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Enabling patients to get innovative treatments faster through machine learning at GSK
Posted on November 13, 2018 at 4:34 pm
This article explains how GSK is using machine learning to increase R&D productivity and accelerating drug development timelines.

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Masato, thank you for the great article! It is fascinating to read about Mitsubishi and all the markets they are playing in. I am wondering if this process of open innovation would work as well in the US. My feeling is that employees in the US – if they have a great idea – would just leave the company and start their own venture. I would be curious to know why MC employees stay and start their businesses inside the Conglomerate. Is this for financial safety reasons? Is this by loyalty for the company? or is this another reason?

Fascinating article! I really enjoyed reading about the implications this might have on the labor market long-term. I agree that the need for talent might be reduced at tech giants – such as Alibaba – as a consequence of open innovation and increased reliance on freelance developers. However, I think this is a great way to foster innovation as this might encourage developers to start their own ventures and build other apps. And this works perfectly in a growing and healthy economy. My only concern would be to ensure that the labor market has the right mechanisms to protect freelancers in a case of an economic downturn.

Fascinating article, Ti! I really like your observation that AM is critical for J&J by enabling faster and cheaper production. I am wondering what will be the implications of that technology beyond developed markets but also on market dynamics:
+ For emerging countries: Will that enable emerging countries to get greater access to medical devices? or will J&J – and other players – focus more on innovation instead of reducing costs therefore limiting the impact on patients in developing countries?
+ For market dynamics: Will that foster greater competition in the medical devices industry by lowering barriers to entry? or will the impact be limited given the number of regulations to launch a new medical device?

Thank you Justin for this article on a great French company! You shed light on a topic that I was not too familiar with. Because Bouygues is a conglomerate I am wondering if they could use additive manufacturing in some of their other businesses. In fact, beyond Bouygues Construction they also have a real estate, a rail road and a telecom / media businesses. My question would thus be can they start using AM in these other businesses and will it also be a source of disruption in these other markets?

On November 15, 2018, Maxime commented on Beating the Beast :

Such a fascinating article! Even though it seems like they have a great plan to use machine learning, I’m wondering about the Loblaw’s ability to compete with Amazon in the long-term on pure technology. From a human and financial capital I think it will be tough for them.
However I’m thinking that, in the long term, they might be better partnering with a technology company (e.g., Google) whose core competency is AI/ML to develop ML applications and focus on their sources of differentiation (e.g., service). That way, they would spend their time on things that differentiate them. The drawback of that approach is obviously that they would become very dependent of the technology company they partner with.

On November 15, 2018, Maxime commented on Chasing Medicare Fraud with Machine Learning :

Great article, Christine! Using machine learning to detect fraud in medical billing raises some ethical questions. On one hand, Medicare focus should be on making the best use of the taxpayer money and reducing unnecessary costs. However, on the other hand, I am worried about overlying on machine learning to detect frauds. What would happen in the case of a false positive (detected as a fraud but honest medical expense)? Would that lead to patients that get their treatments covered anymore? I think the use of technology is effective – and needed – to control rising medical expenditures but human oversight should be preserved to ensure coverage for all ‘honest patients’.