By Lily Chan, Senior Commercialisation Manager at Ploughshare

Artificial Intelligence (AI) is reshaping most industries, and healthcare is not exempt from this. In the health and wellbeing space, this reshaping is happening at a rapid pace, offering breakthroughs in diagnostics, treatment planning, and drug discovery.

Machine learning (ML) models and AI-driven tools are not just enhancing efficiency; they are fundamentally changing how diseases are detected, studied, and treated. From protein-folding predictions to the acceleration of drug discovery, AI is revolutionising healthcare. At Ploughshare we’re incredibly lucky to have been a part of this with our spin-outs like Presymptom as it redefines sepsis detection and diagnosis – but this is just one example (albeit one of our favourites) of how AI is changing healthcare for the better. But what about more generally?

AI in Healthcare Diagnostics: A Game-Changer

One of the most transformative AI-driven tools in healthcare is AlphaFold, a deep-learning system developed by DeepMind. Historically, scientists struggled for decades to predict protein structures accurately, a process crucial for understanding diseases and designing new treatments. AlphaFold has solved this challenge by predicting 3D protein structures with remarkable precision, drastically reducing the time and resources required for drug discovery and personalised medicine. This does still hinge on laboratory work to verify these structures, but the potential discovery time could well be heavily reduced.

Beyond protein folding, AI-powered ML-driven diagnostics are improving potential internal injury detection through advanced scanning technologies. for example, EyeTBI, a technology that is currently in the Ploughshare pipeline of development takes AI-driven technology to accurately detect subtle changes in molecular biomarkers to diagnose traumatic brain injury (TBI). According to The Lancet, TBI is the leading cause of injury-related death and disability worldwide, so this type of advancement is incredibly important to ensure efficient triaging and early diagnosis

This could also be brought to life in areas like pathology, where AI could assist in detecting abnormalities in blood samples or tissue biopsies with higher accuracy. Equally ML algorithms in wearable devices can track real-time health data, predicting potential health risks before they become critical – which is something similar to a heat acclimation technology that the Dutch military is using in wearable form based on a technology Ploughshare has helped liberate and scale.

The potential positive impact on integrating AI into diagnostics is huge. With pressures on healthcare professionals growing, they will be able to provide faster, more precise interventions, ultimately saving lives and reducing hospital workloads.

AI in Drug Discovery: Faster, Safer, and More Efficient

Drug discovery is traditionally an expensive and time-consuming process, often taking over a decade and costing billions to bring a single drug to market. AI is revolutionising this field by rapidly identifying promising drug candidates, predicting side effects, and streamlining clinical trials.

One of the key applications of AI is in drug discovery, from drug design, target validation to even assessing whether a new drug could have harmful effects on the body. Previously, this would require extensive lab testing and lengthy trial phases. AI models could be used to analyse molecular structures and predict potential toxicities and negative effects early in the research process, streamlining processes and significantly reducing development costs thereby improving patient safety.

Companies like Insilico Medicine and BenevolentAI are using deep learning to screen thousands of chemical compounds in days rather than months, accelerating the search for new treatments for conditions like Alzheimer’s and cancer. Since the COVID-19 pandemic, AI-driven research has helped scientists repurpose existing drugs more quickly than ever before, showcasing the technology’s potential in responding to global health problems.

Pharmaceutical companies have the potential to integrate AI into drug discovery processes, and maybe even bring new, safer treatments to market faster, which can offer hope to patients with conditions that lack effective therapies.

The Future of AI-Driven Innovation in Healthcare

AI’s potential in healthcare is far from being fully realised. Looking ahead, with budgets being squeezed and a general expectation to be able to do more with less, AI could really drive innovation in several ways – certainly for national healthcare systems such as the NHS that are under more strain than ever before. For example:

1. Personalised Medicine: AI can quickly enable tailored treatments based on an individual’s genetic makeup, lifestyle, and health history. This could improve outcomes and minimise side effects.

1. AI-Powered Robotics: Robotic-assisted surgeries are closer to being a regular part of healthcare than you might think. AI-driven prosthetics could adapt to users’ needs, with complementary machine learning enhancing the precision and adaptability of medical interventions.
2. Early Disease Prediction and Prevention: AI-driven predictive models and diagnostic tools can help identify disease risks at an early stage, allowing preventative interventions before symptoms even appear.
3. Real-Time Global Health Monitoring: AI could well be crucial in tracking and predicting pandemics, environmental health risks, and emerging diseases by analysing vast amounts of public health and open-source data in real time.

Conclusion

There is no doubt that AI will transform healthcare, and eventually redefine it. From breakthroughs in protein folding to ML-driven diagnostics and AI-accelerated drug discovery, technology is driving faster, more accurate, and more cost-effective healthcare solutions. As AI continues to evolve and change, its ability to revolutionise diagnostics, streamline drug development, and personalise treatments and wellbeing advice will only grow stronger, ensuring that technology and innovation becomes a cornerstone of modern medicine.