Virtual Twins Accelerate Personalized Medicine
- A primary goal in contemporary science is to expedite the delivery of new medications to those in need.
- This landscape is evolving, thanks to digital twins, a technology leveraging artificial intelligence to transform healthcare.
- Although still in its early stages,this technology is being adopted in hospitals and research centers.
virtual Twins: Revolutionizing Personalized Medicine and Accelerating Drug Delivery
Table of Contents
- virtual Twins: Revolutionizing Personalized Medicine and Accelerating Drug Delivery
- Virtual Twins: Revolutionizing Personalized Medicine – Q&A
- What are digital twins in healthcare?
- How do digital twins enhance patient care?
- What are the benefits of using digital twins in drug delivery?
- How is Elem Biotech using digital twins to advance healthcare?
- What data is required to create an effective digital twin?
- What are the challenges associated with digital twin technology in healthcare?
- could digital twins replace animal testing?
- How do digital twins address the issue of non-responsive patients in cardiac resynchronization therapy?
- Key Differences Between Traditional Methods and Digital Twins
A primary goal in contemporary science is to expedite the delivery of new medications to those in need. This not only benefits patients but also yields important economic savings. Though, clinical trial timelines are frequently enough unpredictable, and the likelihood of a molecule reaching the market is slim, with only about 1% succeeding.The remainder are abandoned during progress.
This landscape is evolving, thanks to digital twins, a technology leveraging artificial intelligence to transform healthcare. These virtual representations of objects or patients are constructed from extensive retrospective data. By using real-time data, they predict how the real object or system will respond to various stimuli, enabling simulations of different scenarios and strategies.
Early Implementation and Impact
Although still in its early stages,this technology is being adopted in hospitals and research centers. Christopher Morton, CEO of Elem Biotech, notes, “A thing very important for the industry is to make good decisions when choosing the molecules that go forward. The laboratory tests are challenging, then, studying what may be the risk of the molecule at this time is a very important introduction.”
One key submission is considering human risk indicators during the development of new treatments, well before human trials. According to Morton, halting a development before clinical trials can ”permits to save more than one billion of euros”. Furthermore, this innovation allows for a population diversity in trials that is currently lacking. “It effectively works on much more complete and complex populations, reflecting the diversity that exists in the clinical trials themselves that are done to offer this solution from the finding part,” he adds.
Virtual populations can incorporate hormonal variations that respond to different stages of a woman’s menstrual cycle. ”Other variations are age, time of day or other associated comorbidities,” it is indeed noted. These trials also “permits to test therapies in pregnant and pediatric population”, which is currently unfeasible.
Elem Biotech’s Role in Advancing Digital Twins
Elem Biotech, based in Barcelona and Bristol, utilizes supercomputers in collaboration with the Barcelona Supercomputing Center to advance this technology. They specialize in studying heart function in pacemaker surgery. “Our ability to study different scenarios is very large,” says Morton. They work closely with hospitals and doctors. “The centers guide us, to verify that what we do is fine. A virtual twin in cardiac pathologies allows us to mobilize a person’s heart and, apart, study how a pathology can affect it. We can apply different treatments and possibly make the treatment decision,” he explains.
Personalized Treatment through Virtual Twins
This raises the question of whether animal models are becoming obsolete. Elem Biotech sees this as another advantage of digital twins. “It allows trials in virtual humans before in real human beings without putting the latter in danger,” they insist.
Another significant benefit is the personalization of treatment: administering the correct medication from the outset without observing side effects on the patient, as the human digital twin has already been tested. A digital twin of a human heart “permits to plan several treatments and see the result of each of them”, allowing the selection of the best approach for the patient. Juan Sebastián Romero Fernández, Business Manager Advanced Therapies at Siemens Healthineers, details, “For example, there are 30% of patients who do not respond satisfactorily to cardiac resynchronization.The use of this technology woudl allow the therapy to be applied only to patients who can benefit from it.”
Romero Fernández adds that this reduces patient stress and uncertainty. By combining historical and real-time data, digital twins can identify risk factors for disease onset or progression.
Challenges and Future Considerations
This technology faces challenges, primarily in obtaining data from diverse sources. this includes high-resolution medical images (CT scans, ultrasounds, MRIs), wearables (vital sign monitoring bracelets, electrocardiography devices, oxygen saturation, temperature, non-invasive pressure monitors), and historical patient data (genetics, family history, lab results, diagnoses, and prior progression).
