2020 FDA Drug-drug Interaction Guidance: A Comparison Analysis and Action Plan by Pharmaceutical Industrial Scientists.

BACKGROUND: In January 2020, the US FDA published two final guidelines, one entitled "In vitro Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry" and the other entitled "Clinical Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry". These were updated from the 2017 draft in vitro and clinical DDI guidance. METHODS: This study is aimed to provide an analysis of the updates along with a comparison of the DDI guidelines published by the European Medicines Agency (EMA) and Japanese Pharmaceuticals and Medical Devices Agency (PMDA) along with the current literature. RESULTS: The updates were provided in the final FDA DDI guidelines and explained the rationale of those changes based on the understanding from research and literature. Furthermore, a comparison among the FDA, EMA, and PMDA DDI guidelines are presented in Tables 1, 2 and 3. CONCLUSION: The new 2020 clinical DDI guidance from the FDA now has even higher harmonization with the guidance (or guidelines) from the EMA and PMDA. A comparison of DDI guidance from the FDA 2017, 2020, EMA, and PMDA on CYP and transporter based DDI, mathematical models, PBPK, and clinical evaluation of DDI is presented in this review.

Targeting drug transporters - combining in silico and in vitro approaches to predict in vivo.

Transporter proteins are expressed throughout the human body in different vital organs. They play an important role to various extents in determining absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties of therapeutic molecules. Over the past decade, numerous drug transporters have been cloned and considerable progress has been made toward understanding the molecular characteristics of individual transporters. In this chapter several in vitro and in silico techniques are described with applications to understand transporter behavior. These include employing new techniques to rapidly identify novel ligands for transporters. Ultimately these methods should lead to a greater overall appreciation of the role of transporters in vivo.

Bacterial peptide recognition and immune activation facilitated by human peptide transporter PEPT2.

Microbial detection requires the recognition of pathogen-associated molecular patterns (PAMPs) by pattern recognition receptors (PRRs) that are distributed on the cell surface and within the cytosol. The nucleotide-binding oligomerization domain (NOD)-like receptor (NLR) family functions as an intracellular PRR that triggers the innate immune response. The mechanism by which PAMPs enter the cytosol to interact with NLRs, particularly muropeptides derived from the bacterial proteoglycan cell wall, is poorly understood. PEPT2 is a proton-dependent transporter that mediates the active translocation of di- and tripeptides across epithelial tissues, including the lung. Using computational tools, we initially established that bacterial dipeptides, particularly gamma-D-glutamyl-meso-diaminopimelic acid (gamma-iE-DAP), are suitable substrates for PEPT2. We then determined in primary cultures of human upper airway epithelia and transiently transfected CHO-PEPT2 cell lines that gamma-iE-DAP uptake was mediated by PEPT2 with an affinity constant of approximately 193 microM, whereas muramyl dipeptide was not transported. Exposure to gamma-iE-DAP at the apical surface of differentiated, polarized cultures resulted in activation of the innate immune response in an NOD1- and RIP2-dependent manner, resulting in release of IL-6 and IL-8. Based on these findings we report that PEPT2 plays a vital role in microbial recognition by NLR proteins, particularly with regard to airborne pathogens, thereby participating in host defense in the lung.

Design of high-affinity peptide conjugates with optimized fluorescence quantum yield as markers for small peptide transporter PEPT1 (SLC15A1).

We employed a computational approach to design and synthesize a series of fluorescently labeled hPEPT1 substrates. Five Alexa Fluor-350-labeled peptides were assessed for their in vitro inhibitory activity in hPEPT1-transfected CHO cells. At least four labeled peptides show potent inhibitory activity toward hPEPT1-mediated uptake of [(3)H]-GlySar and three compounds displayed a significant cellular uptake specifically mediated by hPEPT1.

Computational models to assign biopharmaceutics drug disposition classification from molecular structure.

PURPOSE: We applied in silico methods to automatically classify drugs according to the Biopharmaceutics Drug Disposition Classification System (BDDCS). MATERIALS AND METHODS: Models were developed using machine learning methods including recursive partitioning (RP), random forest (RF) and support vector machine (SVM) algorithms with ChemDraw, clogP, polar surface area, VolSurf and MolConnZ descriptors. The dataset consisted of 165 training and 56 test set molecules. RESULTS: RF model 3, RP model 1, and SVM model 1 can correctly predict 73.1, 63.6 and 78.6% test compounds in classes 1, 2 and 3, respectively. Both RP and SVM models can be used for class 4 prediction. The inclusion of consensus analysis resulted in improved test set predictions for class 2 and 4 drugs. CONCLUSIONS: The models can be used to predict BDDCS class for new compounds from molecular structure using readily available molecular descriptors and software, representing an area where in silico approaches could aid the pharmaceutical industry in speeding drugs to the patient and reducing costs. This could have significant applications in drug discovery to identify molecules that may have future developability issues.

Pharmacophore-based discovery of ligands for drug transporters.

