Abstract
Prior to his passing, Dr. Roger Jelliffe, expressed the need for educating future physicians and clinical pharmacists on the availability of computer-based tools to support dose optimization in patients in stable or unstable physiological states. His perspectives were to be captured in a commentary for the AAPS J with a focus on incorporating population pharmacokinetic (PK)/pharmacodynamic (PD) models that are designed to hit the therapeutic target with maximal precision. Unfortunately, knowing that he would be unable to complete this project, Dr. Jelliffe requested that a manuscript conveying his concerns be completed upon his passing. With this in mind, this final installment of the AAPS J theme issue titled “Alternative Perspectives for Evaluating Drug Exposure Characteristics in a Population — Avoiding Analysis Pitfalls and Pigeonholes” is an effort to honor Dr. Jelliffe’s request, conveying his concerns and the need to incorporate modeling and simulation into the training of physicians and clinical pharmacists. Accordingly, Dr. Jelliffe’s perspectives have been integrated with those of the other three co-authors on the following topics: the clinical utility of population PK models; the role of multiple model (MM) dosage regimens to identify an optimal dose for an individual; tools for determining dosing regimens in renal dialysis patients (or undergoing other therapies that modulate renal clearance); methods to analyze and track drug PK in acutely ill patients presenting with high inter-occasion variability; implementation of a 2-cycle approach to minimize the duration between blood samples taken to estimate the changing PK in an acutely ill patient and for the generation of therapeutic decisions in advance for each dosing cycle based on an analysis of the previous cycle; and the importance of expressing therapeutic drug monitoring results as 1/variance rather than as the coefficient of variation. Examples showcase why, irrespective of the overall approach, the combination of therapeutic drug monitoring and computer-informed precision dosing is indispensable for maximizing the likelihood of achieving the target drug concentrations in the individual patient.
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Funding
Dr. Jelliffe’s work was supported over many years in part by National Institutes of Health RO1 grants GM068968, HD070886, EB005803, GM65619, LM05401, RR11526, and by the Stella Slutsky Kunin Fund. He also expressed gratitude for the evaluations by Dr. Alan Tartakoff, Dr. Ellen Rothchild, and others.
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Dr. Martinez was responsible for conveying the many discussions with Dr. Jelliffe on the topics covered in this review and was primarily responsible for the developing the contents of this manuscript. Dr. Liu was responsible for providing his pharmacometrics insights and expertise during the manuscript development. Dr. Drusano was responsible for providing his insights, experience, and expertise in the use of pharmacometric tools as a component of patient care and his experience as a university professor responsible for the medical student education on the use of PK as a component of dosage recommendation.
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Drs. Martinez and Lu are employed by the US FDA and has no conflicts of interest to report. Dr. Drusano has no conflicts to report.
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Jelliffe, R., Liu, J., Drusano, G.L. et al. Individualized Patient Care Through Model-Informed Precision Dosing: Reflections on Training Future Practitioners. AAPS J 24, 117 (2022). https://doi.org/10.1208/s12248-022-00769-z
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DOI: https://doi.org/10.1208/s12248-022-00769-z