No abstract

The development of model‐informed precision dosing (MIPD) tools, especially in the form of native or web‐based applications to be used at the bedside, has garnered marked attention in recent years. Their potential clinical benefit can be large, but it should be ensured that such tools make optimal use of available clinical data and have adequate predictive ability. Unique scientific challenges specific to MIPD remain, which may require adaptation of commonly used diagnostics in pharmacometrics.

Transporter-mediated drug-drug interactions (DDIs) are a major cause of drug toxicities. Using published genome-wide association studies (GWAS) of the human metabolome, we identified 20 metabolites associated with genetic variants in organic anion transporter, OATP1B1 (P < 5 × 10 ). Of these, 12 metabolites were significantly higher in plasma samples from volunteers dosed with the OATP1B1 inhibitor, cyclosporine (CSA) vs. placebo (q-value < 0.2). Conjugated bile acids and fatty acid dicarboxylates were among the metabolites discovered using both GWAS and CSA administration. In vitro studies confirmed tetradecanedioate (TDA) and hexadecanedioate (HDA) were novel substrates of OATP1B1 as well as OAT1 and OAT3. This study highlights the use of multiple datasets for the discovery of endogenous metabolites that represent potential in vivo biomarkers for transporter-mediated DDIs. Future studies are needed to determine whether these metabolites can serve as qualified biomarkers for organic anion transporters. Quantitative relationships between metabolite levels and modulation of transporters should be established.

Therapeutic response to metformin, a first‐line drug for type 2 diabetes (T2D), is highly variable, in part likely due to genetic factors. To date, metformin pharmacogenetic studies have mainly focused on the impact of variants in metformin transporter genes, with inconsistent results. To clarify the significance of these variants in glycemic response to metformin in T2D, we performed a large‐scale meta‐analysis across the cohorts of the Metformin Genetics Consortium (MetGen). Nine candidate polymorphisms in five transporter genes (organic cation transporter [OCT]1, OCT2, multidrug and toxin extrusion transporter [MATE]1, MATE2‐K, and OCTN1) were analyzed in up to 7,968 individuals. None of the variants showed a significant effect on metformin response in the primary analysis, or in the exploratory secondary analyses, when patients were stratified according to possible confounding genotypes or prescribed a daily dose of metformin. Our results suggest that candidate transporter gene variants have little contribution to variability in glycemic response to metformin in T2D.

One-third of type 2 diabetes patients do not respond to metformin. Genetic variants in metformin transporters have been extensively studied as a likely contributor to this high failure rate. Here, we investigate, for the first time, the effect of genetic variants in transcription factors on metformin pharmacokinetics (PK) and response. Overall, 546 patients and healthy volunteers contributed their genome-wide, pharmacokinetic (235 subjects), and HbA1c data (440 patients) for this analysis. Five variants in specificity protein 1 (SP1), a transcription factor that modulates the expression of metformin transporters, were associated with changes in treatment HbA1c (P < 0.01) and metformin secretory clearance (P < 0.05). Population pharmacokinetic modeling further confirmed a 24% reduction in apparent clearance in homozygous carriers of one such variant, rs784888. Genetic variants in other transcription factors, peroxisome proliferator–activated receptor-α and hepatocyte nuclear factor 4-α, were significantly associated with HbA1c change only. Overall, our study highlights the importance of genetic variants in transcription factors as modulators of metformin PK and response.