Introduction
Metformin is an orally administered drug prescribed for the treatment of Type 2 diabetes. It is known to decrease hepatic glucose production, by inhibiting gluconeogenesis, and to increase glucose utilization. Metformin is cationic at physiological pH, is not metabolized, has poor passive permeability, and is excreted unchanged in the urine. OCT1 mediates its hepatic uptake, and its renal clearance is mediated by OCT2, MATE1, and MATE2-K (Figure 1). Metformin is taken along with food to avoid gastrointestinal side effects. Care is also taken not to administer metformin in patients with hepatic or renal impairment as it may lead to lactic acidosis through the inhibition of hepatic glucose production from lactate. Drugs inhibiting OCTs and MATEs could decrease the elimination of metformin and increase its plasma concentration, leading to an elevated risk of metformin-associated lactic acidosis (MALA).

The Dichotomy
Regulatory agencies recommend clinical DDI studies for drugs that are inhibitors of OCT2, MATE1, and/or MATE2-K. A change in systemic exposure of metformin has been monitored as a clinical endpoint in such studies. It has been reported that in spite of unaltered systemic pharmacokinetics of metformin, altered hepatic exposure and antihyperglycemic effect have been observed. On the other hand, increased systemic exposure of metformin did not impact hepatic exposure and efficacy. Based on the clinical evidence, ITC has now recommended considering both pharmacokinetic (PK) and pharmacodynamic (PD) endpoints for deciding on metformin dosing during co-medication with a new molecular entity (NME).

Proposed Metformin DDI Study Design
The following endpoints should be considered for rational dose adjustment of metformin during clinical studies.

  1. Systemic pharmacokinetics (AUC, CmaxHalf-life, V/F, CL/F) : no-effect boundary (0.8-1.25)
  2. Renal clearance: no-effect boundary (0.8-1.25)
  3. Antihyperglycemic effect (oral glucose tolerance test, OGTT): no-effect boundary (0.75-1.33)
  4. Blood lactate concentration (not clinically validated): no-effect boundary not defined yet.

Modeling and Simulation in Metformin DDI Study Design
Physiologically based PK models of metformin are being refined by incorporating efficacy and tissue concentration data for better prediction of clinical DDI outcomes.

Pharmacogenetic Considerations
Transporters involved in the disposition of metformin exhibit polymorphisms, including functionally deficient phenotypes. This may be one of the reasons for pharmacokinetic variability. Hence, a crossover study design is recommended. Where possible, incorporation of genotyping data of study subjects would help in understanding outliers.

Key Takeaways

  • The metformin DDI study design recommended by ITC, incorporating PK and PD assessments, is worth considering.
  • Results from a DDI study involving metformin should not be extrapolated to other drugs, as they are unlikely to predict metformin liver distribution and the resulting efficacy and safety.
  • In a clinical DDI study with dolutegravir (an OCT2 inhibitor) and metformin [1], only metformin systemic exposure was determined (an increase was observed). As renal clearance (a more direct index of OCT2 function) and PD endpoints (reflecting the possible involvement of OCT1 inhibition) were not assessed, a clear dosing recommendation was not possible because the observed DDI could not be explained on the basis of the limited data that was collected.
  • In a clinical DDI study with famotidine (a MATE1 inhibitor) and metformin [1], the determination of both PD parameters (consistent with an increase in hepatic exposure) and PK parameters (increase in both intestinal absorption and renal clearance, resulting in no change in systemic exposure) revealed a complex interaction that would otherwise have been missed.

References

  1. Zamek-Gliszczynski MJChu XCook JACustodio JM, Galetin AGiacomini KMLee CAPaine MFRay ASWare JAWittwer MBZhang L. ITC Commentary on Metformin Clinical Drug-Drug Interaction Study Design That Enables an Efficacy- and Safety-Based Dose Adjustment Decision. Clin Pharmacol Ther. 2018; 104(5):781-784. https://www.absorption.com/kc/transporter-webinar/
  2. Webinar presented by Dr. Zamek-Gliszczynski, Senior Fellow and Director, DMPK, GlaxoSmithKline
  3. Absorption Systems’ Transporter Reference Guide, 2018, 4th Edition, Absorption Systems