JP-7855069-B2 - Methods, systems, and computer programs for calculating optimal individual dosing plans, especially those constrained by clinical limitations.

Inventors

• ジンナイ，ガボール
• コッホ，ギルバート
• フィスター，マルク
• シュロップ，ヨハネス
• ステフェンス，ブリッタ
• バッハマン，フレイヤ

Assignees

• ウニヴェルズィテート バーゼル
• ウニヴェルズィテート コンスタンス

Dates

Publication Date

20260507

Application Date

20221104

Priority Date

20211104

Claims (13)

1. A computer-based method for determining an optimal individualized dosing plan for at least one drug for a patient with a known disease associated with a disease progression model that follows a nonlinear mixed-effects modeling approach called the NLME modeling approach, wherein the method is: (a) Accessing a mathematical model adapted to model the disease progression of the disease, wherein the mathematical model includes a basic mathematical model involving the application of an NLME modeling approach to describe a given population of patients by its population parameters, covariates, and parameter distributions, and the basic mathematical model is a pharmacokinetic or pharmacokinetic/pharmacodynamic model characterized by one or more differential equations including disease state as a variable characterizing disease progression, (b) Using empirical Bayesian estimation, calculate estimated individual model parameters for patients belonging to the given population by maximizing the conditional probability density function of individuals having the population parameters and the patient data of the patients, based on the patient data and the mathematical model. (c) Calculating the optimal individual dosing plan for the patient by solving the optimal control problem using an optimal control algorithm, by minimizing the cost functional that characterizes the difference between the disease state and the desired disease progression based on the mathematical model and the patient's individual model parameters, and by starting with an initial control corresponding to the initial estimation for the dosing plan, The steps include performing method.
2. (d) The method of claim 1, further comprising adjusting an optimal individual dosing plan between two available doses, taking into account at least one clinical constraint, and rounding to the nearest available dose size, or selecting the higher or lower available dose based on the lower corresponding cost functional value, thereby resulting in the optimal individual dosing plan conditioned on at least one clinical constraint.
3. The method according to claim 1, wherein the desired disease progression is given in the form of a mathematical function.
4. The method according to claim 1, wherein at least a portion of the algorithm that performs steps (b) to (c) is approximated by an artificial neural network (ANN).
5. The method according to claim 1, wherein the disease is one of the following: acquired hypothyroidism, more specifically autoimmune and/or non-autoimmune; acquired hyperthyroidism, more specifically autoimmune and/or non-autoimmune; congenital hypothyroidism; or congenital hyperthyroidism.
6. The method according to claim 1, wherein the at least one drug is selected from the group consisting of levothyroxine, carbimazole, and propylthiouracil.
7. The method according to claim 1, wherein at least a portion of the patient data is measured by a wearable device worn by the patient.
8. The method according to claim 7, wherein the wearable device is a wristwatch, more particularly a smartwatch, a mobile phone, and more particularly a smartphone.
9. The method according to claim 7 or 8, wherein the patient data includes heart rate, and the patient's heart rate is measured by the wearable device.
10. A computer system for determining an optimal personalized dosing plan for at least one drug for a patient suffering from a known disease associated with a disease progression model following a nonlinear mixed-effects modeling approach, the system comprising at least one processor configured to perform the steps of the method performed by a computer according to claim 1.
11. The system according to claim 10, further comprising a wearable device configured to measure at least a portion of the patient data.
12. A computer program for determining an optimal personalized dosing plan for at least one drug to a patient suffering from a known disease associated with a disease progression model following a nonlinear mixed-effects modeling approach, wherein the computer program includes instructions, the instructions, when executed on the system according to claim 10, cause the system to perform the method according to claim 1.
13. A computer-readable persistent storage medium on which the computer program according to claim 12 is stored.

