Scientists from the Swiss Interdisciplinary Research Institute for the Development of Technology and Materials Science (Empa) have created digital twins of real patients to experiment with medical treatments that can then be applied to the original human model.
These digital twins are based on mathematical models built with information provided by real patients and enable tailored medical therapies.
They respond to a practical need of modern medicine: although there are effective treatments to treat serious diseases such as cancer, each patient must discover the appropriate dose of the drug to be effective and safe.
Doctors must give different doses to each patient until reaching the limits, either of overdose or of ineffectiveness, to establish the ideal proportion of medication in each case and guide the definitive treatment.
Synthetic opiates For example, synthetic opiates can help control severe pain experienced by cancer patients, the authors of this research explain in a release.
But the exact dosage varies in each case. Fentanyl, a pain reliever 100 times more powerful than morphine, relieves acute pain, but if the dose is not right, it can harm patients with life-threatening side effects.
Currently, these pain relievers are applied to patients through a transdermal patch, which is a way to give patients’ bodies a gentle introduction to the drug without interfering with daily life.
However, it is not easy to find the correct dose for each patient, forcing doctors to practice trial and error in individual cases.
These trials carry the risk of overdose or underdose that no one can observe until reactions are already underway, long after drug administration, with generally unwanted effects.
To ensure that patients receive the correct drug dose specific to individual needs, the digital twin can test potential treatments and simulate how the patient’s body will react at each point of treatment.
Related Topic: Virtual Cancer Avatars Help Personalize TreatmentsRelated Topic: Virtual Cancer Avatars Help Personalize Treatments
Mathematical models The digital twin is constructed from mathematical models that integrate a wide spectrum of variables into the virtual patient, including the age and lifestyle of the real patient.
In the creation of avatar It also takes into account how the actual patient has metabolized the drug and when it reaches that person’s pain center: in this way, the digital twin can accurately predict the effect of a drug.
The digital twin is also updated with psychological and physiological feedback from real patients, to reverse engineer emerging complications after administering the experimental doses to real patients.
For example, humans can provide ongoing information on whether, and to what extent, pain or other side effects persist after a drug dose.
Taking this information feedback into account, the digital twin can dynamically adjust therapy and even predict the course of its evolution, according to the researchers.
The digital twin can also be equipped with sensors that measure physiological parameters of the patient, such as respiratory rate or heartbeat, to update their data in real time.
In extreme cases, doctors can even kill a person’s digital twin multiple times to find the ideal treatment for the real patient, thus ensuring tailored therapy without unnecessary risks.
Hundreds of digital twins
Hundreds of digital twins So far several hundred personalized digital twins of this type have been created and individual therapy procedures have been virtually tested in collaboration with the Cantonal Hospital of St. Gallen.
At this hospital, transdermal patch pain therapy is just the beginning of avatar-assisted therapy for cancer patients.
However, in collaboration with clinics and hospitals, Empa researchers want to optimize other therapies, such as the administration of insulin for diabetes, also using digital twins.
Top image: digital twin undergoing medical treatments from a real person. Empa.
Eddie is an Australian news reporter with over 9 years in the industry and has published on Forbes and tech crunch.