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Surfing on the AI Hype cycle


I occasionally contemplate where we are on the hype cycle with regards to AI and Pharma. On one hand- the companies developing the tech stack of tomorrow are mesmerized by the amounts of data Pharma produces, and can do wonders with this data (and already do!). On the other hand- their clients- the Pharma companies, are risk-averse, heavily regulated, and… well, its hard to admit but when it comes to Data technologies- are not very tech savvy....


So how do we bridge the gap? Well, its always easier to build bridges between smaller gaps- so I suggest we all take a step towards each other:


Tech companies- please bear with us! and help us IMPLEMENT your systems. I see so many awesome startups struggle with onboarding new clients. The typical SaaS model might not be right for us. Your end-user, be it a scientist, a production engineer, quality or regulatory affairs professional- whoever it is- believe me, they are VERY busy at the moment- and the barrier they face with adopting your system is not only the time it would take to transition. They will need the mental capacity to learn a new language, re-structure their current context and connect with all the other moving parts in the company. This is an overwhelming task to say the least.


Pharma companies (especially you- Startups!), don’t miss on the opportunities of big data and AI- we are still at the beginning, and as I said- we don’t know where we are on the hype cycle, but I truly believe we will see the statistically significant knowledge-leverage and risk reduction digital technologies bring in the very near future. And if you don’t believe yet, take a look at what FDA is already doing (link below)…. So in spite of all the other urgencies- take your data and knowledge game a step ahead- it will cost you money and time, but its well worth it.


If I were on the Tech side (and I’m not, so forgive me if I have no clue): I would include in my business model a solid Hands-on implementation offering. I imagine a person that knows both worlds- the Tech and the Pharma, and facilitating (to varying degrees of involvement) with the actual implementation barrier.


Yes- that would probably make the entire thing more expensive- but did I mention that Pharma usually has very deep pockets? Or to rephrase: the costs in Pharma are so high, that the typical Tech stack is a real minor expense. Adding a fixed implementation service in my opinion would make things much more realistic for all sides.


And to go back to the AI Hype cycle for a second- I still don’t know where we stand - but if someone could please train an AI to do this initial implementation for us, that would be great. Thanks!


 

I am happy to share with you daily leaves from my personal tree, which revolves around Pharmaceutical Development, CMC and Beyond!


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