.
This is all about saving time through technology, freeing up humans from the slog of mundane tasks. Lilly’s initiative, which kicked off in 2022, now spans over 100 projects, the equivalent of about 1.4 million human work hours or 160 years of 24/7 graft. Their ambitious aim is to boost this to 2.4 million hours by year-end, roughly equivalent to 274 years. As for the price tag of this initiative, they’re keeping those cards close to their chest.
Ricks has a vision for the three main ways he sees AI could be put to work in Lilly and the wider biopharma sphere. First, it could take on the mundane steps in tasks like contract production or the boring bits of admin work. It’s not about replacing humans, but rather about enhancing human productivity, starting with the easy stuff.
Next, in a heavily regulated industry, AI could take a crack at automating repetitive business processes. Ricks sees this as a perfect task for AI tools like Chat GPT, which can be trained on their data to produce documents more rapidly – documents that, while necessary for regulatory compliance, aren’t directly benefiting the patient.
The final piece of the AI puzzle is drug development. An AI model could throw out ideas from a data set that human chemists might not have considered or been able to visualize. They recently announced a $250 million partnership with pharma tech company XtalPi to sniff out new potential drugs using AI.
As Ricks put it, in the discovery process, you want a broad funnel. In the past, humans may have only considered what they already knew. The beauty of AI is that it doesn’t have that limitation. It knows everything that’s in the data and comes up with constructs humans might not consider. While these constructs are a far cry from becoming actual drugs, they do provide chemists a starting point, a “new white space,” to develop new drugs.
And there’s the game-changer. This could massively change the productivity of the workplace, enabling people to spend their time on more interesting and valuable tasks. Now, isn’t that a picture worth painting?
