Digital Twins: Trends and Opportunities
Second generation digital twins have the potential to transform pharma’s business, clinical research and manufacturing processes while driving the personalised medicine agenda and improving chronic disease diagnosis. But can developers overcome significant challenges such as real-time data collection, technology integration, user adoption and the creation of trusted applications? In this report experts in the field examine the advances and application areas of this disruptive technology and examine the challenges that need to be overcome.
Companies
Google, Amazon, Takeda, Apple, Meta, IQAir, Unlearn, LYS, Mavatar, Medtronic, Q Bio, Virtonomy.io
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- Research methodology and objectives
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- Issues and insights
- There is not one type of digital twin
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- First-generation digital twins need to evolve
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- Data collection to create medical digital twins is only skin-deep
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- Healthcare industry issues, such as ineffective treatments, must be addressed
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- Patients with chronic conditions need a personalised method of treatment
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- Big Tech’s involvement in healthcare creates issues of trust
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- Precision medicine in needed in medicine, but the technology is not ready
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- Data safety standards may not be strong enough for the widespread roll out of digital twin technology
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- Further Reading
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