OPTImization of the Dose of tacroliMUS by Bayesian Prediction (OPTIMUS)

OPTIMIZATION of the Dose of tacroliMUS by Bayesian Prediction in Renal Transplant Patients Including Pharmacogenetic Variables

The pharmacokinetics of tacrolimus (TAC) are characterized by high inter- and intra-individual variability with narrow therapeutic range. Currently, the limiting point of Tac drug monitoring is the inability to individualize doses during the first few days after transplantation. Our group developed a population pharmacokinetic model (PPK) identifying CYP3A4 * 22 and CYP3A5 * 3 polymorphisms and hematocrit as explanatory variables of the observed variability in pre-dose (Co) concentrations. According to this model, the proportion of patients that do not reach the therapeutic target is 40

Study Overview

• Status: Completed
• Conditions: KIDNEY TRANSPLANTATION
• Intervention / Treatment: Drug: Standard dosage of Tacrolimus; Drug: Bayesian Prediction Tacrolimus dosage

Detailed Description

The results of the study of genetic polymorphisms performed in renal transplant patients at our hospital demonstrated the influence of CYP3A5 * 3 and CYP3A4 * 22 single nucleotide polymorphism (SNPs) on exposure to Tac. From these results, the first population pharmacokinetic model was developed, which included CYP3A5 * 3 and CYP3A4 * 22 polymorphisms as well as hematocrit as explanatory variables of interindividual variability. Based on our population model and using the simulation tool, the percentage of patients reaching the therapeutic target based on Co values within the range of 6-10 ng / mL was determined after being dosed according to the strategy of Conventional dosage empirically according to Co achieved. The simulation of 50 Co values according to the conventional dosage allowed to determine the proportion of patients reaching the therapeutic target in each case and their confidence interval. 40% of the patients did not reach the therapeutic objective. Based on the clusters of the two polymorphisms, the percentages of patients on or below exposed varied according to whether they were slow or fast metabolizers respectively. Due to this high variability in Tac PK, the individualization of the Tac posology was calculated by calculating the initial dose according to the population model previously developed and adjusting the subsequent doses, as a function of the Tac Co through Bayesian approximations with the inclusion of genotyping and Hematocrit, can contribute greatly to achieve optimal exposure to the drug from the start of treatment in the immediate post-transplant and reduce the variability observed in the Co-achieved; This may be particularly important for patients with a slow and rapid metabolizer profile. All of this may contribute to minimizing adverse effects, ensuring greater efficacy in the target population, reducing the risk of acute rejection, and reducing associated costs.

In the present study we intend to incorporate pharmacogenomics for its application in de novo patients, which will allow us to perform a more individualized therapy for each patient based on the values of target Co and the CYP3A5 * 3 and CYP3 A4 * 22 polymorphisms of the patient since The initiation of immunosuppressive therapy and thus improve efficiency and decrease adverse effects.

• Study Type: Interventional
• Enrollment (Actual): 96
• Phase: Phase 4

Contacts and Locations

Study Locations

• Spain
  • Barcelona, Spain
    • Hospital Universitari de la Vall d'Hebron
  • L'Hospitalet De Llobregat, Spain
    • Hospital Universitari de Bellvitge

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Kidney transplant recipients, from cadaveric and living donor.
• Patients that are going to receive immediate release Tacrolimus (Prograf/Adoport) as part of immunosuppressive treatment.
• Concomitant immunosuppression with Mycophenolate mofetil/Mycophenolic acid and steroids.
• Induction with Basiliximab is permitted.
• Subjects able to provide written informed consent.
• Female subjects of child-bearing potential must have a negative serum pregnancy test and must be practicing an effective, reliable, and medically approved contraceptive regimen during the study.

Exclusion Criteria:

• Subjects treated with drugs that can potentially interfere with Tacrolimus, especially CYP3A4 inhibitors (telaprevir, boceprevir, ritonavir, ketoconazole, voriconazole, itraconazole, telithromycin or clarithromycin) or CYP3A4 inductors (rifampicin or rifabutine).
• Subjects that receive induction treatment with Thymoglobulin or rituximab.
• Subjects participating in another investigational study within 30 days before inclusion.
• Subjects with hepatopathy.
• Subject or donor with a history of any malignancy (within the past 5 years), except non-metastatic basal or squamous cell carcinoma of the skin .
• Female subjects who are pregnant or breast feeding.
• Subjects receiving an ABO incompatible kidney.
• Subjects have Donor Specific Antibodies.
• Recipients of an allograft with ischemic cold time > or = 24 hours.
• Subjects with a history of active hepatitis C virus (HCV-RNA positive) and/or hepatitis B virus (DNA-HBV or HBsAg positive) infection.
• Subjects with a history of human immunodeficiency virus (HIV-Ab positive) infection.
• Subjects with psychiatric or physical illness that could interfere with the ability of the subject to participate in the study.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: TREATMENT
• Allocation: RANDOMIZED
• Interventional Model: PARALLEL
• Masking: NONE

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
ACTIVE_COMPARATOR: GROUP I Standard adjustment; Standard dosage of Tacrolimus	Drug: Standard dosage of Tacrolimus; Immediate release Tacrolimus (Prograf/Adoport); Other Names: Tacrolimus
EXPERIMENTAL: GROUP II Bayesian prediction adjustment; Bayesian prediction Tacrolimus dosage	Drug: Bayesian Prediction Tacrolimus dosage; Immediate release Tacrolimus (Prograf/Adoport); Other Names: Tacrolimus

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Tacrolimus plasmatic concentrations measurement	Concentration measured at day 6, 10, 15, 30, 60 and 90 post transplant and after each Tacrolimus dose adjustment	Day 6, 10, 15, 30, 60 and 90 post transplant

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Time to achieve Tacrolimus therapeutic target levels	Time to achieve Tacrolimus therapeutic target levels within the 90 days post transplant	90 days
Number of Tacrolimus dose changes to achieve target levels	Number of Tacrolimus dose changes to achieve target levels	90 days

Collaborators and Investigators

• Sponsor: NURIA LLOBERAS BLANCH
• Investigators: Principal Investigator: Núria Lloberas, PhD, Hospital Universitari de Bellvitge

Study record dates

Study Major Dates

• Study Start (ACTUAL): March 21, 2017
• Primary Completion (ACTUAL): September 21, 2020
• Study Completion (ACTUAL): September 21, 2020

Study Registration Dates

• First Submitted: February 23, 2018
• First Submitted That Met QC Criteria: March 13, 2018
• First Posted (ACTUAL): March 14, 2018

Study Record Updates

• Last Update Posted (ACTUAL): January 8, 2021
• Last Update Submitted That Met QC Criteria: January 7, 2021
• Last Verified: January 1, 2021

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Physiological Effects of Drugs; Molecular Mechanisms of Pharmacological Action; Enzyme Inhibitors; Immunosuppressive Agents; Immunologic Factors; Calcineurin Inhibitors; Tacrolimus
• Other Study ID Numbers: OPTIMUS

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No