Insights"Real-world data is more useful than clinical trials"

"Real-world data is more useful than clinical trials"

For the CEO of Almirall Pharmaceuticals, Peter Guenter, there is no doubt that personalized medicine is the top priority of his industry. To achieve this, he relies on big data and IA, and on collaborating with start-ups to learn from their findings and their way of innovating.

Although precision medicine has not yet delivered on its promise to offer personalized drugs for each patient, Almirall's CEO, Peter Guenter, believes that an alliance between homogenized data analysis and artificial intelligence (AI) will be able to do so. For the manager, this will be the ultimate recipe for optimizing time, costs and results in both trials and clinical developments.

Guenter, who has accumulated decades of experience in the pharmaceutical sector, has led the Catalan group since 2017 on its consolidation journey as a global company specializing in medical dermatology. In this way, the person in charge has resorted to collaboration with the innovative ecosystem to promote research, but also to transform the internal culture of the corporation and turn it into a more agile and enterprising environment.

Each year, MIT Technology Review publishes a report on the 10 technologies with the greatest potential to change the world. One of the highlights of the 2019 list is the prediction of premature births, capable of finding common traits in the RNA of future babies that indicate a high probability of reaching the world early, demonstrating the trend to apply data in medicine to prevent rather than cure. What do you think of this trend? How is the sector in general and your company in particular adapting to it?

At Almirall we believe that data will be of paramount importance in order to remain at the forefront of innovation. Until 15 or 20 years ago everything worked through trial and error, and sometimes, with luck, you got it right. The traditional model used to launch a product for a group of patients who had suffered, for example, a myocardial infarction.

They were given an antithrombotic treatment that, in theory, would reduce their risk of suffering a new episode. But what happened was that some patients responded well to the treatment while others did not, and we could not determine which group they belonged to until they suffered a second heart attack.

This is where new technologies come in. What impact does data analysis have on pharmaceutical companies?

Right now, the main concern of healthcare and pharmaceutical companies is that we want to offer personalized treatments for each patient, even if we haven't reached that point yet. And the better we use the data, the more we will be able to have patient-specific pharmaceutical approaches.

Of course data analysis will also have an impact on the pharmaceutical value chain, but the big focus is on research, on how to discover new medicines, precision treatments.

"The main concern of the pharmaceutical companies is to offer personalized treatments".

In recent years, Almirall has redirected its strategy to consolidate itself as a global group focused on skin health. In a data-driven world, how could the risk of each patient suffering from a skin condition or anticipating a drug reaction be calculated?

Let's take as an example the atopic dermatitis, eczema. There is a widespread belief that it is not a serious problem but severe eczema is an incredibly debilitating disease that prevents a normal life. Now there are new treatments that modulate the immune system, and although they are fantastic, they only work in 50% of patients. In this context, predictive data analysis can help determine the effectiveness of a drug.

Why is this important? Firstly, because you avoid exposing the patient to a potential side effect and, secondly, because of the costs. You are only going to give that treatment to patients who are going to respond positively, and this is an example of how data analysis is incredibly important in optimising medical treatment for patients with serious illnesses.

In addition to shortening research times and optimising costs, what impact does data analysis have on clinical development?

From the first time you experiment with a product until you put it on the market, we can be talking, depending on the disease, about five years to eight years, and billions of euros. So, if we can somehow spend less time and money on clinical development, the price of the drug on the market will be more affordable.

In medicine we do serious things, we are talking about improving the lives of patients, saving their lives. So we can't go wrong, or at least not that often. One of the main problems we have with big data analysis is lack of homogeneity. We should not underestimate the challenge of cleaning up these data.

How would it be possible to reduce the gap between a clinical trial and tracking drug use data in the real world?

A clinical trial is conducted with a specific population group, in certain academic centres and with doctors who are accustomed to doing it under the highest standards. But the product is used in real life, and you can't exclude a patient with diabetes or any other insufficiency, who is 75 years old or taking another medication, and you can't prevent the drug from not being given as prescribed.

"Knowing how drugs are used in the real world is what really matters."

Therefore, real-world data are much more useful than clinical trials. I'm convinced that knowing how drugs are used in the real world is what really matters. I think the answer will be to collect that big data, homogenize that data, and find a way for artificial intelligence algorithms to eliminate bias.

New technologies have favoured the entry of other companies into the sector. How important is knowledge transfer and collaborative R&D for your company?

First of all, I have to acknowledge my respect for the in-house researchers, I think we have people of the highest quality; but of course it is a bit of an illusion to think that they are the only ones who are going to discover something revolutionary. The more people research new pharmacological profiles, new markets, new molecules, the better. And, of course, the possibility of widening the scope of findings outside the home is multiplied.

What can you tell us about AlmirallShare, the company's open innovation platform?

We are open to any collaboration, whether with academia or with young biotech companies. In short, potential partners. It is working really well, we have already received many proposals to make a good selection in the second wave of the program.

In addition, we have teams on the US West Coast and in Asia that track and evaluate all relevant scientific advances that could have applications in medical dermatology. When we find something that might interest us, we contact the company that owns the idea and propose a collaboration model at a very early stage or after clinical development.  

The future of work is moving towards a labour market in which digital employees are becoming increasingly important. How does this trend affect the pharmaceutical sector?


A lot of interesting things are already happening in medical dermatology. For example, we know of a Dutch company that has managed to prevent 200,000 cases of melanoma thanks to an early detection system that exploits the sharpness of smartphone cameras in front of the human eye. It is an example of how big data analysis combined with a suitable algorithm can be applied to interpret the information and determine if there are indications to conclude that there may be a melanoma.

Of course, you always have to go to the dermatologist, human intelligence always comes into play, but the process is optimized if you have an artificial intelligence that can report with 100% reliability on whether there is something to worry about or not.

Digital transformation is another key effort in a company's innovation strategy. Where is Almirall?

When I arrived in Almirall in September 2017, there was a lot to do, and in 2018 I began to reflect on what the digitization of a company like Almirall should be like. In terms of size, we are a medium sized pharmaceutical company focused on dermatology, so we had to set a realistic agenda. First, we created a Digital Board and our external advisors helped us map out our digital transformation roadmap, on-board talent, facilitators, and so on. In the first three months the initial work was perfected and now we have a Digital Agenda that will be launched from the Digital Office, born last February.

Incorporating new teams and lines of work requires a change in the culture of the organization. How can a message be transmitted to the teams?

The collaboration with the start-ups with which we develop solutions is very positive. Their way of working, thinking, experimenting and testing, that culture of entrepreneurship, ends up impregnated in the dynamics of Almirall.

I want Almirall's corporate culture to change. And I think we're on the right track to move from being a relatively conservative typical pharmacist to an entrepreneurial company where teams work less hierarchically and there are no structures. From this process, I hope to achieve a growing cultural benefit.

"A CEO must demonstrate to the team that senior management is committed to digitization.”

What is the CEO's role in leading transformation in your organization? What capabilities do you think a leader should have and what advice would you give to other managers?

One cannot be a specialist in everything. A CEO who wants to carry out a digitization process like the one we want to do at Almirall must demonstrate to the team that senior management is committed to digitization.

In a company the size of Almirall, which does not have the resources of the big pharmaceutical companies, the additional challenge is to try to make the right decisions as soon as possible. The key message is to engage the company in an act of faith even if we don't have all the answers yet. If the pharmaceutical industry wants to remain relevant, not today but 10 to 15 years from now, it must make decisions to transform it now. Otherwise, it will be too late.





Published by OPINNO © 2022 MIT TECHNOLOGY REVIEW spanish edition