The effect of food on pharmacokinetic properties of drugs is a commonly observed occurrence affecting about 40% of orally administered drugs. Within the pharmaceutical industry, significant resources are invested to predict and characterize a clinically relevant food effect. Here, the predictive performance of physiologically based pharmacokinetic (PBPK) food effect models was assessed via de novo mechanistic absorption models for 30 compounds using controlled, pre-defined in vitro, and modeling methodology. Compounds for which absorption was known to be limited by intestinal transporters were excluded in this analysis. A decision tree for model verification and optimization was followed, leading to high, moderate, or low food effect prediction confidence. High (within 0.8- to 1.25-fold) to moderate confidence (within 0.5- to 2-fold) was achieved for most of the compounds (15 and 8, respectively). While for 7 compounds, prediction confidence was found to be low (> 2-fold). There was no clear difference in prediction success for positive or negative food effects and no clear relationship to the BCS category of tested drug molecules. However, an association could be demonstrated when the food effect was mainly related to changes in the gastrointestinal luminal fluids or physiology, including fluid volume, motility, pH, micellar entrapment, and bile salts. Considering these findings, it is recommended that appropriately verified mechanistic PBPK modeling can be leveraged with high to moderate confidence as a key approach to predicting potential food effect, especially related to mechanisms highlighted here.

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Elevated homocysteine level is an independent risk factor for ischemic stroke, thrombotic and cardiovascular diseases. The enzyme methylenetetrahydrofolate reductase (MTHFR) plays a crucial role in regulating the levels of homocysteine. A C677T mutation in this gene results in reduced activity. Sixty-nine patients with arterial stroke, six patients with venous stroke (confirmed by computed tomography and/or magnetic resonance imaging) with hyperhomocysteinemia were selected for the study. Forty-nine subjects with no past history of stroke served as controls. MTHFR genotypes were determined by PCR using specific primers, followed by restriction digestion and gel analysis. The prevalence of the mutated homozygous and heterozygous C677T MTHFR genotype in the patients with arterial stroke was 1.4% (one of 69) and 31.88% (21 of 69), respectively. There frequency was 16.6% (one of six) and 33.3% (two of six) in venous stroke. The genotyping results from controls showed that there was only one heterozygote out of the 49 studied (2.08%). There was a significant difference between the control and the patient groups. Odds ratio for the probability of the C677T MTHFR gene mutation in the patients versus control group was 22.29 (95% CI 4.89-98.8). This indicates that C677T MTHFR mutation is strongly associated with arterial stroke especially in young adults. MTHFR allele evaluation will help in preventing/reducing morbidity caused by stroke.

Diabetes is gradually getting the status of a global epidemic, with India projected as the capital of type 2 diabetes mellitus (T2DM). Nephropathy is an important complication of diabetes and a major cause of end-stage renal disease. Studies from different parts of the world have given controversial results regarding the association of methylene tetrahydrofolate reductase (MTHFR) gene variation with T2DM and diabetic nephropathy (DN). This case-control study assessed the association of MTHFR C677T mutation in T2DM and DN cases. Genotyping of MTHFR was carried out for 236 T2DM cases with diabetes diagnosed for >8 years, having either normoalbuminuria (n=100) or established DN (n=136). One hundred age- and sex-matched healthy individuals with normal blood sugars and no family history of T2DM were selected as controls. This first report from India gives a highly significant odds ratio of 4.0423 (95% confidence interval=1.8753-8.7133), indicating that the MTHFR 677T allele confers a fourfold risk of developing DM in our population. The frequency of the T allele in both the DM and DN groups was similar (i.e., 0.16 and 0.11, respectively), showing no association with the initiation or progression of DN. Individuals with a family history of diabetes or with risk factors such as obesity, hypertension, and impaired glucose tolerance should be screened for MTHFR C677T mutation and may be prescribed folic acid, vitamin B6, and vitamin B12 to assess if this helps in delaying the onset of diabetes.

Abstarct: Membrane transporters play an important role in intestinal absorption, distribution and clearance of drugs. Additionally transporters along with enzymes regulate tissue exposures (e.g. liver, kidney and brain), which are important for safety and efficacy considerations. Early identification of transporters involved guides generation of in vitro and in vivo data needed to gain mechanistic understanding on the role of transporters in organ clearance, tissue exposures and enables development of physiological-based pharmacokinetic (PBPK) models. A lot of progress has been made in developing several in vitro assay systems and mechanistic in silico models to determine kinetic parameters for transporters, which are incorporated into PBPK models. Although, intrinsic clearance and inhibition data from in vitro systems generally tend to underpredict in vivo clearance and magnitude of drug-drug interactions (DDIs), empirical scaling factors derived from a sizable dataset are often used to offset underpredictions. PBPK models are increasing used to predict the impact of transporters on intestinal absorption, clearance, victim and perpetrator DDIs prior to first in human clinical trials. The models are often refined when clinical data is available and are used to predict pharmacokinetics in untested scenarios such as the impact of polymorphisms, ontogeny, ethnicity, disease states and DDIs with other perpetrator drugs. The aim of this review is to provide an overview of (i) regulatory requirements around transporters, (ii) in vitro systems and their limitations in predicting transporter mediated drug disposition and DDIs, (iii) PBPK modelling tactics and case studies used for internal decision making and/or for regulatory submissions.