In a previous article, Digital twins for personalized medicine: promising with caveats, we examined the pros and cons of digital twin technology applied to medicine at a personal level. Digital twin technology was devised to model physical objects, both their elements as well as the dynamics of their operation. Each model is a unique one-to-one correspondence with the physical object.

Applying this approach to medicine, simulating the whole human through genomics, physiology and environments and lifestyle over time, the promise is a much-improved delivery of healthcare. We raised some concerns about this, but a recent announcement from the National Institutes of Health has actually addressed some of those concerns. Others remain.

In 2015, the Obama administration announced a genetic and collection program, The Precision Medicine Initiative or PMI. The NIH created a research program to gather data from one million volunteers, the “All of Us,” program, designed to jumpstart personalized medicine. That program has recently come out of beta testing and is in production. While the program itself is not explicitly aimed at creating digital twins, its operation is creating much of the data needed to develop digital twins.

PMI just completed a yearlong beta test period with 25,000 volunteers, and is looking to transform the relationship between researchers and participants, bringing them together as partners to inform the program’s directions, goals and return of research information. These efforts include building trust among populations historically underrepresented in research.

Unlike many large medical research studies, All of Us has some unique and very positive aspects. For instance:

• Participants in the program will be considered partners.
• The collection of participants will reflect the diversity of the American population.
• Trust will be earned through engagement and transparency.
• Participants have access to information and data about themselves.
• Participants may withdraw at any time, and remove their data except for those instances where it is already used in a study.
• Data will be broadly accessible, but:
• The program will adhere to the PMI Privacy and Trust Principles and the PMI Data Security Policy Principles and Framework.

It is unusual for a medical study to engage with participants as well as nontraditional researchers. The above guidelines do not, however, address the issues of:

• Identity management
• De-identification
• Encryption
• Physical security
• Security policy and procedures

The PMI program should be commended for addressing all of these concerns, and it will govern the use of the use of the data. Creating a cohort of digital twins that include genomic, physiologic and social data on individuals poses a massive risk of invasion and disclosure, both malicious and innocent. The data security framework allays some concerns expressed in the previous article. To summarize:

Summary of concerns about digital twins for personalized medicine

Digital Twins can provide a way to analyze practices in current debates on health care, such as wellness, disease, preventative care and enhancement. In the same way a Digital Twin of a jet engine in flight can analyze and react to inputs, a patient Digital Twin will follow “normal functioning,” “derangement,” “preventative medicine,” “performance optimization” and “enhancement.”

The PMI is addressing some of the concerns about digital twins for personalized medicine, but other concerns remain:

• Discrimination: Such intimate detail about an individual’s genome, habits, medications and ethnicity can be an indelible identifier and potentially inhabit their lives.
• Medicine is shaky: The practice of medicine simply cannot be reduced to a series of algorithms, especially when expert opinion embedded in the models is far from unanimous.
• Weight of Standard of Care: Practitioners are protected from liability by not deviating form is considered the standard. No amount of model sophistication can overcome that.
• Reliance on Funded research: With funding for research coming from deep-pocketed organizations with an agenda, published research is not reliable.
• Conflict of Interest in the NIH itself: The NIH and FDA both have a history of exchanging their leaders with those from the healthcare industry.
• Inability to detach from your twin: It is easy to conceive of a situation where a patient’s twin follows then from doctor to doctor. Whatever bias, incompleteness and error exists in the model, it would be difficult to minimize it.

Given its lofty principles, the PMI has the potential to make a significant contribution to our understanding of healthcare. Issues about a Digital Twin, however, are still concerning.

Image: spirit111/Pixabay