Description

This invention relates to a method, system, and computer program for determining an optimal administration plan for at least one drug to a patient suffering from a known disease. For the vast majority of diseases, individualized treatment remains challenging because disease progression varies among patients and clinical settings. Specifically, determining the optimal individualized treatment plan—particularly in a clinical setting—in a sufficiently rapid and reliable manner to ideally enable control of disease progression, leading to patient recovery while minimizing treatment-related adverse events, often remains a challenge. In detail, among these diseases, congenital hypothyroidism is the most common congenital endocrine disorder globally and the most common preventable cause of intellectual disability [Polak 2017]. Disease severity varies greatly from person to person at the time of diagnosis; thyroid-stimulating hormone (TSH) levels range from 6 to 1200 mU/L, while the standard range is 0.5–5 mU/L. The main effects of thyroid hormones are axonal growth and myelin formation of interneurons, processes that are ongoing in humans, mainly after birth. Neonatal screening allows for the diagnosis of children with congenital hypothyroidism before they suffer from clinical signs and irreversible neurological defects. Over the past 40 years, neurological outcomes for patients with congenital hypothyroidism have been significantly improved by 1) shortening the time window between screening and treatment initiation (currently 4-5 days in Switzerland) and 2) increasing the initial dose of levothyroxine (from 5-8 mcg/kg/day to 10-15 mcg/kg/day). The goal of alternative therapy with levothyroxine is to correct hypothyroidism as quickly as possible to protect brain development. Clinicians aim for free thyroxine (T4) levels to reach the upper limit of the normal reference range within 14 days (see Figure 3(a)). However, several studies have revealed that up to 10% of children were overdosed on initial and maintenance doses of 10-15 mcg/kg/day for longer than the appropriate period. Furthermore, at age 11, their neurological outcomes were comparable to those of children with periods of underdose during follow-up, and both children with overdose and underdose had poorer neurological outcomes compared to children with levothyroxine doses that maintained thyroid hormone levels within the reference range during follow-up. Current international guidelines recommend more frequent monitoring during the first two years of life to maintain thyroid hormone levels within the physiologically normal reference range, allowing for more frequent and necessary adjustments to the individual's age-appropriate dosage. While this allows for faster detection of overdoses and underdoses, it does not prevent episodes of suboptimal dosage. Consequently, the final step to improving neurological outcomes in affected patients should focus on optimizing alternative dosing over the long term by considering clinical and research data for individualized dosing during follow-up. Therefore, being able to determine the optimal individualized dosing during the first two years of life is particularly desirable, as it is essential for brain development and long-term normal cognitive function. Central congenital hypothyroidism is a subgroup of congenital hypothyroidism with low TSH and FT4 levels resulting from pituitary and hypothalamic dysfunction, treated in the same manner with levothyroxine. Furthermore, congenital hyperthyroidism occurs in approximately 10% of newborns of mothers with autoimmune hyperthyroidism (Graves' disease), resulting from the placental transfer of stimulating antibodies against thyroid-stimulating hormone (TSH) receptors. It exposes infants to significant risk of morbidity and mortality. In contrast to infants with congenital hypothyroidism, who are asymptomatic in about 95% of cases at birth and during the first week of life, infants with congenital hyperthyroidism present with typical signs and symptoms ranging from mild tachycardia and sweating to weight loss, vomiting, diarrhea, dehydration, severe fever, epileptic seizures, and heart failure. Onset can occur immediately after birth or be delayed until 4-10 days postpartum due to the placental transfer of maternal antithyroid medications. Again, the severity of the disease varies greatly, from extremely mild forms to life-threatening complications. Delayed onset further complicates optimal treatment, necessitating clinical observation and laboratory monitoring at 1, 4, 7, 10, and 14 days postnatally. Furthermore, for congenital hyperthyroidism, optimizing treatment by predicting which children are at risk of a severe clinical course and when treatment should be initiated, and by finding the minimum effective initiation and maintenance doses appropriate to the severity of the disease, given the potential for serious side effects of antithyroid drugs (agranulocytosis, hepatitis