Vithanage Madhushani Jadetimes Staff
V.E.K. Madhushani is a Jadetimes news reporter covering Innovation.
How Digital Twins Could Revolutionize Drug and Device Discovery
In a quiet corner of Northumberland, the future of healthcare is taking shape not in operating rooms or laboratories, but within the confines of a computer. Adsilico, a cutting edge AI firm, has created a revolutionary tool: digital twins of the human heart. These hyper realistic, computer-generated models are being used to rigorously test medical devices and treatments in ways that could transform drug discovery and patient care.
The Rise of Virtual Testing: What Are Digital Twins?
A digital twin is a virtual replica of a physical object, system, or in this case a human organ. Adsilico’s digital twin technology simulates the intricacies of a human heart, down to its anatomical structure and physiological functions. By creating thousands of unique digital hearts, Adsilico’s AI powered simulations replicate conditions such as varying blood pressures, diseases, and even diverse ethnic characteristics.
These virtual hearts allow researchers to test devices like stents and prosthetic valves in a controlled, computer generated environment, bypassing the limitations of traditional clinical trials. "Virtual testing enables us to replicate countless scenarios that would be impractical or impossible with human or animal trials," says Sheena Macpherson, Adsilico’s CEO.
Diverse Hearts, Diverse Solutions: How AI is Expanding Representation
Clinical trials have long been criticized for their lack of diversity, with data heavily skewed toward white male participants. Adsilico’s digital twin technology directly addresses this issue by incorporating data from various demographics, including underrepresented groups. "This allows us to create more inclusive devices that work safely across diverse populations," explains Macpherson.
The AI models are trained using MRI and CT scan data from consenting patients, combined with cardiovascular datasets. This integration ensures the simulations are grounded in real human anatomy, while also addressing gaps in clinical data. By testing medical devices on virtual patients with varying conditions, researchers can predict outcomes for a broader range of individuals, improving safety and efficacy.
Saving Time, Lives, and Money: The Promise of Digital Twin Technology
Digital twins are not just about improving outcomes they’re also a game-changer for efficiency. Traditional clinical trials can take years and cost millions. Virtual testing can significantly shorten this timeline.
Adsilico’s simulations allow researchers to test thousands of scenarios in days, cutting costs and speeding up the path to approval. For pharmaceutical companies, the financial implications are staggering. Sanofi, a global leader in drug development, aims to reduce its testing period by 20% using digital twin technology. "A mere 10% increase in success rates could save $100 million, given the high costs of late-stage clinical trials," says Matt Truppo, Sanofi’s head of research platforms.
Revolutionizing Drug Development: Sanofi’s Pioneering Use of AI Simulations
Sanofi is among the first major pharmaceutical companies to integrate digital twins into its drug discovery process. Instead of testing drugs solely on human participants, the company creates AI-based virtual patients. These digital replicas simulate how drugs interact with the body, providing insights into absorption rates and potential side effects.
This approach is particularly promising in tackling complex diseases like cancer and autoimmune disorders, where traditional testing methods often fall short. "With many diseases being highly intricate, AI-powered digital twins represent the next frontier in medical research," says Truppo.
Challenges of Bias and Legacy Data in Virtual Models
Despite their potential, digital twins are only as reliable as the data they are trained on. Charlie Paterson, an associate partner at PA Consulting, warns that outdated or biased data could perpetuate the very disparities digital twins aim to resolve.
Legacy data, often collected using methods that excluded marginalized populations, presents a challenge for companies like Sanofi. To address this, the firm supplements its internal datasets with third-party sources such as electronic health records and biobanks. "We recognize the need for robust, inclusive datasets to ensure our simulations reflect real-world populations," says Truppo.
The Ethical Horizon: Could Digital Twins End Animal Testing?
One of the most exciting possibilities of digital twin technology is its potential to eliminate animal testing. Current drug and device testing often relies on animals like dogs, pigs, and sheep models that differ significantly from human biology.
"A virtual heart is closer to a human heart than that of any animal," says Macpherson. By simulating human conditions more accurately, digital twins could render animal trials obsolete, accelerating the shift toward more ethical and effective research methods.
The Future of Medicine, Powered by AI
From reducing clinical trial timelines to enhancing safety across diverse populations, digital twins represent a paradigm shift in medical research. While challenges like data bias remain, companies like Adsilico and Sanofi are paving the way for a future where innovation meets inclusivity.
As this technology continues to evolve, it’s not hard to imagine a world where the first phase of any medical trial begins not in a lab but inside the virtual body of a digital twin.
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