With the evolution of artificial intelligence (AI), personalized medicine will finally be a reality with AI helping to tackle the vast amount of patient data collected and analyzed from sequencing a patient genome. AI will be used to identify patterns within the high volume of genetic data sets, allowing for the prediction of a patient’s probability of developing certain diseases or assisting physicians with designing potential therapies. AI will be used to help physicians predict how tumors will evolve following treatment, allowing physicians to change the course of treatment if the tumor develops a resistance. AI could be used as a predictive prognostic tool to develop links between DNA mutations and known outcomes. Early detection of certain troubling genes could allow physicians to use CRISPR for gene editing of the target sequence.


AI for the detection of Cancer

Studies done on the error rates of cancer diagnosis has found that as much as 1 in 4 suffers from inadequate physical examinations and incomplete diagnostic tests. AI will fix this! AI will soon be able to be linked to tools that are able to analyze compounds in the human breath, detecting illnesses like cancer. AI tools have been and will continue to be trained with data from patients with various types of cancers. Cancers produce a distinctive smell of volatile organic compounds. AI will one day be able to decipher through normal chemical compounds in breath samples to identify those being emitted by the tumor. AI detection tools will not be used to replace physicians, but rather it will function as a supportive tool to help confirm their conclusions. The AI tool will be able to take minutes to autonomously analyze a breath sample that traditionally takes physicians hours to analyze.


AI for predicting stable dose treatments

In many diseases like cancer, there is a very narrow window in which a therapeutic agent will prove to be effective. Insufficient dosing or targeting is often associated with higher rates of toxicities or metastasis.  Therefore, there is an increasing need to develop strategies for determining appropriate doses and dosing windows. There are many factors that affect the pharmacokinetics of detecting an appropriate dose or dosing window including ethnicity, age, gender, concomitant medication, and weight. AI could be used to investigate the clinical and genetic factors significantly associated with the appropriate dosing and timing.


Empowering, the patient

 AI in combination with blockchain and the Internet of Things will help patients to play a more active role in their health. Patients will soon have their records stored on a single platform for all of their doctors to access when diagnosing and prescribing medication. Patients will soon be able to leverage IoT tools to help monitor their glucose levels and heart rates, allowing for patients to respond to potential issues earlier. By having the power in their fingertips, patients can obtain reliable second and third opinions by granting access to all of their medical records in Realtime.




              There is a fear that AI will soon take over the world, displacing humans in the market place. This fear is becoming warranted with the emergence of self-driving cars, shopping cart recommendations, and manufacturing robots. It is further supported by the fact that machines are projected to replace 800 million jobs by 2030. Though these may come true, I think that AI will not replace humans but will rather become a mere tool for our use. As I’ve discussed, I think that AI will help transform the way we approach human. AI will allow us to identify potential diseases by analyzing the human genome. Early detection is critical and helps prevent patients from dying from diseases that are curable in its early stages, using gene editing tools.  It will also allow doctors to develop personalized solutions for conditions like cancer. We know that each human body is different and requires different approaches for each human being. AI will change the way we assist human beings.