AI, Everywhere and also in Healthcare

Although Artificial Intelligence (AI) was conceived in the 1950s, its true boom has occurred recently, capturing the attention of society and businesses due to its transformative capabilities. This technology has permeated various sectors, optimizing tasks that previously consumed a lot of time or exceeded human capacities. In education and institutions, it has simplified administrative tasks. In manufacturing, AI-assisted robotics has reduced production costs. Real-time translation into different languages has become a reality, and even streaming platforms like Netflix use AI algorithms to suggest personalized content. And beyond ChatGPT, generative AI is opening doors to possibilities previously unimaginable in the world of design, music, and textual content, redefining what technology can achieve.

However, the real impact on improving the quality of life for people becomes more palpable in the field of healthcare. Here, Artificial Intelligence emerges as a revolution, potentially transforming the pharmaceutical and biotechnology industry, redefining how drugs are created, clinical processes are optimized, and new ways to enhance patients’ lives are sought. So much so that Big Data is expected to penetrate the healthcare sector more rapidly than other industries. In fact, it is estimated that the global Big Data in healthcare market will steadily grow at a compound annual growth rate (CAGR) of 36% until 2025.

Benefits and Applications in Healthcare

 

• Development of New Medications

 

The drug discovery process is long and expensive, with a relatively low success rate, and this has not changed in recent years. An analysis published by the Massachusetts Institute of Technology (MIT), based on data collected from the year 2000 to October 2015, revealed that only 13.8% of drugs successfully pass clinical trials. Furthermore, it is estimated that the average cost of developing a new drug to complete the entire clinical trial process and obtain FDA approval ranges from $314 million to $2.8 billion, and it takes an average of 10 to 15 years for regulatory approval, according to the PhRMA organization.

For these reasons, one of the most promising aspects of AI for the pharmaceutical industry is its ability to accelerate the development of new medications. Pharmaceutical companies are implementing advanced algorithms to analyze extensive datasets and anticipate which compounds could have beneficial effects in treating various diseases. These machine learning algorithms gather and group compounds with similar effects before passing clean data to researchers, who can decide how to leverage this knowledge in their work. This approach can enable a more precise selection of compounds for further research and development, potentially leading to a significant reduction in both costs and the time required to bring new drugs to the market.

 

• Personalized Treatments and Improvements in Adherence

 

Lack of medication adherence is a significant challenge in healthcare. AI is addressing this issue by providing innovative solutions such as applications to monitor patient compliance with medication administration, ensuring they take the right doses at the right time. This not only improves treatment effectiveness but also reduces costs associated with non-adherence. Accenture emphasizes this point, estimating that such clinical healthcare AI applications can generate $150 billion in annual savings for the U.S. healthcare economy by 2026 and projecting that the value of reducing dosage errors could amount to around $16 billion for the same year.

 

• Patient Selection for Clinical Trials

 

Finding the right patients for clinical trials is crucial for the success of pharmaceutical research and can be a time-consuming process. This is because most clinical trials involve patients referred by physicians, and in many countries like the United States, it’s a challenging task. In the U.S., less than 4% of adults participate in clinical trials, a figure that has remained stagnant or decreased for decades, especially in areas like oncology. Furthermore, according to a study, the majority of clinical trials, up to 85%, struggle to recruit and retain enough participants, and four out of five trials fail, despite an annual investment of nearly $1.9 billion in recruitment.

AI is being used to streamline this process. By employing natural language processing algorithms and data analysis, it can identify patients who meet specific clinical trial criteria and create profiles for doctors and researchers to find suitable candidates for a clinical trial. By having a machine handle this task, the process becomes much faster and more accurate, potentially increasing recruitment efficiency, reducing waiting times for patients in need of access to new therapies, and cutting costs, with estimated potential annual benefits of $13 billion. In this regard, new startups are emerging with the goal of storing patient information to proactively identify perfect candidates for a specific drug trial, potentially laying the foundation for a new recruitment model.

Social Perception of AI Application in Medicine

Despite the advances in the application of AI in medicine, with the emergence of ChatGPT, the conversation about this technology and its application in various sectors has resurfaced like never before, capturing the interest of almost every conversation and raising questions from both healthcare professionals and the general public. According to a recent survey by Morning Consult, approximately 70% of American adults have concerns about the growing use of AI in healthcare. Older adults, such as Baby Boomers (77%) and Generation X (70%), expressed a higher level of concern compared to younger Generation Z individuals (63%). It is noteworthy that citizens are more likely to feel comfortable with the use of AI for administrative tasks than for tasks such as diagnosing a disease or creating a treatment plan. Most respondents also stated that they would demand to be informed if AI is used in any way during their diagnosis, treatment, or medical care.

Simultaneously, questions are also being raised about ethical issues, data privacy, and decision-making. As AI continues to play an increasingly significant role in healthcare, it will be essential to address these concerns and establish clear guidelines for its responsible and beneficial use for patients and the healthcare system as a whole.

Horizon 2024: Transparency, Communication, and Security

It is clear that AI is not just a trend that is everywhere but an essential tool that will make a difference in people’s lives. However, as with any technological revolution, it also faces crucial challenges. To fully embrace this technological advancement, it must be ensured that patient data is protected, and the highest standards of security are followed. Additionally, recognizing the importance of transparency and effective communication in its implementation in medicine is crucial, ensuring that patients understand the benefits and risks associated with it. Only in this way, by working together from public and private institutions to multilateral organizations to invest in research and development, can we fully harness its transformative potential, which can generate significant savings and benefits for both the industry and patients and healthcare systems.