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11 real ways AI is transforming healthcare
Healthcare is rapidly evolving, thanks to advancements in artificial intelligence (AI), which promises to make treatments more personalized and impactful than ever before. A recent report from the World Health Organization highlighted AI's transformative potential in global health, emphasizing how it will revolutionize drug development, administration, diagnosis, treatment, and patient care. When properly regulated and integrated, AI has the power to enhance access to high-quality services for everyone, alleviate workforce shortages, and reduce healthcare system expenses.
Looking ahead, we can anticipate treatment plans customized specifically for each patient, factoring in genetic profiles, medical histories, and lifestyle choices to ensure the best possible interventions. The ability of AI to sift through vast amounts of data provides medical professionals with crucial insights to accurately detect, diagnose, and create tailored treatments for critical health concerns and diseases, ultimately saving more lives. Clinicians will benefit from real-time support, improving their decision-making abilities. In surgical settings, intelligent robotic systems, such as F.MED's microsurgery robots, will assist with intricate procedures, performing minimally invasive surgeries that lead to superior outcomes and quicker recovery times. AI-powered remote monitoring will enable patients to receive continuous care and therapy from the comfort of their homes. By simplifying processes and lightening administrative burdens, AI will allow healthcare professionals to focus on what truly matters—delivering exceptional patient care.
In this new AI-driven healthcare landscape, systems will become more proactive, offering patient-centered experiences that reach a broader audience. Breakthroughs in medical science will happen faster, and treatments will significantly enhance patient outcomes. Personalized insights and wellness management tools will empower more individuals to adopt healthier lifestyles. With all this in mind, let's explore some of the remarkable ways AI is already making a difference in healthcare worldwide:
**How is AI being used in healthcare?**
1. **Research and Development:** AI is reshaping product and drug discovery. In silico compound screening accelerates the development process by mapping millions of chemical compounds based on structure and function—similar to how generative AI creates content but applied to molecular structures. Deep learning algorithms assist in virtual screenings by analyzing extensive datasets of chemical compounds to predict how drugs might interact with specific proteins or molecules. Scientists can then concentrate on the most promising candidates. Generative models, paired with detailed data analysis, can also help identify existing drugs that may be repurposed for new therapeutic uses.
2. **Clinical Trials:** AI is proving invaluable in optimizing clinical trials. It helps identify the most suitable participants more quickly and predicts trial outcomes to cut down on time and costs. Biomarkers assist in assembling diverse and representative populations, while digital medical writing assistants, powered by natural language generation, streamline regulatory filings and reporting. These tools analyze vast datasets swiftly, uncovering key insights and patterns to expedite decision-making. By improving efficiency throughout the clinical development process, pharmaceutical companies could see a 50% reduction in costs due to streamlined clinical trial processes and automated document drafting, along with faster trials by over 12 months and at least a 20% increase in net present value.
3. **Manufacturing:** Major pharmaceutical companies like GlaxoSmithKline and Sanofi have adopted AI to boost the efficiency and reliability of drug production. AI models support predictive maintenance, enabling early fixes and replacements before equipment malfunctions disrupt manufacturing. They also optimize stock management to prevent waste. By analyzing quality control issues—known as deviations—at production sites and automating the review process for minor deviations, Sanofi has slashed closure times by 60%, resulting in shorter cycles, improved quality, and enhanced reliability across the supply chain.
4. **Safety and Quality Regulations:** AI enhances safety and quality in healthcare and pharmaceuticals by automating compliance checks and reporting. It streamlines the regulatory submission process by generating necessary documents, tracking changes, and verifying data. In drug manufacturing, AI detects anomalies in production data, resolving potential issues promptly and minimizing non-compliance risks. For ongoing drug safety, AI analyzes clinical data to proactively spot potential adverse effects and safety risks, continuously monitoring feedback from healthcare providers and patients.
5. **Commercialization:** McKinsey estimates that AI could add $60 billion to $110 billion annually in economic value to the pharmaceutical and medical-product industries by accelerating compound identification, speeding up development and approval processes, and improving marketing strategies. Marketers can leverage AI's advanced search and data analysis capabilities to glean deeper insights from customer research, physician data, and updates on policy changes, legal developments, and formulary considerations. Armed with this information, marketers can better understand target markets and refine campaign strategies accordingly.
