OptiDose: Computing the Individualized Optimal Drug Dosing Regimen Using Optimal Control

Computing optimal drug dosing with OptiDose: implementation in NONMEM

Determining a drug dosing recommendation with a PKPD model can be a laborious and complex task. Recently, an optimal dosing algorithm (OptiDose) was developed to compute the optimal doses for any pharmacometrics/PKPD model for a given dosing scenario. In the present work, we reformulate the underlying optimal control problem and elaborate how to solve it with standard commands in the software NONMEM. To demonstrate the potential of the OptiDose implementation in NONMEM, four relevant but substantially different optimal dosing tasks are solved. In addition, the impact of different dosing scenarios as well as the choice of the therapeutic goal on the computed optimal doses are discussed.

Clinically practical pharmacometrics computer model to evaluate and personalize pharmacotherapy in pediatric rare diseases: application to Graves' disease

Objectives

Graves' disease (GD) with onset in childhood or adolescence is a rare disease (ORPHA:525731). Current pharmacotherapeutic approaches use antithyroid drugs, such as carbimazole, as monotherapy or in combination with thyroxine hormone substitutes, such as levothyroxine, as block-and-replace therapy to normalize thyroid function and improve patients' quality of life. However, in the context of fluctuating disease activity, especially during puberty, a considerable proportion of pediatric patients with GD is suffering from thyroid hormone concentrations outside the therapeutic reference ranges. Our main goal was to develop a clinically practical pharmacometrics computer model that characterizes and predicts individual disease activity in children with various severity of GD under pharmacotherapy.

Methods

Retrospectively collected clinical data from children and adolescents with GD under up to two years of treatment at four different pediatric hospitals in Switzerland were analyzed. Development of the pharmacometrics computer model is based on the non-linear mixed effects approach accounting for inter-individual variability and incorporating individual patient characteristics. Disease severity groups were defined based on free thyroxine (FT4) measurements at diagnosis.

Results

Data from 44 children with GD (75% female, median age 11 years, 62% receiving monotherapy) were analyzed. FT4 measurements were collected in 13, 15, and 16 pediatric patients with mild, moderate, or severe GD, with a median FT4 at diagnosis of 59.9 pmol/l (IQR 48.4, 76.8), and a total of 494 FT4 measurements during a median follow-up of 1.89 years (IQR 1.69, 1.97). We observed no notable difference between severity groups in terms of patient characteristics, daily carbimazole starting doses, and patient years. The final pharmacometrics computer model was developed based on FT4 measurements and on carbimazole or on carbimazole and levothyroxine doses involving two clinically relevant covariate effects: age at diagnosis and disease severity.

Discussion

We present a tailored pharmacometrics computer model that is able to describe individual FT4 dynamics under both, carbimazole monotherapy and carbimazole/levothyroxine block-and-replace therapy accounting for inter-individual disease progression and treatment response in children and adolescents with GD. Such clinically practical and predictive computer model has the potential to facilitate and enhance personalized pharmacotherapy in pediatric GD, reducing over- and underdosing and avoiding negative short- and long-term consequences. Prospective randomized validation trials are warranted to further validate and fine-tune computer-supported personalized dosing in pediatric GD and other rare pediatric diseases.

Approach to the Patient With Congenital Hypothyroidism

Congenital hypothyroidism (CH) is the most frequent neonatal endocrine disorder and the most common preventable cause of development delay and growth failure if diagnosed and treated early. The thyroid is the first endocrine gland to develop during embryonic life and to be recognizable in humans. Thyroid development and maturation can be divided into 2 phases: a first phase of embryogenesis and a second phase of folliculogenesis and differentiation with thyroid hormone production at the final steps. Regulation of the thyroid function requires normal development of the hypothalamic-pituitary-thyroid axis, which occurs during the embryonic and neonatal period. Defects in any of steps of thyroid development, differentiation, and regulation lead to permanent CH. Newborn screening programs, established in only one-third of countries worldwide, detect CH and are cost-effective and highly sensitive and specific. During the last decade, epidemiology of CH has changed with increased frequency of thyroid in situ in primary CH. Advances in molecular testing have expanded knowledge and understanding of thyroid development and function. However, a molecular cause is identified in only 5% of CH due to thyroid dysgenesis. The purpose of this article is to describe the clinical approach to the child with CH, focusing on diagnostic work-up and future challenges on optimizing thyroid replacement therapy and regenerative medicine. The review is written from the perspective of the case of 2 girls referred for CH after newborn screening and diagnosed with thyroid ectopy. The genetic work-up revealed novel mutations in TUBB1 gene, associated with large platelets and abnormal platelet physiology.

Optimal control in pharmacokinetic drug administration

We consider a two-box model for the administration of a therapeutic substance and discuss two scenarios: First, the substance should have an optimal therapeutic concentration in the central compartment (typically blood) and be degraded in an organ, the peripheral compartment (e.g., the liver). In the other scenario, the concentration in the peripheral compartment should be optimized, with the blood serving only as a means of transport. In either case the corresponding optimal control problem is to determine a dosing schedule, i.e., how to administer the substance as a function u of time to the central compartment so that the concentration of the drug in the central or in the peripheral compartment remains as closely as possible at its optimal therapeutic level. We solve the optimal control problem for the central compartment explicitly by using the calculus of variations and the Laplace transform. We briefly discuss the effect of the approximation of the Dirac delta distribution by a bolus. The optimal control function u for the central compartment satisfies automatically the condition u≥0. But for the peripheral compartment one has to solve an optimal control problem with the non-linear constraint u≥0. This problem does not seem to be widely studied in the current literature in the context of pharmacokinetics. We discuss this question and propose two approximate solutions which are easy to compute. Finally we use Pontryagin's Minimum Principle to deduce the exact solution for the peripheral compartment.