5 Things Big Pharma Can Expect from the 2020s / Episode 13 - The Medical Futurist

The global revenue of the pharmaceutical market is 1.2 trillion dollars. With such capital at stake and with the pace of technological disruption, the pharma industry has to embrace new technologies, therapies, and innovations and put a greater focus on prevention and digital health.

In this video, we take a dive into the five trends of how big pharma will adapt to these changing times:

1. Artificial intelligence for drug research and development
2. Patient design - DIY medicine movements
3. In silico trials to bypass in vivo clinical testing
4. New technologies, such as blockchain, in the supply chain
5. New drug strategies by big pharma companies

Read our magazine for further updates and analyses on the future of healthcare:

#pharmaceutics #digitalhealth #pharma

[Biomeducated]

This is a fantastic video! Really eye-opening, and triggering me to urgently start redirecting my skills! Love, simply LOVE your channel and content!

[koralite]

i believe technology will bring hospital to the patient's bed at home. A lot of big machines in hospitals are bulky and outdated. we should harness a.i and genomic analysis and cloud computing to prevent and reduce cost.

[eranimisrael]

Excellent video . In the field of pharmacovigilance and the use of Real-world Data, AI will be key to use many different sources to have a better risk benefit profile

[aaimaayub]

Hi.. I have an extreeemly urgent question: Do artificial or bio-artificial organs come under pharmaceutical industry?

[sanjaybhat]

Hi thanks for the wonderful videos.
Can you pls suggest which are the free sources/trends to get healthcare market market share nos countrywise

[elianasmith]

Hello, Please continue to post such an informative and creative videos. Therefore, people like us will be motivated and learn in real life.

[saumyasingh]

Thank you so much for this video😊... This video is really gonna save my future.

[squamish]

You started this channel just five years ago, and then a once-in-a-century pandemic struck with incredible virulence and disruption.

One silver lining is that it gives you an amazing opportunity to witness and comment on how all the trends you have talked about are interacting with the challenge and which ones have been pushed into evolving rapidly during this difficult time. Some, I think, will have moved forward by a decade or so in just a few months!

[catvisiontv]

And how do you know if AI is not corrupt?

[nabilahbharuddin]

Hello, I wanna ask if is there any new reasearch (in 10 years) from 2010-2020 about application enzymes in pharmaceutical industry?
I'm doing school task which is need to find application of enzymes in pharmaceutical industry, latest in 10 years. I hope you can help me. Thank you :)

[carewow]

What the substitute available of sutures use during surgery in future

[shresthitripathi]

Sir can you please post a video about the sectors of pharma companies that would show more employment opportunities in the coming future

[jasonzhong]

how about orphan drugs and customized therapies for small patients population

[ricardodsavant]

I enjoy old school meds like cannabis and magic mushrooms.

[Repz]

The Medical Futurist = Show future healthcare
Two Minute Papers = Give insight on AI future

Both have PhD in there field.

[tamarabartolo]

Yes I agree that pharmaceuticals will need to evolve to be more patient aware through the help of AI Technology but will their greed of making the most money be a negative for the patient?

[scientifico]

Everyone is now trying to push this idea of "applying AI for industry X" to cut costs. But many forget that the AI adoption might actually turn out to be not very much less expensive, than doing a regular discovery process. You just open a whole new can of worms. Certainly, this technology will change usual way of things in R&D, but the actual costs might not be as low as many would imagine, AI is one of the most expensive technologies in terms of talent cost, for example. And if you try to save some budget and hire less expensive (so less skilled, talented etc) AI engineers -- the result might not be very innovative, as well.