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Dmitry Kaminskiy Presents at GSK's 2018 Hub in a Day

On May 2 2018 Dmitry Kaminskiy spoke at Glaxo Smith Kline's 2018 Hub in a Day event on how the intersection of AI, Longevity and Precision Medicine are poised to disrupt the BioPharma Industry.


He also touched on how advances in biomarker monitoring combined with developments in digital health, wearables, IoT, and mHealth sectors could enable close to real-time personalised therapeutic testing, adjustment and validation within the next 3-5 years. Furthermore, he also made the connection between individual, personalised, real-time reaction and the pressing need for BioPharma corporations to reinvent their business models and operating structures in order to become real-time reacting entities themselves.


Considering the accelerating progress in the sphere of AI for advanced R&D, biomarker development and drug discovery in recent years, it is obvious that in the next 5-10 years there will be significant shifts from treatment to prevention. However, the convergence of these emerging technologies can even further accelerate the dynamic of the progress and shorten the timespans associated with even very bold predictions.


AI in conjugation with mHealth, IoT, Blockchain, Digital Health solutions will bring multiple tools to transform BioPharma operating procedures and science AI-driven consumer-oriented solutions with a significant shift to preventive medicine, not only on the technological side, but also on the side of BioPharma and Healthcare corporations business models as well.


Leading IT-giants are already in most cases data-analysis driven corporations. The case will be the same for healthcare companies 10 years from now. Taking into consideration the significant recent developments in biomedicine and AI, the health-adjusted life years (HALY) that companies can add to their users will become a reliable basis for their valuation. The BioPharma companies of the future will have to become the mathematical corporations driven by data science, AI and quantitative health parameters like HALY. At the same time, given the increasing interest of IT-giants such as Google, Amazon, Apple, Tencent and Alibaba in healthcare, we can expect that in 10 years’ time they themselves will become global healthcare corporations and their capitalization will eventually depend on measurable and quantifiable parameters associated with HALY they can provide to their users.


If BioPharma wants to survive the coming disruption of their industry by AI and data-driven medicine, they will need to be capable of embracing and absorbing change in the manner of the IT giants of today, and to allow themselves to be driven not by the validated paradigms and operating procedures of yesterday, but instead by the quantitative technological changes of today, and most importantly that it is in their power to do so, provided that the industry commits sufficient will and proactively allocates and optimizes their resources and efforts in order to do so.

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One of the main existing obstacles in sphere AI in Healthcare is the lack of advanced data scientists on a global scale and strong AI specialists particularly in the niche of AI for Drug Discovery and advanced R&D. It is notable that on average AI companies consist of 55% administrative staff, 30% biotech specialists and only 15% of AI specialists.


At the same time, the UK is one of the most active spots specifically for AI in Healthcare. It is home to many AI companies and a lot of activities are progressing here, including government support with very clear interest in this topic. Therefore we can predict quite a good future for further positive progress of this industry in close coming years in the UK, and GSK most likely will be able to maintain leading positions in this arena in the UK, and also one of the leading positions on the international level.


Kaminskiy also spoke on several main conclusions to come out of Deep Knowledge Analytics report on the AI for Drug Discovery, Biomarker Development and Advanced R&D industry landscape, noting most relevantly that a large number of aggressive Chinese investors and companies are emerging to acquire increasingly large stakes in the AI for Drug Discovery sector, and are in some sense now leading international developments in this area ahead of the UK and USA. Today's BioPharma giants are rapidly approaching their “Kodak moment” without even realizing it, and should consider their main competitors to be not other BioPharma corporations, but rather IT-giants generally and Chinese IT-corporations specifically. It is reasonable to predict that in 10 years' time there will be no BioPharma corporations as we know them today; instead, there will be advanced healthcare companies driven by data science and AI and providing preventive rather than reactive medical care, increasingly taking the shape of “mathematical corporations”.

He also, however, noted that there is good evidence and signs that GSK in particular recognizes this issues and already developing its long terms strategy accordingly to these key points. GSK is among the most progressive BioPharma companies due to their willingness to adopt and on-board emerging AI for Drug Discovery technologies into their core R&D (even to the point of launching an entire AI for Drug Discovery division), which puts them in a better position to make the necessary transition from BioPharma giant to data-driven, AI-enabled healthcare corporation than many of their competitors. Nonetheless, IT and tech corporations remain the most active players in this growing industry, and BioPharma corporations like GSK, despite making excellent first steps towards prioritizing AI in their internal operations, should become even more proactive in committing to the potential of AI for drug discovery, biomarker development and advanced biomedicine if they wish to remain relevant and profitable in 10 years’ time.

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