The healthcare industry is transforming significantly, moving away from traditional one-size-fits-all approaches toward highly personalised treatment plans. This shift is driven primarily by AI integration, which enables healthcare providers to consider each patient’s unique genetic makeup, medical history, and lifestyle factors when developing treatment strategies.
“There is a significant gap or opportunity between the best knowledge and the best care available today and what most people have access to,” says Rafael Jegundo, founder and CEO at Whitesmith. AI helps bridge this gap by providing personalised treatment insights that might otherwise require multiple specialists.
AI systems can analyse vast amounts of data, including genetic information, medical records, and lifestyle factors, to create personalised treatment plans that consider numerous variables simultaneously. This capability democratises access to specialised medical knowledge previously limited to those with access to multiple specialists.
How AI enables personalization
AI excels at analysing complex, interconnected data points to identify patterns and make treatment recommendations. These systems can analyse genetic data to identify the most effective medications for individual patients based on their genetic makeup. They cross-reference medical literature with patient records to suggest evidence-based treatments tailored to specific conditions and circumstances.
Beyond initial treatment selection, AI systems can monitor real-time patient data to adjust dosages and interventions as needed, creating truly dynamic treatment plans. They can also identify potential adverse drug interactions before they occur, preventing complications from medication combinations.
The clinical impact of this AI-enabled personalisation is already showing promising results. Patients experience reduced trial-and-error periods when finding effective treatments, as AI can more accurately predict which interventions will likely succeed. This leads to better patient outcomes through targeted interventions tailored to individual needs. Healthcare providers report fewer adverse events from inappropriate medications when using AI-guided prescription systems. The healthcare system benefits from more efficient resource allocation by focusing on treatments most likely to succeed for each patient.
Real-world applications
In genetic profile analysis, AI is revolutionising how genetic information informs treatment decisions.
“You could get a genetic test and get more context and more detail with AI autonomously about what would be, for example, the food, the lifestyle and the behaviours that would better match your gene profile,” explains Rafael Jegundo.
AI algorithms process extensive patient data, including genetic information, to create personalised treatment plans and identify hidden insights that may have gone unnoticed.
For chronic disease management, AI is particularly valuable in personalising treatment. AI-powered systems analyse patient data to provide tailored interventions and management strategies for diabetes and asthma. These systems can predict disease progression and recommend preventive measures based on individual risk profiles.
In mental healthcare, AI matches patients with the most appropriate treatments based on their unique symptoms and needs. This personalised approach leads to more effective interventions and better patient outcomes by considering the complex, multifaceted nature of mental health conditions.
Future outlook
Despite challenges related to data privacy, algorithmic transparency, and healthcare equity, the future of personalised treatment through AI looks promising. “We are going to get new frontier models from all the big labs, which will be better and better in these areas,” notes Rafael Jegundo.
By combining human medical expertise with AI’s ability to process vast amounts of data, we’re moving toward a healthcare model where treatments are tailored to individual needs. This transformation makes the exceptional standard of care that was once available only to a few accessible to many more people, potentially reducing healthcare disparities and improving outcomes across populations.
________
More about how AI can change the healthcare industry here and here.
The Non-Technical Founders survival guide
How to spot, avoid & recover from 7 start-up scuppering traps.
The Non-Technical Founders survival guide: How to spot, avoid & recover from 7 start-up scuppering traps.
