The use of artificial intelligence (AI) and its machine learning subset in the healthcare and clinical trials spaces has increased significantly in recent years. These technologies can be helpful in discovering and repurposing therapies more quickly, efficiently and at a lower cost, as well as improving the design and recruitment process of clinical trials. Despite this, human employees remain vital to many companies’ operations, including those of healthcare and wellbeing specialists Euromed Pharma.

Pharmaceutical Technology spoke to Edo Madussi, managing director of Euromed Pharma US and business unit head of its Clinical Trial department, about the importance, advantages and challenges of working with real people in delivering development services and programmes for healthcare and wellbeing.

What is the importance of real people to the healthcare/wellbeing industry in an increasingly tech-driven world?

I think that in an environment where the competition has become numerous – specifically in the clinical trials [sector] in which several players have been developing good technology to advance innovation rapidly – there is one element that, in my mind, will never change, and that will always remain the differentiator between organizations that do what we do: people. In a world where we can extrapolate information and try to come up with assumptions and do analysis based almost [entirely] on artificial intelligence run by computers, hiring and putting together a variety of different minds and backgrounds in a clinical trials supply setting will help make the difference because it’s going to be the connections to the external world that will make or break projects.

What are the main differences when working with real people as opposed to machines?

The basic one is that both positively and negatively, people are unpredictable. [With machines] you set up a proper algorithm and you have a certain data set, and you expect a certain result. You can almost anticipate [the result], and it’s then confirmed by the algorithm. With people, you can try to read a personality and character, but you never really know until you experience the outcome of a certain person or employee. In that sense, making the right choices and putting together the right team is critical for the success of any project, let alone an organization.

What characteristics, skills and experience do you look for at Euromed Pharma when hiring people for your operations?

In an industry where basic knowledge of pharmaceutical frameworks is a must, and so the tendency is to hire people that only have a certain pharma background, I try to go the opposite way, looking for talents with experiences also from other industries. I like to bring on board personalities who are sometimes coming from really different businesses, but within those industries, they have skills that are transferrable to what we do. In the clinical trials supply market, we have to be able to see the big picture not only from a patient or medicine perspective but also from a supply chain [business] one. Trials can take place on world levels, as we now know, their complexity in design and reach keep on increasing. Professionals in this business have to be ready to shift gears and suddenly change focus because new trials results are shifting priorities – and this has an impact on how supplies are arranged throughout the world.

I find it interesting, for example, to bring in people who have international logistics experience from other industries, or professionals from creative tech firms because they have developed critical thinking to be able to face constant change. Often, while developing supply chain strategies, it’s more helpful to have someone who’s less science-minded and more creative. Because if in a team everyone has the same experience and background it is likely to end with a biased outcome. The technical knowledge [pharmaceuticals] is of course required and the minimum level to start from, but the ability to think outside the box is something that can be easily from the outside.

Where do you tend to find the right people for Euromed Pharma’s operations?

If I had an easy answer, we’d probably be exceeding any expectations on the market! Again, maybe I sound redundant, but I believe people are the most important asset to an organization. For the same reasons machines have not been able to replace the human factor in business decision making, finding and selecting the right people is still an exercise that has to be done relying on other people. There are excellent tools now like LinkedIn and Indeed, several platforms where you can find job postings, but in reality, the better candidates I’ve found were within a network of recommendations or indications of a friend of a friend who knew someone who had a certain skill set.

Are there aspects of human knowledge or experience that can’t be replicated with machine learning?

Absolutely yes, I think at least until now – maybe in 100 years it will be different – in a critical situation, or when there is an issue – again going back to predictability – the machine learning will have limited resources to react to the situation. These limitations are of course in part caused by humans when programming the machines, but as of today, the human element in a crisis, will find and reassess the situation, find a creative solution that the machine wouldn’t be able to. The machine would always be looking at the same data sets and coming up with x number of results based on an algorithm. A [good] human would say, “You know what, let’s maybe change our data set, let’s reevaluate the starting assumptions and find a better solution for this problem.”

