The pharmaceutical and healthcare industry, along with the food industry, is one of the largest and most advanced sectors in the world, making it more willing to integrate new disruptive technological elements.
Like all industries around the world, these sectors have been affected by digitization and technological advances. Digitization especially has transformed healthcare in a big way thanks to technologies such as Big Data and Artificial Intelligence. The use of these for advanced data analytics has greatly facilitated both the processing, as well as the case of analysis of huge amounts of patient-generated information. The implementation of these techniques in healthcare will allow the transformation of the way we diagnose, as well as personalize treatments, help identify risk factors and, in general, improve the results and productivity of the healthcare sector.
In this article we will focus on the potential of Artificial Intelligence, and in particular on Generative Artificial Intelligence, in these sectors.
Covid-19 Accelerated Generative IA
The outbreak of the COVID-19 pandemic put the healthcare sector on edge around the world. It was necessary to develop fast and effective solutions to curb the health emergency that for more than three years swept the entire world. In this context, the development of technologies such as Generative AI was positively impacted.
In the work environment, all companies had the need to implement other ways of working than face-to-face, as the whole world was quarantined. In the social sphere, people had to invent new ways of meeting their loved ones, most of them through the Internet and a screen. On the health front, diagnostic tools had to be adopted quickly to detect the virus. Some of these tools were powered by artificial intelligence. This, along with many imaging systems needing greater accuracy, helped drive market growth.
One example of the advances that were achieved through Generative AI research was carried out by teams from Oxford University and IBM. These scientists teamed up to deploy a method of developing a new class of antivirals to tackle the virus based on Generative AI. Generative AI had the ability to process massive amounts of data and generate new insights that would enable the creation of new molecules not currently found in nature that could be used to support new drug discovery. Ultimately, the team came up with 4 potential antivirals for COVID in much less time than it would have taken if they had used conventional methods. This not only helped in the face of the pandemic experienced in recent years, but also helps us to be prepared for possible future pandemics.
Pharmacology
Generative AI is being used in the pharmaceutical industry to reduce the average cost of producing a drug. This is a process that goes from drug discovery to commercialization and can amount to billions of euros. Only one third of this money was spent on discovery costs, and this is the longest phase of the process (3 to 6 years on average). The drug discovery process is becoming increasingly complex and requires advanced tools and techniques.
It is also helping to reduce the time of this process, designing drugs in just months, a considerable reduction of the average discovery time. For the pharmaceutical industry especially, this means major changes in reducing costs and time.
This technology also addresses this process by analyzing large amounts of data, extracting complex patterns and even generating new molecules with the desired properties. In this way we can extract the most relevant information quickly and efficiently, automating and streamlining the process involved in data analysis.
Clinical trials are also accelerated and improved thanks to Generative AI, and can help researchers design more effective clinical trials by predicting and identifying which patients will be most likely to respond to a particular treatment. This would allow clinical trials to be faster and smaller, reduce costs, and bring new therapies to market faster. Medicine would be much more personalized and tailored to patients’ characteristics, and treatments would be more effective.
Thanks to Generative AI, drug discovery becomes a more efficient and cost-effective process.
Healthcare
Promising benefits are expected from implementing Generative AI in relation to improving the clinical experience for patients. Early successes of this technology in healthcare are being shown in different use cases.
Healthcare is one of the industries with a large amount of data, and an increasing demand for automation in its processing. Generative AI looks set to mark a before and after in advances in precision medicine. This technology would help analyze doctors’ notes, medical images and other unstructured data. Thanks to this analysis, recommendations could be developed not only for diagnosis, but also for treatment.
Generative AI can also share medical advice and data-driven information, making patients have greater access to knowledge about their health status. It would improve physician experience by automating administrative tasks such as writing referral letters or clinical coding.
With the use of Generative AI we can obtain accurate and confident diagnoses favoring decision making. These techniques can also be applied to work in preventive medicine: thanks to the information extracted, we can anticipate the patient’s needs.
In short, Generative AI is transforming the healthcare sector and bringing technological advances to ensure a positive and enriching future for the industry.
Image: Unsplash | James Yarema
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