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Methodologies for dose individualization based on calculation of individual pharmacokinetic parameters and PK/PD targets (AUC/MIC) are available but not widely adopted in clinical practice [ 103].
Treatment individualization based on specific molecular biomarkers is becoming increasingly important in oncology.
Current nutrition recommendations advise individualization based on treatment goals, physiologic parameters, and medication usage.
However, dose individualization based on these covariates would achieve little clinical benefit in the scenarios explored.
Relevant outcome measures, such as overall programme performance, cancellation rates and costs, will in concert help to determine the true value of treatment individualization based on response prediction.
For most cancers and cancer subgroups, no biomarkers and effective targeted therapy are available and therefore the great majority of patients still receive standard therapies with no individualization based on their tumor's molecular characteristics.
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Abstraction also (iv) masks the lag-times of distribution processes and (v) does not allow the integration of an individualization framework based on patient physiology.
The individualization of treatment based on syndrome differentiation is one feature of TCM treatment, and there are diverse combinations of therapeutic techniques.
With further refinement, imaging predictors of response could play an important role in oncology, contributing to individualization of therapy based on the specific tumour phenotype.
This paper suggests that Mass-Individualization, which is based on a consumer product that consists of an open hardware platform and multiple modules that are interfaced with the platform, will constitute the next paradigm in product design.
Individualization of DBS parameters based on neural oscillations may optimize the clinical benefits of DBS.
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