Treatment and Intervention Effectiveness Forecasting

Understanding treatment and intervention effectiveness is an essential research topic for achieving optimal patient outcomes and advancing precision medicine. This requires analysing various data types, including clinico-demographic data and real-world data. Being able to forecast the likely effectiveness of a treatment or intervention for an individual is crucial to improve success probabilities of treatments.

Typical quantum computing paradigms that can be mapped onto these kind of problems are quantum machine learning algorithms. There are for example studies that have applied Quantum Neural Networks (QNNs). One study predicted drug response by deriving IC50 values using QNNs, and another used QNNs with clinico-demographic data to forecast knee arthroplasty effectiveness.

Forecasting treatment effectiveness supports the journey towards precision medicine and aims to help individuals achieve optimal outcomes. Early results using QNNs were encouraging. This work demonstrates the potential of quantum algorithms in predicting treatment success.