Safe and effective use of drugs requires an understanding of metabolism and transport. We identified the 100 most prescribed drugs in six countries and conducted a literature search on in vitro data to assess contribution of Phase I and II enzymes and drug transporters to metabolism and transport.Eighty‐nine of the 100 drugs undergo drug metabolism or are known substrates for drug transporters. Phase I enzymes are involved in metabolism of 67 drugs, while Phase II enzymes mediate metabolism of 18 drugs. CYP3A4/5 is the most important Phase I enzyme involved in metabolism of 43 drugs followed by CYP2D6 (23 drugs), CYP2C9 (23 drugs), CYP2C19 (22 drugs), CYP1A2 (14 drugs) and CYP2C8 (11 drugs). More than half of the drugs (54 drugs) are known substrates for drug transporters. P‐glycoprotein (P‐gp) is known to be involved in transport of 30 drugs, while breast cancer resistance protein (BCRP) facilitates transport of 11 drugs. A considerable proportion of drugs are subject to a combination of Phase I metabolism, Phase II metabolism and/or drug transport.We conclude that the majority of the most frequently prescribed drugs depend on drug metabolism or drug transport. Thus, understanding variability of drug metabolism and transport remains a priority.

The aim of this study was to determine the association between the renal clearance (CL(renal)) of metformin in healthy Caucasian volunteers and the single-nucleotide polymorphism (SNP) c.808G>T (rs316019) in OCT2 as well as the relevance of the gene-gene interactions between this SNP and (a) the promoter SNP g.-66T>C (rs2252281) in MATE1 and (b) the OCT1 reduced-function diplotypes. Fifty healthy volunteers genotyped for the c.808G>T were enrolled in the study. The distribution was 25 GG, 20 GT, and 5 TT volunteers. The pharmacokinetics of a 500 mg single oral dose of metformin was studied. When analyzed alone, the c.808 (G>T) affected neither the CL(renal) nor the secretory clearance (CL(sec)) of metformin. However, both CL(renal) and CL(sec) were increased for the volunteers with minor alleles in c.808 (G>T) who were also homozygous for the reference variant g.-66T>C: CL(renal): GG, GT, and TT: 28.1, 34.5, and 44.8 l/h (P = 0.004), respectively and CL(sec): GG, GT, and TT: 21.4, 27.8, and 37.6 l/h (P = 0.005), respectively. In the volunteers with minor alleles in c.808 (G>T) who were also heterozygous for g.-66T>C, both CL(renal) and CL(sec) were found to be reduced (P < 0.028) when compared with volunteers with minor alleles in c.808 (G>T) carrying the g.-66T>C reference genotype. We report counteracting effects of the c.808 (G>T) and g.-66T>C on the renal elimination of metformin. When adjusted for the genetic variation g.-66T>C, our results suggest that c.808 (G>T) could have a dominant genotype to phenotype correlation.

Fracture risk is increased in individuals with type 2 diabetes (T2D). The pathophysiological mechanisms accentuating fracture risk in T2D are convoluted, incorporating factors such as hyperglycaemia, insulinopenia, and antidiabetic drugs. The objectives of this study were to assess whether different insulin regimens, metformin and rosiglitazone influence bone metabolism. We explored if the concentration of metformin and rosiglitazone in blood or improved glycaemic control altered bone turnover. Two-year clinical trial designed to investigate effects of antidiabetic treatment in 371 T2D patients. Participants were randomized to short or long-acting human insulin (non-blinded) and then further randomized to metformin + placebo, rosiglitazone + placebo, metformin + rosiglitazone or placebo + placebo (blinded). Fasting bone turnover markers (BTM) representing bone resorption (CTX) and formation (PINP) including HbA1c were measured at baseline and after 3, 12 and 24 months. Trough steady-state plasma concentrations of metformin and rosiglitazone were measured after 3, 6 and 9 months of treatment. Associations between treatments and BTMs during the follow-up of the trial were analysed in mixed-effects models that included adjustments for age, gender, BMI, renal function and repeated measures of HbA1c. BTMs increased from baseline to month 12 and remained higher at month 24, with CTX and PINP increasing 28.5% and 23.0% (all: p < 0.001), respectively. Allocation of insulin regimens was not associated with different levels of BTMs. Metformin and metformin + rosiglitazone but not rosiglitazone alone were associated with lower bone formation (PINP). Neither metformin nor rosiglitazone plasma concentrations was associated with BTMs. HbA1c was inversely associated with CTX but not P1NP. The choice of insulin treatment is not influencing BTMs, metformin treatment may decrease BTMs, and improvement of glycaemic control may influence bone resorption activity.