The pharmaceutical industry has faced enormous and unprecedented challenges in this period, affecting the lives of all of us. It is a huge and elaborate industry that ranges from large multinationals to small pharmacies. And today we can say it: on the whole, it has responded to these unprecedented phases of emergency with excellent responsiveness. And it continues to do so.
How was this possible? Of course, there is no single answer.
The reasons are varied and multifaceted; the commitment of all players in this industry has been enormous. But we have one certainty: this rapid and effective response would have been impossible without Digital Transformation, a revolution that was already underway at all levels in this industry.
When we talked about advantages and applications of Big Data in this sector, we started from the basics of the digital revolution: we focused on big data and its application in the pharmaceutical sector. If big data is the fuel, Artificial Intelligence is the central unit that sets change in the pharmaceutical sector in motion, making the “machine” more and more efficient every day. As you can understand, the two aspects are intimately related.
And it is precisely on the topic of artificial intelligence in pharma that we dedicate this new post.
What do we mean when we talk about AI?
AI, artificial intelligence: a buzzword on everyone’s lips, which is often waved around like a slogan, only to lose its concrete and operational meaning.
So let’s start by quickly defining the boundaries of this vast field, relying on some definitions provided by Accenture.
First of all, it’s important to underline that artificial intelligence is not a single technology, but “a set of different technologies that interact to enable machines to perceive, understand, act, and learn with human-like levels of intelligence” (Source: Accenture).
Proceeding in our analysis, two types of artificial intelligence can be distinguished:
- Restricted (or weak) AI: the most common in our daily lives, which concerns specific areas of action, related to single tasks that are often very consequential. In this type of application, the primary goal is to increase the efficiency of all processes.
- General (or strong) AI: here we are in a wide and ever-changing field, the one that concerns computer systems capable of “thinking” strategically, abstractly, and creatively and “with the ability to manage a series of complex tasks”.
Let’s put it right out there: applications of artificial intelligence in Pharma involve both sides. These applications are many, some are intertwined with processes that concerns other sectors to which Pharma is connected, they are constantly changing, and this cannot be the place to offer a complete and exhaustive overview.
Here is an eloquent figure: about 50% of Pharma and healthcare companies will implement artificial intelligence strategies by 2025 (Source: pharmanewsintel.com).
And here’s a fundamental clarification: implementation of AI systems does not mean replacing humans with “machines”. On the contrary, we are talking about an increasingly close collaboration in order to really put the human being, the patient, at the center of everything: in short words the Customer Experience. This is the key point that should always be kept in mind!
In the continuation of this post, we have isolated 4 macro-themes that cover very different but interconnected areas. In this way, we want to offer the reader the broadest possible overview of artificial intelligence in Pharma: a starting point for further investigation.
1. Smart Factories and new logistics
The Smart Factory is the basic unit of what is often referred to as the Fourth Industrial Revolution, or Industry 4.0. A process that – of course – affects all industries, not just pharmaceutical.
To put it briefly, it’s about bringing digital transformation to manufacturing plants, increasing connectivity between machines,through IoT (Internet of Things) systems and implementing data analytics, machine learning, and all the data-driven dynamics.
The goals and benefits?
- Maximum control over processes
- Optimization along all production chains
- Significant increase in productivity
- Increased safety
But that’s not all: Factory 4.0 is the breakthrough needed to reduce time to market, responding to the challenges of an environment that demands maximum responsiveness with rapid, scalable, flexible responses. Think about it: that’s exactly what’s been needed in this time of healthcare emergency.
Finally, there is the huge issue of logistics and distribution. This is another delicate issue for Pharma, which needs a capillary distribution network that is fast and able to react to stress quickly and in an automated way. All of this must be done without imploding and while maintaining a complex scale of priorities (just think about the difference between the distribution of urgent and ordinary drugs, of the issue of perishability, or of requests that can proceed in waves, sometimes unforeseen, with all the complex consequences).
