Drug concentration prediction and delivery

In medical practice, the decision-making process regarding drug dose is critical to patients’ health and recovery. For drugs with narrow therapeutic ranges, the medical doctor decides the quantity (dose amount) and frequency (dose interval) on the basis of a set of patients’ parameters. Computer-aided tools for drug dose administration makes the prescription procedure faster, more accurate, more objective, and less expensive. We describe an advanced integrated Drug Administration Decision Support System (DADSS) to help clinicians/patients with the dose/frequency computing. Based on a support vector machine (SVM) algorithm, enhanced with the random sample consensus technique, this system is able to predict the drug concentration values and computes the ideal dose amount and dose interval for a new patient. With an extension to combine the SVM method and the explicit analytical model, the advanced integrated DADSS system is able to compute drug concentration-to-time curves for a patient under different conditions.