How would that look in a healthcare or wellbeing context?

When using forecasting tools, for instance, to assign supplies across multiple countries or when you run feasibility studies to decide which countries to file a clinical trial application, there are several assumptions to be made and various moderators that influence the expected outcomes. The forecasting model will use a very basic yet sufficiently complex set of criteria and come up with an algorithm and assumptions to establish “Okay, we’ll have to have 300 units of this particular product here, we’ll have to have 300 units there, we’ll probably need this type of buffer in re-supplies of the materials.” All these numbers come up off these basic assumptions in the forecasting model.

Well, say we have a situation like Covid, where suddenly the models and basic assumptions on which the algorithms are built constantly change because every other week, we have maybe countries that are closing and won’t allow people to go to hospitals, we have lockdowns, we have certain situations. That’s a situation in which currently only a human can be quick enough and ready enough to make a call on the spot and say, “This is what we’ll have to do.” Most likely, the result of the decision might not be as perfect as the algorithm would’ve come up with if we’d had the exact or correct assumptions, but at that moment, you will not have those assumptions.

How does Euromed Pharma manage the potential for human error in the development, trial and distribution processes?

Robust training. I think once we find the talent and have the right people, continuous training and development motivate and empower everyone. Allowing people to grow within the organization, and offering them growth within the actual knowledge of the industry, not only keeps people motivated but also ensures that, because they’re acquiring all this knowledge, they can also put it properly into practice. In turn, this allows individuals to be more mindful of their actions and the consequences that they have and normally reduces the mistakes and error rate. The more knowledge we acquire, the more we feel empowered, the more we are conscious of our actions. It’s a virtuous trend and a constant growth. In my mind, it is a win-win both for the organization and for every single individual [working there].

Does the use of real people in these processes slow things down at all?

It has the opposite effect. If you think about it, and depending on the scale of the operation – if we were to speak about commercial distribution on a global scale, I probably wouldn’t be saying this, but because of the particular industry we are in, in the clinical trial setting – things are done on a small scale and a quick basis, rather than on a large scale and [with] a systematic approach. So the human component, as long as it’s well-trained, actually allows [you] to increase the pace of certain things.

Is it easier to ensure full regulatory compliance when working with people rather than machines?

That’s where I think there’s a good bridge – the combination of both will ensure maximum regulatory compliance because we’ll be able to put certain boundaries within the systems and within the quality management systems that you apply. And then in training, individuals will know the extent to which they can operate and what-not.

Are the different backgrounds helping to market products and ensure they get off to a strong launch?

For us in this particular moment, certainly. As we recently opened an organization, having people – as I said before, even having people from different backgrounds and industries ‒ is increasingly excellent. It allows very steep growth in various directions. If the company was built off four pharmacists that had only done pharmacy all their lives, and that’s all they’d done, we would probably replicate a pharmacy.

By bringing in people who come from the commercial supply chain, logistics, international trade, laboratories, clinical development, clinical operations, we have built a strong variety. When we work together we learn through the cross-fertilization of these experiences. Maybe we can implement what has been used in the automotive industry for the transportation of small parcels also into the pharmaceutical [industry]. So it gives an interesting approach or outlook on how to do things and how to grow [our operations].

Are there any particular challenges in trying to coordinate people across departments?

As long as the goal of your organization is clear for everyone, and as long as the actual direction in which we are set to go is clear, I find that interaction is normally very productive. We are people and everyone has a different way of doing things, so there is a common understanding that everyone needs a good level of empathy to appreciate, you know, “I’m dealing with someone else who has maybe the same goal but wants to achieve it differently.”

In summary, if you invest in the right individuals ‒ finding creative and open-minded people that are willing to challenge themselves and to learn from one another – then the team will provide incredible results that are the sum of the individual’s experiences.