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The future of digital investments

The future of digital investments I Philippe Barillon is the Head of Insights & Analytics Europe & Canada, Takeda. 

At Eye For Pharma Virtual (Barcelona) Philippe Barillon spoke about investing in Digitization in terms of financial and process aspects. Barillon believes there are three main areas in Digitization that should be given top priority. According to him, R&D is probably one of the biggest areas. The opportunity to apply machine learning and agile ways of working can really improve the rate of success of R&D engines. 

The second area is customer experience, which is closer to what he does at Takeda. The ability to propose and to create superior customer experience is proven to actually make a big impact on customers’ willingness to partner with Takeda as an industry and trust in its products.

The third area is patient experience. In Barillon’s view, it represents a shrewd opportunity. The more you learn from the patient, the more you can reinforce your R&D and your customer experience. 

Regarding how R&D be altered so that digitization can be encouraged more and have a sustainable model; Barillon believes it needs to be combined with process for design. Digitization represents an initial investment on top of what is already an expensive engine in the industry. There is a need to evolve from a historical high-volume outcome that is our input-based paradigm to a high value outcome-based paradigm where higher prices can be claimed as superior outcomes.

On areas where civic investments need to be made, he said there is need to screen and analyze more molecule, more drug candidates faster and testing them against more and more complex models. This is so there can be identification of potential success and failures early enough in the R&D process.  With this information, the industry can either focus on them or eliminate those faster in order to avoid unnecessary costs.

When it comes to machine learning in the health and pharma industry, Barillon feels there are limitations. One of such limitations of machine learning is that as human beings, we like to understand what’s behind those algorithms and how do they generate this prediction. There is need to become more mentally agile in order to accept that these algorithms have an ability to process data in such a way that really goes beyond the ability of our individual brains. 

On the subject of whether or we’re entering an era where the potential to cure is actually higher, Barillon is positive.

According to him, there is need to realize that these patient populations certainly deserve the attention of industry and certainly deserve pharma future digital investments.  

Barillon believes on the one end, things will continue in the way of more cures being found. But on another end, when it comes to treating chronic conditions or pandemics, like what we have currently, we need to join forces and to understand where we are headed so we can all go together. This will enable the industry to bring curative medicine faster to the market than following traditional approaches

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