Romero Fernández emphasizes the importance of ensuring data protection and warns of cybersecurity risks. “It is necesary the creation of a specific regulation for digital twin technologies that implements the existing regulations, such as the General Data Protection Regulation (RGP, with specific guidelines for cybersecurity and civil liability. In addition, the right to withdraw consent at any time could directly affect functionality and compromise treatment,” he concludes.
Virtual Twins: Revolutionizing Personalized Medicine – Q&A
What are digital twins in healthcare?
Digital twins in healthcare are virtual representations of patients or even populations, created using extensive data, including ancient records and real-time information. They leverage artificial intelligence to predict how the real-world counterpart would respond to various stimuli, allowing for simulations of different treatment scenarios and strategies. They act like what they represents.
How do digital twins enhance patient care?
Digital twins enhance patient care in several ways:
personalized Treatment: By testing different treatment options on the digital twin, doctors decide on the moast effective medication and approach for a patient from the outset, minimizing side effects and uncertainty.
Predictive Analysis: Combining historical and up-to-date data allows digital twins to identify risk factors for disease onset or progression.
Comprehensive Patient View: Integrating data from EHRs, medical devices, and genetic information provides a holistic view of a patient.
What are the benefits of using digital twins in drug delivery?
Digital twins offer critically important benefits in drug delivery, including:
Accelerated Drug Growth: By simulating clinical trials, digital twins can speed up the process of bringing new medications to market which can benefit patients but also yield economic savings.
Reduced Development Costs: identifying and halting the development of ineffective molecules before clinical trials can save billions of euros.
Diverse Population Trials: Digital twins enable the inclusion of diverse populations, considering factors such as hormonal variations, age, time of day, and comorbidities, which are often lacking in conventional trials.
Trials in pregnant and pediatric populations, which are normally unfeasible.
How is Elem Biotech using digital twins to advance healthcare?
Elem Biotech, based in Barcelona and Bristol, uses supercomputers in collaboration with the Barcelona Supercomputing Center to advance digital twin technology. Their work focuses on:
Studying heart function, particularly in pacemaker surgery, to analyze different treatment scenarios.
Working closely with hospitals and doctors to ensure the accuracy and relevance of their simulations.
Mobilizing a person’s heart to enable in-depth study of how pathologies affect it and how different treatments can be applied.
What data is required to create an effective digital twin?
Creating an effective digital twin requires a wide range of data from diverse sources, including:
high-resolution medical images (CT scans, ultrasounds, MRIs)
Wearable device data (vital sign monitoring bracelets, electrocardiography devices)
Historical patient data (genetics, family history, lab results, diagnoses, prior progression).
Oxygen saturation levels.
Body temperature.
Non-invasive pressure monitoring.
What are the challenges associated with digital twin technology in healthcare?
The challenges include:
data Acquisition: Gathering sufficient and high-quality data from diverse sources can be complex.
Data Protection and Cybersecurity: Ensuring the security and privacy of sensitive patient data is crucial, necessitating specific regulations and guidelines.
Functionality compromise with the right to withdraw consent at any time.
* Regulatory framework: The creation of specific regulation for digital twin technologies that implements the existing regulations, such as the General Data Protection Regulation (RGP, with specific guidelines for cybersecurity and civil liability.
could digital twins replace animal testing?
Elem Biotech views digital twins as a promising choice to animal models,stating that they “allow trials in virtual humans before in real human beings without putting the latter in danger.”
How do digital twins address the issue of non-responsive patients in cardiac resynchronization therapy?
Juan Sebastián Romero Fernández from Siemens Healthineers points out that about 30% of patients do not respond satisfactorily to cardiac resynchronization therapy. Digital twin technology would address this by allowing the therapy to be applied onyl to patients who are likely to benefit from it.
Key Differences Between Traditional Methods and Digital Twins
| Feature | Traditional Methods | Digital twins |
| ———————- | ———————————————————— | —————————————————————————————————————————– |
| Trial Diversity | Limited diversity, often lacking depiction of specific demographics.| More complete and complex populations, reflecting real-world diversity, including hormonal variations, age, and comorbidities. |
| Risk Assessment | Risk indicators are typically assessed during human trials. | Human risk indicators can be considered well before human trials, potentially saving significant costs.|
| Personalization | Treatments generally administered without individual testing. | Allows personalization of treatment by simulating various therapies on a digital twin of the patient. |
| Safety | Risks to real patients during trials.| No risk to real patients, as trials are conducted on virtual twins. |
| Cost | High costs,with only a small percentage of molecules reaching the market. | Potentially lower costs due to more efficient decision-making and reduced need for extensive real-world trials. |