AI-generated digital humans and organs are revolutionizing clinical trials, enhancing drug testing, reducing costs, and ensuring more diverse and inclusive research.
In a groundbreaking development, AI-generated digital humans and organs are changing the landscape of clinical trials, making drug testing faster, safer, and more inclusive. These digital innovations are particularly beneficial for medical device testing and pharmaceutical research, addressing long-standing challenges in medical trials.
Enhancing Clinical Trials with Digital Twins
One of the most significant advancements comes from Adsilico, a company at the forefront of creating AI-powered digital twins—virtual human organs that simulate real-life bodily functions. For instance, Adsilico has developed a digital twin of the human heart, which beats and reacts similarly to a real heart but exists solely in the digital realm. This innovation allows for testing cardiovascular devices such as stents and valves without the need for physical prototypes.
These AI-generated models are designed to replicate various human characteristics, including age, weight, gender, blood pressure, and ethnicity. Traditional clinical trials have often ignored these demographic factors, but digital twins address these gaps, offering a more diverse and inclusive approach to medical device testing.
“By using digital twins, we can capture diverse patient anatomies and responses, ensuring that devices are not only safer but more suitable for a wider range of people,” said Sheena Macpherson, CEO of Adsilico. “This method improves the reliability of medical devices and ensures they are inclusive of various populations.”
The potential of digital twins is enormous. A global investigation in 2018 reported over 83,000 deaths and 1.7 million injuries linked to medical devices. Macpherson believes that AI-powered digital twins can help reduce these numbers by providing thorough testing without the extensive costs and time associated with traditional clinical trials.
“Thorough testing is crucial, but clinical trials are expensive. Virtual testing helps reduce costs and allows us to conduct more extensive and diverse tests,” she explained. “For example, we can simulate testing the same heart under different conditions, such as varying blood pressures or disease progressions.”
Digital twins are also breaking down barriers for underrepresented groups in clinical trials. For years, women and marginalized communities have been excluded from many medical studies, but Adsilico’s AI models are changing that. By using real data from cardiovascular patients—including MRI and CT scans—Adsilico ensures their digital models reflect diverse anatomies and provide more accurate testing results.
Speeding Up Drug Development
The pharmaceutical industry is also embracing AI-generated digital twins to streamline drug development. Sanofi, a leading pharmaceutical company, is leveraging this technology to cut testing time by 20% and increase drug success rates. Sanofi’s virtual patients are diversifying trial populations, allowing for more relevant results and improving the efficiency of the drug discovery process.
Sanofi’s AI models simulate drug properties and predict how drugs interact with human biology, providing early insights into drug performance. According to Matt Truppo, Sanofi’s head of research platforms, the benefits of this technology are substantial. “With a 90% failure rate for new drugs, a 10% increase in success can save $100 million per drug,” he said.
AI-generated digital twins also help drug companies test how drugs behave in different conditions, offering a better understanding of potential outcomes. This is particularly useful in tackling complex diseases, where traditional testing methods may fall short.
Overcoming Limitations and Challenges
Despite the remarkable potential of digital twins, there are some limitations. One key challenge is that AI models depend heavily on the quality and diversity of their training data. Charlie Paterson, a healthcare expert at PA Consulting, warned that outdated or biased data could affect the accuracy of the models.
To combat this, Sanofi supplements its internal data with third-party sources like health records and biobanks, ensuring that its AI models are as diverse and accurate as possible.
The Future of Medical Testing
Looking forward, Macpherson hopes that AI digital twins will eventually eliminate the need for animal testing. “A virtual heart is far more realistic than using a dog’s or pig’s heart,” she said. As AI and digital twin technology continue to advance, the future of drug discovery and clinical trials appears more efficient, ethical, and inclusive.
The integration of AI-powered digital twins into drug development and medical device testing marks a significant shift toward safer, faster, and more cost-effective research. With the potential to revolutionize clinical trials, this technology could reshape the future of healthcare, making it more accessible and effective for all.