I think you can go for of these approaches:

1. cluster your data based on the specified features and then you will be able to identify each group/cluster average, maximum, minimum, ....etc drug dosage. then you can judge any instance by how far it is from it`s cluster mean(far by n-Standard deviations) then decide that the instances that fall 3-sd(Standard deviations) are anomaly and need to be adjusted.

2. Use Anomaly detection techniques which will help you detect different/extreme behavior in data.

I think you can go for one of these approaches:

1. cluster your data based on the specified features and then you will be able to identify each group/cluster average, maximum, minimum, ....etc drug dosage. then you can judge any instance by how far it is from it`s cluster mean(far by n-Standard deviations) then decide that the instances that fall 3-sd(Standard deviations) are anomaly and need to be adjusted.

2. Use Anomaly detection techniques which will help you detect different/extreme behavior in data.