For years, it has been believed that the future of medicine and patient treatment lies within personalized medicine and the up-and-coming field of pharmacogenetics. Instead of treating medicine as a one-size-fits-all policy, personalized medicine can tailor disease treatments to a patient’s unique genetic makeup, as well as how their body processes a drug. This targeted approach to patient care could make ineffective treatments a thing of the past. However, large issues arise in workforce shortages as well as technological barriers. 

Pharmacogenetics considers a patient’s genetic differences and how they impact their response to medications. This is especially crucial for patients on multiple drugs, for whom providers must ensure there will be no harmful drug interactions when prescribing new treatments. Traditionally, this can require multiple rounds of trial and error to find a safe, effective dose for each patient, requiring significant time for every individual case. So, widespread implementation has not yet been possible. This is where quantum computing comes in. Unlike normal computers, quantum computers can explore many possibilities simultaneously, significantly cutting down the time required. In tasks like drug discovery, where there are billions of possible combinations to test, quantum computing could take just minutes to explore all of these instead of years, reducing the strain on researchers. 

A research team from Spain led by Dr. Adrián Llerena took on this challenge and developed a quantum pharmacogenomics model that can be integrated with existing healthcare systems. Titled QHealth, the project incorporates genetic and physiological conditions along with a patient’s full medication history and their response to each drug. Addressing every individual variability of a patient seems impossible in our current pharmacology practices, but it is made possible through quantum computing. The QHealth system is able to consider thousands of pharmaceutical treatment options in real time and provide the optimal drug dosage as well as potential adverse reactions or inefficacies that could occur. This reduces the appointments needed to alter prescriptions and test multiple drugs, giving physicians the ability to increase the amount of patients they see. 

Utilizing quantum computers has the potential to reduce the risk of complications and ineffective treatment for all patients…

Llerena and his colleagues then worked to integrate this system into current healthcare practice systems. The system will gather patient information from a chart, including everything from genetic testing and lab results to symptoms and diagnoses. All of these factors are used as input for the computer, and the system explores thousands of drug dosage combinations simultaneously. The quantum computer aims to find the optimal balance between medication safety and efficacy for the patient and quickly narrows down the options. Ultimately, the system is able to give the most optimal drug and dosage to the practicing physician as well as warnings about patient-specific potential drug interactions that could lead to a reaction. These inquiries could happen during patient appointments, as the quantum computer only needs seconds to analyze drug interactions and overall has the potential to reduce the “trial and error” prescriptions required to find a successful combination. Quantum computers have the potential to reduce the risk of complications and ineffective treatment for all patients, but especially those on multiple medications with higher chances of drug interactions. In the coming years, precision medicine will likely become standard practice, and quantum computing has the ability to transform this currently exhausting ordeal of deciding and dosing medication into a rapid, precise process.