Literature DB >> 29077992

Population pharmacokinetics of exendin-(9-39) and clinical dose selection in patients with congenital hyperinsulinism.

Chee M Ng1, Fei Tang1, Steven H Seeholzer2, Yixuan Zou1, Diva D De León2,3.   

Abstract

AIMS: Congenital hyperinsulinism (HI) is the most common cause of persistent hypoglycaemia in infants and children. Exendin-(9-39), an inverse glucagon-like peptide 1 (GLP-1) agonist, is a novel therapeutic agent for HI that has demonstrated glucose-raising effect. We report the first population pharmacokinetic (PopPK) model of the exendin-(9-39) in patients with HI and propose the optimal dosing regimen for future clinical trials in neonates with HI.
METHODS: A total of 182 pharmacokinetic (PK) observations from 26 subjects in three clinical studies were included for constructing the PopPK model using first order conditional estimation (FOCE) with interaction method in nonlinear mixed-effects modelling (NONMEM). Exposure metrics (area under the curve [AUC] and maximum plasma concentration [Cmax ]) at no observed adverse effect levels (NOAELs) in rats and dogs were determined in toxicology studies.
RESULTS: Observed concentration-time profiles of exendin-(9-39) were described by a linear two-compartmental PK model. Following allometric scaling of PK parameters, age and creatinine clearance did not significantly affect clearance. The calculated clearance and elimination half-life for adult subjects with median weight of 69 kg were 11.8 l h-1 and 1.81 h, respectively. The maximum recommended starting dose determined from modelling and simulation based on the AUC0-last at the NOAEL and predicted AUC0-inf using the PopPK model was 27 mg kg-1  day-1 intravenously.
CONCLUSIONS: This is the first study to investigate the PopPK of exendin-(9-39) in humans. The final PopPK model was successfully used with preclinical toxicology findings to propose the optimal dosing regimen of exendin-(9-39) for clinical studies in neonates with HI, allowing for a more targeted dosing approach to achieve desired glycaemic response.
© 2017 The British Pharmacological Society.

Entities:  

Keywords:  NONMEM; congenital disorders; modelling and simulation; pharmacokinetics; population analysis

Mesh:

Substances:

Year:  2017        PMID: 29077992      PMCID: PMC5809353          DOI: 10.1111/bcp.13463

Source DB:  PubMed          Journal:  Br J Clin Pharmacol        ISSN: 0306-5251            Impact factor:   4.335


  44 in total

1.  Ways to fit a PK model with some data below the quantification limit.

Authors:  S L Beal
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-10       Impact factor: 2.745

2.  Handling data below the limit of quantification in mixed effect models.

Authors:  Martin Bergstrand; Mats O Karlsson
Journal:  AAPS J       Date:  2009-05-19       Impact factor: 4.009

3.  Population Pharmacokinetic Model of Sublingual Buprenorphine in Neonatal Abstinence Syndrome.

Authors:  Chee M Ng; Erin Dombrowsky; Hopi Lin; Michelle E Erlich; David E Moody; Jeffrey S Barrett; Walter K Kraft
Journal:  Pharmacotherapy       Date:  2015-07-14       Impact factor: 4.705

4.  Population pharmacokinetics of rituximab (anti-CD20 monoclonal antibody) in rheumatoid arthritis patients during a phase II clinical trial.

Authors:  Chee M Ng; Rene Bruno; Dan Combs; Brian Davies
Journal:  J Clin Pharmacol       Date:  2005-07       Impact factor: 3.126

5.  Rationale for fixed dosing of pertuzumab in cancer patients based on population pharmacokinetic analysis.

Authors:  Chee M Ng; Bert L Lum; Veronica Gimenez; Steve Kelsey; David Allison
Journal:  Pharm Res       Date:  2006-05-26       Impact factor: 4.200

6.  Evaluating pharmacokinetic/pharmacodynamic models using the posterior predictive check.

Authors:  Y Yano; S L Beal; L B Sheiner
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-04       Impact factor: 2.745

7.  Population pharmacokinetics of phenobarbital in infants with neonatal encephalopathy treated with therapeutic hypothermia.

