Using Chronobiology to Improve Lenvatinib Efficacy

Trial Title: Using Chronobiology to Improve Lenvatinib Efficacy

NCT ID: NCT06321120

Condition: Lenvatinib Treatment

Conditions: Official terms:
Lenvatinib

Conditions: Keywords:
cancer
lenvatinib
constrained disorder principle
digital pill

Study type: Interventional

Study phase: Early Phase 1

Overall status: Recruiting

Study design:

Allocation: N/A

Intervention model: Single Group Assignment

Intervention model description: An open-labeled, prospective, single-center proof-of-concept clinical trial lasting 14 weeks was conducted to investigate the impact of an algorithm-based regimen on enhancing lenvatinib effectiveness.

Primary purpose: Treatment

Masking: None (Open Label)

Intervention:

Intervention type: Drug
Intervention name: variability-based lenvatinib regimen
Description: Dosages and administration times were tailored within individual predefined ranges to accommodate personalized therapeutic regimens. As per protocol, the daily dose was limited to match or remain below the patients' pre-enrollment dosage level. In the initial 4 weeks of the follow-up, participants followed a fixed standard regimen with the app serving as a reminder, allowing for an adaptation period. Subsequently, the algorithm-driven treatment plan was implemented for an additional 10 weeks.
Arm group label: Variability-based lenvatinib treatment

Summary: The goal of this proof-of-concept clinical trial is to assess the efficacy and safety of chronobiology implementation into lenvatinib treatment regimens of thyroid cancer patients, via a mobile application. Participants will use a mobile application to follow variability-based physician approved drug administration schedules.

Detailed description: Systemic treatments for thyroid cancer have emerged in the past decade, accompanied by a deeper understanding of its underlying molecular mechanisms. Among these, lenvatinib, a multi-targeted tyrosine kinase inhibitor, was approved as a monotherapy for treating locally advanced or metastatic radioactive iodine refractory differentiated thyroid cancer. Despite its efficacy, lenvatinib is associated with a spectrum of adverse events (AEs), including hypertension, fatigue, proteinuria, and gastrointestinal disturbances, which often necessitate dose reduction, interruption, or permanent discontinuation. To overcome these challenges, the investigators address to the Constrained Disorder Principle (CDP), an innovative approach that emphasizes the exploration of constrained variability in treatment regimens to optimize drug effectiveness and minimize AEs. In other disease contexts, such as congestive heart failure, multiple sclerosis, and chronic pain, the integration of CDP-based second-generation artificial intelligence (AI) systems into treatment regimens has shown promising results in enhancing therapeutic outcomes by dynamically adjusting treatment parameters. The investigators hypothesize that a personalized dynamic adjustment of lenvatinib dosages and administration timing, guided by an AI-driven approach via a mobile application, may reduce AEs, improve adherence, and enhance overall treatment efficacy. In this proof-of-concept study, the investigators aim to evaluate the feasibility and efficacy of utilizing a CDP-based second-generation AI system to optimize the therapeutic regimen of lenvatinib in patients with cancer.

Criteria for eligibility:
Criteria:
Inclusion Criteria: 1. Age 18-80 years 2. Lenvatinib treated cancer patients, who suffer from loss of response of dose-limiting adverse effects. Exclusion Criteria: 1. Current or history of drug abuse 2. Pregnancy/lactation/planned pregnancy 3. The subject is currently enrolled in or has not yet completed at least 60 days since ending another investigational device or drug trial. 4. Unable to comply with study requirements.

Gender: All

Minimum age: 18 Years

Maximum age: 80 Years

Healthy volunteers: No

Locations:

Facility:
Name: Hadassah Medical Organization

Address:
City: Jerusalem
Zip: 91120
Country: Israel

Status: Recruiting

Contact:
Last name: Hadas Lemberg, PhD

Phone: +97226777572
Email: lhadas@hadassah.org.il

Start date: March 1, 2023

Completion date: June 2024

Lead sponsor:
Agency: Hadassah Medical Organization
Agency class: Other

Source: Hadassah Medical Organization

Record processing date: ClinicalTrials.gov processed this data on November 12, 2024

Source: ClinicalTrials.gov page: https://clinicaltrials.gov/ct2/show/NCT06321120