Evidence map›Paper›PMID 26873229›Full record

Trial reportClinical pharmacokinetics2016

Population Pharmacokinetics of Daclizumab High-Yield Process in Healthy Volunteers and Subjects with Multiple Sclerosis: Analysis of Phase I-III Clinical Trials.

Lei Diao, Yaming Hang, Ahmed A Othman, Ivan Nestorov, Jonathan Q Tran

Abstract readClinical Trial, Phase IClinical Trial, Phase IIClinical Trial, Phase III
PubMed Publisher
In one paragraph

Trial report in Clinical pharmacokinetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Daclizumab: Development, Clinical Trials, and Practical Aspects of Use in Multiple Sclerosis.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2017
    Review
  10. Review
  11. Review
  12. Review
  13. Daclizumab.Hospital pharmacy · 2016
    Article
  14. Article
  15. Population PK-PD analyses of CD25 occupancy, CD56British journal of clinical pharmacology · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lei DiaoClinical Pharmacology and Pharmacometrics, Biogen, Cambridge, MA, USA. leidiao@hotmail.com.
Yaming HangClinical Pharmacology and Pharmacometrics, Biogen, Cambridge, MA, USA.
Ahmed A OthmanClinical Pharmacology and Pharmacometrics, Abbvie, North Chicago, IL, USA.
Ivan NestorovClinical Pharmacology and Pharmacometrics, Biogen, Cambridge, MA, USA.
Jonathan Q TranClinical Pharmacology and Pharmacometrics, Biogen, Cambridge, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesDaclizumab high-yield process (HYP) is a humanized IgG1 monoclonal antibody that binds to the α-subunit (CD25) of the interleukin-2 receptor. The present work characterized the population pharmacokinetics of daclizumab HYP in healthy volunteers (HVs) and subjects with relapsing-remitting multiple sclerosis (RRMS) and evaluated the effects of covariates on daclizumab HYP exposure.

methodsMeasurable serum concentrations (n = 17,139) from 1670 subjects in seven clinical studies (three phase I, one immunogenicity, one phase II with extension, and one phase III) were included in this pharmacokinetic analysis using non-linear mixed-effects modeling. The three phase I studies evaluated single or multiple doses that ranged from 50 to 400 mg with either intravenous or subcutaneous (SC) administration in HVs (n = 71). The phase II with extension studies evaluated doses of 150 or 300 mg SC every 4 weeks (n = 567), and the immunogenicity (n = 113) and the phase III (n = 919) studies evaluated 150 mg SC every 4 weeks, all in RRMS patients.

resultsA two-compartment model with first-order absorption and elimination adequately described daclizumab HYP pharmacokinetics. Clearance (CL) was 0.212 L/day and the central volume of distribution was 3.92 L, scaled by [body weight (kg)/68] with exponents of 0.87 and 1.12, respectively. The peripheral volume of distribution was 2.42 L. Absorption lag time, mean absorption time, and absolute bioavailability (100-300 mg SC) were 1.61 h, 7.2 days, and 88 %, respectively. The daclizumab HYP terminal half-life was 21 days. Baseline CD25, age, and sex did not influence daclizumab HYP pharmacokinetics. Body weight explained 37 and 27 % of the inter-individual variability for CL and central volume of distribution, respectively. Neutralizing antibody (NAb)-positive status (included as a time-varying covariate) increased daclizumab HYP CL by 19 %.

conclusionsConsistent with previous findings in HVs, this analysis including extensive data from RRMS patients demonstrates that daclizumab HYP is characterized by slow CL, linear pharmacokinetics at doses above 100 mg, and high SC bioavailability. The pharmacokinetics of daclizumab HYP were not influenced by age (range 18-66 years), the sex of adult subjects, or the baseline CD4+CD25+ T cells (target level). The impact of covariates (body weight, NAb) on daclizumab HYP pharmacokinetics is unlikely to be clinically relevant.

Indexed as

Administration, IntravenousAdolescentAdultAgedAntibodies, Monoclonal, HumanizedBiological AvailabilityDaclizumabDose-Response Relationship, DrugFemaleHealthy VolunteersHumansImmunoglobulin GImmunosuppressive AgentsInterleukin-2 Receptor alpha SubunitMaleMiddle AgedAntibodies, Monoclonal, HumanizedDaclizumabdaclizumab HYPIL2RA protein, humanImmunoglobulin GImmunosuppressive AgentsInterleukin-2 Receptor alpha SubunitReceptors, Interleukin-2

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.