Authors:  Renée A Shellhaas; Chee M Ng; Christina H Dillon; John D E Barks; Varsha Bhatt-Mehta
Journal:  Pediatr Crit Care Med       Date:  2013-02       Impact factor: 3.624

8.  High Risk of Diabetes and Neurobehavioral Deficits in Individuals With Surgically Treated Hyperinsulinism.

Authors:  Katherine Lord; Jerilynn Radcliffe; Paul R Gallagher; N Scott Adzick; Charles A Stanley; Diva D De León
Journal:  J Clin Endocrinol Metab       Date:  2015-09-01       Impact factor: 5.958

9.  Long-term follow-up of 114 patients with congenital hyperinsulinism.

Authors:  Thomas Meissner; Udo Wendel; Peter Burgard; Silvia Schaetzle; Ertan Mayatepek
Journal:  Eur J Endocrinol       Date:  2003-07       Impact factor: 6.664

Review 10.  The Diagnosis and Management of Hyperinsulinaemic Hypoglycaemia.

Authors:  Klára Roženková; Maria Güemes; Pratik Shah; Khalid Hussain
Journal:  J Clin Res Pediatr Endocrinol       Date:  2015-06
View more
  7 in total

1.  Population pharmacokinetics of exendin-(9-39) and clinical dose selection in patients with congenital hyperinsulinism.

Authors:  Chee M Ng; Fei Tang; Steven H Seeholzer; Yixuan Zou; Diva D De León
Journal:  Br J Clin Pharmacol       Date:  2017-12-06       Impact factor: 4.335

Review 2.  Congenital Hyperinsulinism: Diagnosis and Treatment Update.

Authors:  Hüseyin Demirbilek; Khalid Hussain
Journal:  J Clin Res Pediatr Endocrinol       Date:  2017-12-27

Review 3.  Update of variants identified in the pancreatic β-cell KATP channel genes KCNJ11 and ABCC8 in individuals with congenital hyperinsulinism and diabetes.

Authors:  Elisa De Franco; Cécile Saint-Martin; Klaus Brusgaard; Amy E Knight Johnson; Lydia Aguilar-Bryan; Pamela Bowman; Jean-Baptiste Arnoux; Annette Rønholt Larsen; May Sanyoura; Siri Atma W Greeley; Raúl Calzada-León; Bradley Harman; Jayne A L Houghton; Elisa Nishimura-Meguro; Thomas W Laver; Sian Ellard; Daniela Del Gaudio; Henrik Thybo Christesen; Christine Bellanné-Chantelot; Sarah E Flanagan
Journal:  Hum Mutat       Date:  2020-02-17       Impact factor: 4.878

4.  Functional GLP-1R antibodies identified from a synthetic GPCR-focused library demonstrate potent blood glucose control.

Authors:  Qiang Liu; Pankaj Garg; Burcu Hasdemir; Linya Wang; Emily Tuscano; Emily Sever; Erica Keane; Ana G Lujan Hernandez; Tom Z Yuan; Eric Kwan; Joyce Lai; Greg Szot; Sreenivasan Paruthiyil; Fumiko Axelrod; Aaron K Sato
Journal:  MAbs       Date:  2021 Jan-Dec       Impact factor: 5.857

5.  Divergent Effect of Central Incretin Receptors Inhibition in a Rat Model of Sporadic Alzheimer's Disease.

Authors:  Jelena Osmanovic Barilar; Ana Knezovic; Jan Homolak; Ana Babic Perhoc; Melita Salkovic-Petrisic
Journal:  Int J Mol Sci       Date:  2022-01-04       Impact factor: 5.923

Review 6.  The Role of GLP-1 Signaling in Hypoglycemia due to Hyperinsulinism.

Authors:  Melinda Danowitz; Diva D De Leon
Journal:  Front Endocrinol (Lausanne)       Date:  2022-03-24       Impact factor: 6.055

7.  Exendin-(9-39) Effects on Glucose and Insulin in Children With Congenital Hyperinsulinism During Fasting and During a Meal and a Protein Challenge.

Authors:  Darko Stefanovski; Mary E Vajravelu; Stephanie Givler; Diva D De León
Journal:  Diabetes Care       Date:  2022-06-02       Impact factor: 17.152

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.