Once again, in this field the only possible answer comes from digital technology and artificial intelligence systems capable of processing a huge amount of different data and inputs, transforming them, in a very short time, into effective and functional outputs and decisions.
2. A boost for the research and development front
On the Research & Development front, we have already dwelt on the subject of big data. Once again, the starting point is the collection and analysis of information. The point of arrival is the ability to interpret and make these analyses operational. And this is precisely what artificial intelligence must do in the Pharma sector.
How does this translate?
- Reduced timelines for new drug discovery and development.
- Efficiency in recruiting volunteers for clinical trials, both in terms of timing and in identifying the most suitable profiles.
- Identification of new therapeutic combinations.
- Support for screening and diagnosis.
- Increased quality in the final pharmaceutical product.
- Increased safety.
- Reduction of costs and waste.
- Possibility to quickly recalibrate research and development based on the interpretation of early results.
Clearly, we’re talking about a vast set of factors of utmost importance. And the point to always keep in mind is that the application of AI systems has a huge beneficial impact on all of these simultaneously. What is triggered is a powerful virtuous cycle.
In 2020, the news of the first drug made entirely with the support of artificial intelligence was released: it’s the molecule DSP- 1181, developed by the startup Exscientia in collaboration with the Japanese company Sumitomo Dainippon Pharma, for the treatment of obsessive-compulsive disorder.
In just 12 months, they accomplished what would have taken several years with traditional methods (Source: europeanpharmaceuticalreview.com).
3. IoMT and therapy 4.0
The acronym IoMT (Internet of Medical Things) includes technologies and digital devices for the health and well-being of individuals, from smartphone applications to wearable devices, up to ingestible or implantable sensors under the skin. It’s another truly vast and expanding field, which we have already mentioned.
The consequence of all this is the improvement of therapeutic combinations, which become faster (even in real time) and more reliable. In addition – and this is a truly central aspect – therapy is becoming increasingly personalized. This is a real breakthrough that takes the name of “precision medicine” (Source: Medline Plus).
Moreover, the combination of IoMT and artificial intelligence is – and will be – a formidable support for everything related to prevention: from cancer pathologies to mental health or neurodegenerative motor problems.
Finally: not only prevention. Thanks to IoMT, it’s possible to establish a more frequent and close interaction with the individual, who will thus be more inclined to monitor and possibly modify harmful behaviors and habits, over the short or long term.
4. The patient at the center: pharmacies and the new personalized digital communication
We started with factories 4.0, we moved on to the big numbers of R&D, then to IoMT and to increasingly tailored therapies…and here we are finally tightening the circle on individual people, individual patients.
Even in Pharma, the path must always be from digital to physical, from big data to relationships with individuals. And the first line of these relationships is constituted – without a doubt – by the pharmacies scattered throughout a territory.
The application of artificial intelligence systems in Pharma also concerns this network that is so intricate and part of our daily habits, in an increasingly important way.
Even in the “small world” of the pharmacy, the implications of AI are multiple and fundamental. There is the optimization of the pharmacist’s work. There is the improvement of warehouse and order management. And above all, there is the attention to customer satisfaction. This last point, in particular, is decisive. And it translates into the need to accompany and integrate the traditional side with the digital side.
In concrete terms, then: starting from the digitalization of CRM (Customer Relationship Management) systems, to build a new automated, always-on and personalized digital communication with the individual patient.
Here’s an example. By relying on companies like Doxee, you can start from the data collected in your CRM to produce effective, functional, engaging digital communications like personalized videos: videos that adapt to the characteristics of individual recipients and their browsing choices, in real time and in an interactive way.
In this way, a one-to-one dialog is also built in digital mode, useful for facilitating purchases or requests for advice and consultancy.
This dialog integrates with the physical one. And the two aspects, finally, reinforce each other, with benefits for everyone: from companies, to pharmacies, to patients!
