Model based dose personalization in clinical trials

Personalized medicine is an important area of medical research which consists of designing therapies specifically for a patient or a group of patients. For drugs having a narrow therapeutic index or for vulnerable patients, methods such as therapeutic drug monitoring are used in a hospital setting to ensure that the blood concentration of the drug is maintained within a pre-decided range. However, such methods can not be used for drugs which are still in the developmental phase since, generally, insufficient information is available about the pharmacokinetic behaviour of the drug.

In this paper, we present a new methodology for explicit optimization of dose regimens during the course of the pharmacokinetic studies such that the resultant blood concentration of the drug in each subject is maintained around a desired target concentration or within a target range.

We demonstrate that our algorithm is able to achieve the clinical objective of PK estimation while simultaneously individualizing the dose to every subject in the trial. Our algorithm computes dose regimens that, on average, have a relative efficiency of 97% with a standard deviation of less than 5%. The results show that the algorithm can be relied upon to ensure that the subjects in the trial are minimally over- and under-exposed to the test therapy.

The proposed methodology can assist in ensuring correct dosing to each subject in a clinical trial so that each subject receives only the intended exposure to the drug while simultaneously estimating the PK profile of the drug. Our methodology can also be applied in randomized concentration-controlled trials where maintenance of the target concentration in the subjects is a fundamental requirement for conducting these trials.