WEF Funding Universities to Develop “Artificial Patients” for Clinical Trials

In the world of human complexity, particularly biological diversity, robust clinical trials play an essential role in the testing of new synthetic drugs before licensing and commercialization.

Now, some of us may raise an eyebrow at just how much “testing” is actually taking place, given that certain drugs known as “COVID-19 vaccines” were operation-warp-speeded into the arms of over 5 billion people worldwide.

Yet, it typically takes over 10 to 15 years to complete all three phases of clinical trials, costing on average $1 to roughly $3 billion until a new drug is approved for clinical use.

Recruiting participants for clinical trials can be challenging, particularly for rare diseases. Patients with the underlying condition of research interest are usually the participants; they are randomly assigned either the new medicine under investigation or a placebo, with those receiving the latter being part of the “control group.”

Now, can you imagine a world where patients suffering from a disease are replaced with computerized data that mimic their unique characteristics and symptoms?

That’s right.

Lo and behold—introducing the “artificial patient.”

An artificial intelligence (AI) program generates an “artificial patient” after processing an exhaustive patient information database compiled from previous clinical trials.

Also known as a “synthetic patient,” it is a set of computerized data that, ideally, represents the distinguishing characteristics of a patient with the underlying disease of interest, e.g., common symptoms, weight, blood pressure, and even genetic factors.

If you’re feeling somewhat uneasy or downright outraged with the idea of AI-generated data replacing actual patients—even for the control group—you’re not alone.

However, know that there is growing interest in, and growing money injected into, the research and development of “synthetic patients.”

During the annual World Economic Forum (WEF) meeting in Davos, Switzerland, political, business, and cultural leaders worldwide gathered to discuss AI as a “driving force for the economy and society” that could “benefit all.”

Indeed, this particular theme occupied 32 sessions throughout the 5-day convention; it is, therefore, unsurprising to learn that the WEF is currently funding research on using AI to “create artificial patients with similar health information to real patients in clinical trials” in a “partnership” with the United Kingdom (U.K.) since 2019.

Those who support using AI to generate such medical data claim it could help overcome problems associated with:

Yet, the realm of human physiology, interwoven with mindset and attitude toward managing illness, is remarkably intricate and highly diverse. Even two individuals, such as genetically identical twins or parent and child, can differ significantly in their immune systems and susceptibility to diseases.

As explained in a previous article, the resultant output of an AI program reflects its underlying design but, above all else, the amount, quality, and diversity of data used in developing that program.

A large and diverse database containing thousands of medical records is needed to develop a reliable AI program. Thus, the ability to generate large-scale “synthetic patients” demands a database involving proper distribution of demographics, medical conditions, dietary intake—and previous and current lifestyle choices and social determinants of health, which are not typically recorded in medical data.

Still, proponents of integrating computer-generated data that resemble the profiles of disease-stricken patients into clinical trials will persevere whenever adequate funding is provided.

Given the arrangement between the U.K. and WEF to foster “a ‘regulation revolution’ that meets the challenges and opportunities of technological advances,” the Medicines and Healthcare Products Regulatory Agency (MHRA), which is the U.K. government’s agency and pharmaceutical regulatory authority, received over $950,000 to fund 12 to 18-month projects that are currently ongoing at two U.K. universities.

“In the future,” reads the project summary, “these approaches could be combined with, or even replace, real patient information.”

Well, isn’t that just great? Let’s do away with patients—real human beings as extraordinarily complex organisms—and replace them with AI-generated data that might supposedly “change the way clinical trials are performed in common and rare diseases, lowering their cost and improving how new treatments are tested.”

As part of this cozy arrangement to promote public-private partnerships, the country from which America sought independence became the first to partner with the highly influential WEF’s  Centre for the Fourth Industrial Revolution. Indeed, let us not forget that the leader of the WEF once boasted, “We penetrate the [government] cabinets.”

And for…