How Does AI in Personalized Medicine Impact Patients and Healthcare Providers? 

What is Personalized or Precision Medicine?

Unlike traditional medicine, where doctors treat patients based on their symptoms, personalized medicine goes one step further. At the heart of this medical practice lie several factors that differentiate one patient from another, even if they suffer from the same disease. 

Key Factors in Personalized Medicine 

1. Genomics: Genomics is the first and most important factor. It helps doctors study the genetic profile of the patients. The profile says a lot about how their body will react to certain medicines and the likelihood of diseases that may be either genetic or new. 
2. Biomarkers: Biomarkers are the second factor in personalized medicine. Proteins, genes, and metabolites are a few biological indicators in the human body that tell a lot about overall health including physical and mental. Getting this information from lab reports or past medical history is rarely possible.
   This information helps doctors to predict whether a patient will likely develop a disease or how well a treatment works for them. Doctors can use this information to create or modify more effective treatments.
3. Lifestyle Factors: How a person lives, eats, and sleeps can unfold many useful insights about their health. It also tells whether they need similar treatment or not. For example, a heart patient who follows a healthy lifestyle does not need the same medication level compared to someone who does not.

Benefits of Personalized Medicine

• Improved treatment outcomes: Doctors can achieve quality patient care and positive outcomes for each patient by considering all the different factors mentioned above. 
• Reduced side effects: Customized treatments reduce any side effects that traditional medicine may cause.
• Enhanced patient satisfaction: Personalized treatment increases patients' satisfaction and trust in hospitals' services.
• Cost-effective: Optimizing treatment plans also reduces healthcare costs for diagnosis, medical imaging, lab tests, and more, making healthcare services affordable to all. 

AI in Personalized Medicine: How Does it Help Healthcare Providers? 

Precision medicine benefits healthcare providers and patients only when they have accurate data. The healthcare industry generates tons of data daily. From genomic sequences to wearable devices to EHRs, traditionally, analyzing these large and complex data sets is difficult. 

Moreover, healthcare data is often siloed and trapped in various systems across hospitals, clinics, and labs. Consolidating this data in one place, segregating the different types of suitable data for analysis, transforming unstructured to structured data, and reaching a meaningful conclusion is a big challenge. 

Here's how AI is converting this challenge into new opportunities for the healthcare industry: 

1. Analyzing Complex Data

Unlike traditional systems, which have limited processing capacity, AI is limitless. Through deep learning and machine learning, it can deal with both high-volume and complex data.

2. Predicting Responses

AI algorithms have predictive power beyond human capabilities. This is especially useful in medical diagnosis, where effective outcomes can save a patient's life from life-threatening diseases like cancer. Not just diagnosis, doctors can find the treatment that works the best for the patients, improving survival rates.

3. Developing Precision Drugs and Therapies

Personalized medicine begins with developing drugs specific for a particular group of patients with similar lifestyle, genetic, and health profiles. AI helps pharmaceutical companies manufacture such drugs faster, bringing more precision to treatments and medications.

4. Optimizing Dosage

Identifying the best treatment, therapy, and medicine is only one part of the equation; prescribing accurate dosage is also important. In personalized medicine, AI also helps minimize the chances of overdose or side effects. 

5. Continuous Monitoring and Real-Time Adjustments

Using artificial intelligence in medical diagnosis requires fresh data. This data can come from wearable devices and health apps that continuously monitor patient vitals such as heart rate and blood pressure. Through these insights, doctors can modify prescriptions and treatment plans according to patients' real-time conditions. 

6. Root-Cause Analysis

Traditional medicine only treats patients' symptoms and not the root cause. Using AI in personalized medicine will help identify the actual cause of symptoms, making treatments more effective. It also relieves patients from multiple diagnoses and unnecessary spending on ineffective treatments.

7. Patient Engagement

AI empowers patients to not blindly believe the prescribed medicines and treatment but rather check their recovery progress on their own. AI-driven chatbots and virtual assistants can educate them about alternative treatment options and preventive measures. 

This instant access gives them better control over their treatment journey. AI in patient care also brings transparency, empowering patients to hold healthcare providers accountable.

Challenges of Using AI in Medicine and Healthcare

The benefits of AI-powered treatment are clear: improved treatment efficacy, fewer side effects, and faster recovery. But do not overlook the challenges it brings along with these benefits. 

Data privacy will always be a sensitive area of the healthcare industry. Every new technology entering this industry needs to take good care of data, including patients' personal information and health data. 

From extracting, storing, and cleaning to analyzing, healthcare providers using artificial intelligence in medical diagnosis should ensure its protection and responsible usage. The healthcare industry cannot afford to be biased in treatment, patient care, or operations. However, AI models can be biased, specifically when trained on incomplete, poor, or generic data. 

Regulatory and ethical considerations will also be a double-edged sword. While regulations will promote AI's safe and ethical use in patient care, they will restrict innovation and accessibility. How?

• Healthcare regulations like GDPR and HIPAA may require healthcare providers to explain how AI algorithms reach high-stakes medical decisions.
• Regulations will also penalize AI solutions for patient care that discriminate against certain patient groups.
• AI-powered medical devices, chatbots, and software must undergo strict clinical trials and approval.
• It will also require more transparency in healthcare services to keep patients aware of the use of AI in patient care and treatment. 

Striking the right balance between AI and regulation will be crucial for healthcare providers. 

Final Thoughts 

AI will bring healthcare providers closer to their goal of offering high-quality patient care. With AI-powered personalized medicine, treatments would be more patient-centric rather than symptom-centric. For hospitals, AI will reduce hospital readmission rates, improve their reputation, bring greater patient satisfaction, and minimize side effects. 

However, these benefits are possible only with AI solutions that successfully beat the barriers of data privacy, regulations, and biases. Softude's AI experts help you overcome both technical and domain-specific barriers. Our AI solutions have been developed to make a bigger impact in the healthcare industry while balancing development costs and quality outcomes. Consult our experts for more information.