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RecruitingNCT06321120Updated Mar 20, 2024

Using Chronobiology to Improve Lenvatinib Efficacy

An Early Phase 1 interventional study of variability-based lenvatinib regimen in Lenvatinib Treatment, sponsored by Hadassah Medical Organization. Recruiting at 1 site in Israel. Open to participants aged 18 Years to 80 Years. Per ClinicalTrials.gov, last updated 2024-03-20.

Sponsored by Hadassah Medical Organization · Early Phase 1, Interventional, and Treatment

From the registry’s dates

  • Primary completion was expected by Apr 2024, 2 years 6 months ago, but the record still lists the study as recruiting.
  • Registered 1 year after the study started (first participant enrolled Mar 2023, registered Mar 2024).
  • Started Mar 2023; still recruiting 3 years 7 months later.
Phase
Early Phase 1
Study type
Interventional
Enrollment
10
Allocation
Not applicable
Ages
18 Years to 80 Years
Sex
All
01

Study 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.

Read the 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.

02

Conditions studied

  • Lenvatinib Treatment

Keywords

  • cancer
  • lenvatinib
  • constrained disorder principle
  • digital pill
03

In context

Lead sponsor

Hadassah Medical Organization is the lead sponsor of 659 studies on the registry; 54 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 80 Years
Sexes eligible
All
Accepts healthy volunteers
No

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

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.
05

Study design

Phase
Early Phase 1
Primary purpose
Treatment
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
10 participants (estimated)

Study arms

  • Experimental
    Variability-based lenvatinib treatment

    Dosages and administration times were tailored within individual predefined ranges to accommodate personalized therapeutic regimens. The first level of the algorithm, employed in the present study, utilizes a pseudo-random number generator to select dosages and administration times from the ranges stipulated by the physician.

    Drug: variability-based lenvatinib regimen

Interventions

  • Drugvariability-based lenvatinib regimen

    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.

06

What researchers measure

Primary outcomes

  1. disease progression/ tumor response

    tumor response according to positron emission tomography-computed tomography (PET-CT) and tumor markers (thyroglobulin)

    Time frame: at enrollment and at study completion (14 weeks later)

Secondary outcomes

  1. Adverse effects occurrence

    Safety assessments are performed throughout the study and include the recording of symptoms and emergency room visits or hospitalizations through a regular monthly telephone check-up and a hospital and ambulatory medical records review. Additionally, patients can report AEs online via the application. Hematological and biochemical laboratory testing, urinalysis, and self-conducted home blood pressure monitoring are also executed.

    Time frame: Blood tests will be drawn at enrollment and at study completion (14 weeks later). Telephone check-ups will be conducted monthly during the follow-up.

07

Study locations

1 of 1 sites recruiting
  • Hadassah Medical Organization
    Jerusalem, 91120, Israel
    Recruiting
08

References and documents

Publications

  • Schlumberger M, Tahara M, Wirth LJ, Robinson B, Brose MS, Elisei R, Habra MA, Newbold K, Shah MH, Hoff AO, Gianoukakis AG, Kiyota N, Taylor MH, Kim SB, Krzyzanowska MK, Dutcus CE, de las Heras B, Zhu J, Sherman SI. Lenvatinib versus placebo in radioiodine-refractory thyroid cancer. N Engl J Med. 2015 Feb 12;372(7):621-30. doi: 10.1056/NEJMoa1406470. PubMed 25671254 ↗
  • Gelman R, Hurvitz N, Nesserat R, Kolben Y, Nachman D, Jamil K, Agus S, Asleh R, Amir O, Berg M, Ilan Y. A second-generation artificial intelligence-based therapeutic regimen improves diuretic resistance in heart failure: Results of a feasibility open-labeled clinical trial. Biomed Pharmacother. 2023 May;161:114334. doi: 10.1016/j.biopha.2023.114334. Epub 2023 Mar 9. PubMed 36905809 ↗
  • Ilan Y. Overcoming Compensatory Mechanisms toward Chronic Drug Administration to Ensure Long-Term, Sustainable Beneficial Effects. Mol Ther Methods Clin Dev. 2020 Jun 10;18:335-344. doi: 10.1016/j.omtm.2020.06.006. eCollection 2020 Sep 11. PubMed 32671136 ↗
  • Ilan Y, Spigelman Z. Establishing patient-tailored variability-based paradigms for anti-cancer therapy: Using the inherent trajectories which underlie cancer for overcoming drug resistance. Cancer Treat Res Commun. 2020;25:100240. doi: 10.1016/j.ctarc.2020.100240. Epub 2020 Nov 19. PubMed 33246316 ↗

Individual participant data

Plan to share: No — irrelevant

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Mar 20, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT06321120
Lead sponsor
Hadassah Medical Organization
Responsible party
Sponsor
First posted
Mar 20, 2024
Start date
Mar 1, 2023
Primary completion
Apr 2024 (estimated)
Completion
Jun 2024 (estimated)
Last update
Mar 20, 2024

Study contacts

Aharon Popovtzer, MD
Contact
ARON@HADASSAH.ORG.IL
972509010225
Tal Sigawi, MD
Contact
SIGAW@HADASSAH.ORG.IL
09725115691

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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