6. **Consultation:** Patients may soon interact with AI virtual assistants before visiting a doctor. These assistants gather medical records, assess symptoms, and triage patients based on their conditions. Doctors benefit from more focused consultations, armed with valuable insights to aid diagnosis and treatment. Natural language processing (NLP) tools relieve administrative burdens by transcribing and summarizing all clinical interactions, saving doctors time.
7. **Diagnostics:** Training AI algorithms to analyze medical images and detect patterns from symptoms and other factors enables earlier and more accurate identification of conditions like cancerous lesions and tumors. For instance, the American Cancer Society found that many mammograms yield false positives, leading half of healthy women to believe they have cancer. However, AI can review and interpret mammograms 30 times faster with 99% accuracy, drastically reducing unnecessary biopsies.
8. **Medical Decision-Making:** AI assists medical professionals in diagnosing conditions, creating effective treatment plans, and predicting patient outcomes by consolidating and deriving insights from various data sources, including medical records, lab results, and imaging data. Machine learning models are especially useful for detecting serious conditions like sepsis, meningitis, and heart disease, which might otherwise go unnoticed during initial consultations. AI also helps build comprehensive patient views by integrating data from electronic health records, lab results, wearable devices, and more.
9. **Treatment:** In the UK, over 14,000 hospital beds are occupied daily by patients who are fit for discharge but cannot leave due to bed shortages. Busy hospitals face significant challenges in ensuring patient safety. AI predicts admission rates, identifies seasonal peaks, and optimizes staffing, resource allocation, and bed management. NLP tools generate discharge summaries much faster, easing the workload on healthcare staff and expediting the discharge process. AI also improves communication between departments, crucial for coordinating care in complex cases involving multiple specialists.
10. **Follow-Up Care:** AI is revolutionizing patient follow-up care through effective remote monitoring and personalized experiences. It sends personalized follow-up messages and medication reminders to reduce readmission rates and flags abnormalities for timely interventions. Tools like personalized diabetes management apps help track adherence to treatment plans, offering recommendations based on real-time patient data.
11. **Health Assessment/Self-Monitoring:** Consumer wearables enhanced by AI technology are transforming chronic illness management, particularly for heart disease. Better monitoring allows healthcare professionals to closely track patient symptoms and detect potentially life-threatening episodes earlier. Smartwatches feature heart rate monitoring and use AI algorithms to analyze heart rhythms, helping users identify irregularities such as atrial fibrillation.
**Dassault Systèmes and the Future of AI in Healthcare**
Like in our daily lives and across most industries, AI is poised to become a core component of global healthcare systems. Over 70% of healthcare organizations are currently experimenting with and implementing AI capabilities to enhance patient experiences and streamline operations. Many believe that AI, coupled with other technological advancements, will fundamentally transform the industry, ushering in an era of efficient, personalized, and proactive care.
This vision aligns closely with Dassault Systèmes' mission to innovate and improve efficiency in life sciences and healthcare—a future where patients become active consumers in control of their health, and virtual twin experiences drive sustainable innovation and efficient healthcare systems.
Through its virtual twin capabilities and powerful AI tools, Dassault Systèmes aims to empower healthcare organizations, pharmaceutical companies, and consumers with data-driven methods to visualize, predict, and manage responses to treatments and interventions. This includes creating dynamic, highly detailed digital replicas—or virtual twins—of patients, incorporating their individual anatomy, genetics, and real-world medical data. In clinical trials, virtual twins will replace traditional placebo groups, using synthetic patient data to accelerate research and expand access to innovative therapies. When scaling precision medicine production, virtual twins and AI will enable efficient biologic manufacturing and global delivery.
"Imagine if you could understand, represent, test, and predict what is invisible—from how a drug impacts a disease to the outcome of a surgical intervention," said Claire Biot, our VP of Life Sciences and Healthcare, introducing Dassault Systèmes' vision earlier this year. "That's exactly what we're striving to achieve, positioning the virtual twin as a platform for medical excellence and value-based care."