The pharmaceutical market in the US has been growing steadily, and is projected to reach a value of USD $861.6 billion by 2028, with a compounded annual growth rate of 6.3%. To remain competitive in this rapidly expanding market, pharmaceutical companies must leverage AI to expedite drug discovery and shorten the time from initial research to market launch, ultimately improving patient outcomes and ensuring continued growth in the industry.
Irish companies are at the forefront of AI and drug discovery, and it’s no wonder why. The Irish lifesciences sector is a powerhouse, exporting over €45 billion annually and employing over 50,000 people directly. In fact, Ireland comprises 15 of the world’s top 25 medtech companies, 8 of the world’s top 10 medical device companies, and 18 of the world’s top 20 pharmaceutical companies.
As the global pharmaceutical industry continues on the path towards further digitization, looking towards technology like AI can help to impact the efficiency areas that may not be universally known to need such innovation — such as in the areas of drug research and development which can take over a decade to complete.
This is where AI shines. AI programs, when properly implemented, can offer benefits such as significantly reducing the time that it takes to develop these drugs, as well as offering digitally identified treatments for diseases that humans have yet to cure. Particularly in drug discovery, the amount of data produced at each stage can prove astronomical. AI can demystify this data at a quicker pace than previously possible – reducing the overall process exponentially.
ICON, for example, uses AI to speed up patient recruitment, site selection, protocol optimization, and clinical trial design. By leveraging machine learning algorithms, ICON can identify eligible patients for clinical trials more efficiently, increasing the speed at which clinical trials can be conducted. This leads to faster drug development, which ultimately benefits patients who may receive life-saving treatments sooner.
Teckro uses AI to automate protocol analysis and document management, providing real-time data insights to clinical trial teams. This enables teams to make more informed decisions, and helps to reduce errors and streamline processes. By automating these tasks, Teckro can reduce the time and resources required for clinical trial management, enabling more efficient drug development.
A second positive benefit of the implementation of AI technology is its potential to both reduce drug development timelines, as well as identify treatments for diseases humans have been thus far been unable to cure. An example of this is Irish company Nuritas, who use their proprietary ‘Nuritas Magnifier’ AI tool to automate the discovery of unique bioactive peptides, biological molecules normally buried in the structure of parent proteins who become active after the cleavage of the proteins. The discovery of these peptides can have potential anti-inflammatory, antimicrobial, and even anti-cancer effects. Another Irish company, Deciphex, utilizes AI to enable pathologists to drive high-quality, efficient reporting, which allows for both accelerated drug development and enhances the existing standard of care patients are under.
These successful companies are just a few examples of the many benefits that can be utilized through AI to positively disrupt the existing norms of the pharmaceutical industry. And AI is certainly not the only way the industry can be digitally disrupted for the better, either.
For example, pharmaceutical company APC uses machine learning to predict and analyze the behavior of molecules during drug development, enabling the identification of the most promising drug candidates. This reduces the time and resources required for traditional trial and error methods, where researchers may need to test thousands of molecules manually. APC’s machine learning-driven approach can help identify potential drug candidates more quickly and accurately, potentially saving years of research and development time.
It’s important to note that AI is not without fault. AI systems, like any other software, are vulnerable to cyber-attacks that can compromise the confidentiality, integrity, and availability of sensitive data.
One significant risk associated with AI in drug discovery is the potential for data breaches. The amount of data generated during drug development and clinical trials is vast and sensitive, containing confidential patient information and intellectual property. If this data were to fall into the wrong hands, it could be used to create counterfeit drugs, harm patients, or give competitors an unfair advantage.
In addition, there is also a risk of bias in AI algorithms. If the data used to train AI systems is incomplete, biased, or unrepresentative of the population, the resulting algorithms could be similarly biased. This could lead to incorrect drug recommendations for certain groups of patients, potentially causing harm or limiting access to effective treatments.
To mitigate these risks, pharmaceutical companies must implement robust security measures and follow best practices for AI security. These measures include securing data storage and transmission, regularly testing systems for vulnerabilities, implementing access controls and user authentication, and training staff to recognize and respond to cyber threats. By prioritizing cybersecurity, companies can ensure that AI-powered drug discovery remains secure and effective.
Allowing for digital optimization in necessary industries, such as the pharmaceutical industry, especially through collaborations and partnerships with foreign entities like Ireland, can lead to both positive growth and meaningful collaboration. By expressing a willingness to collaborate with companies in other countries, U.S. industries and businesses can optimize their ability to cater to the needs of customers and keep up with the demands of an ever-changing global marketplace.
Jennie Lynch
Jennie Lynch is the Senior Vice President of LifeSciences, Enterprise Ireland, based in Boston, Massachusetts. Jennie focuses on the medtech, pharmaceutical, and healthtech sectors and supports Irish companies targeting these sectors by providing insight regarding market opportunities, facilitating connections to key contacts, and forming strategic partnerships in the US. Prior to Enterprise Ireland, Jennie worked within the consultancy sector in the US, advising large companies on technology trends and identifying opportunities for expansion. Jennie studied Strategic Management at Harvard University, has an MSc in Biotechnology and Business from UCD Smurfit School of Business, and a BSc in Molecular Biology from UCD.