The ability to identify ligands for drug transporters is an important step in drug discovery and development. It can both improve accurate profiling of lead pharmacokinetic properties and assist in the discovery of new chemical entities targeting transporters. In silico approaches, especially pharmacophore-based database screening methods have great potential in improving the throughput of current transporter ligand identification assays, leading to a higher hit rate by focusing in vitro testing to the most promising hits. In this review, the potential of different in silico methods in transporter ligand identification studies are compared and summarized with an emphasis on pharmacophore modeling. Various implementations of pharmacophore model generation, database compilation and flexible screening algorithms are also introduced. Recent successful utilization of database searching with pharmacophores to identify novel ligands for the pharmaceutically significant transporters hPepT1, P-gp, BCRP, MRP1 and DAT are reviewed and the challenges encountered with current approaches are discussed.

Rapid identification of P-glycoprotein substrates and inhibitors.

Identifying molecules that interact with P-glycoprotein (P-gp) is important for drug discovery but is also generally reliant on time-consuming in vitro and in vivo studies. As an alternative approach, the current study applied pharmacophore models and database screening to rapidly retrieve molecules that bind as substrates or inhibitors for P-gp from commercial databases and then confirmed their affinity as inhibitors in vitro. Seven molecules (acitretin, cholecalciferol, misoprostol, nafcillin, repaglinide, salmeterol, and telmisartan) with no published details for P-gp affinity, one positive control inhibitor (miconazole), and two negative control molecules (phenelzine and zonisamide) were selected for testing. The MDCK-MDR1 in vitro cell model was used to confirm their inhibitory effect on [3H]digoxin transport, and the ATPase assay was used as an additional in vitro tool to indicate P-gp activation. All seven test drugs were confirmed to have P-gp affinity. Additionally, our experimental results provided plausible explanations for the published pharmacokinetic profiles of the tested drugs and their classification according to the biopharmaceutics and drug disposition classification system. In this study, we showed the successful application of pharmacophore models to accurately predict P-gp binding, which holds promise to anticipate drug-drug interactions from screening drug databases and a priori prediction of novel P-gp inhibitors or substrates.

In vitro and pharmacophore-based discovery of novel hPEPT1 inhibitors.

PURPOSE: The human proton-coupled small peptide carrier (hPEPT1) is a low-affinity, high-capacity transporter with broad substrate specificity. We have taken an iterative in vitro and in silico approach to the discovery of molecules with hPEPT1 affinity. METHODS: A pharmacophore-based approach was taken to identifying hPEPT1 inhibitors. The well-characterized and relatively high affinity ligands Gly-Sar, bestatin, and enalapril were used to generate a common features (HIPHOP) pharmacophore. This consisted of two hydrophobic features, a hydrogen bond donor, acceptor, and a negative ionizable feature. RESULTS: The pharmacophore was used to search the Comprehensive Medicinal Chemistry (CMC) database of more than 8000 drug-like molecules and retrieved 145 virtual hits mapping to the pharmacophore features. The highest scoring compounds within this set were selected and tested in a stably transfected CHO-hPepT1 cell model. The antidiabetic repaglinide and HMG CoA reductase inhibitor fluvastatin were found to inhibit hPEPT1 with sub-millimolar potency (IC(50) 178 +/- 1.0 and 337 +/- 4 microM, respectively). The pharmacophore was also able to identify known hPEPT1 substrates and inhibitors in further database mining of more than 500 commonly prescribed drugs. CONCLUSIONS: This study demonstrates the potential of combining computational and in vitro approaches to determine the affinity of compounds for hPEPT1 and, in turn, provides insights into key molecular interactions with this transporter.

Functional characterization of the peptide transporter PEPT2 in primary cultures of human upper airway epithelium.

This study characterizes the expression and function of the peptide transporter hPepT2 (SLC15A2) in differentiated primary cultures of human upper airway lung epithelia obtained from six human donors. Genotype analysis of a SNP in exon 15 of hPepT2 genotypes in six donors revealed an expected distribution of the two main variants present at similar frequency (two AA homozygotes, two BB homozygotes, and two AB heterozygotes). Real-time PCR analysis of the hPepT2 mRNA message revealed no significant differences among genotypes. hPEPT2 was expressed on the apical membrane in all donor specimens, demonstrated by cell surface biotinylation and Western analysis (104 kD). We then compared transepithelial transport of the prototypical substrate (3)H-glycylsarcosine in all donor cultures in the absence and presence of known inhibitors of hPEPT2 to ascertain the phenotype of functionally expressed hPepT2 in the upper airway epithelium. An array of inhibitors included dipeptides, beta-lactam antibiotics, bestatin, and ACE inhibitors. hPEPT2 exhibited saturable Michaelis-Menten-type kinetic parameters for GlySar, corroborating previously reported values for K(T) and J(max). Donor-to-donor variation of transport for different substrates did not correlate with hPepT2 haplotypes in this sample cohort. These findings demonstrate functional hPEPT2 transporter expression in primary cultures of human lung epithelial cells. hPEPT2-mediated transport could serve as a strategy for noninvasive systemic delivery of peptides and peptidomimetics drugs.

Molecular basis of vitamin E action: tocotrienol modulates 12-lipoxygenase, a key mediator of glutamate-induced neurodegeneration.

Vitamin E is a generic term for tocopherols and tocotrienols. This work is based on our striking evidence that, in neuronal cells, nanomolar concentrations of alpha-tocotrienol, but not alpha-tocopherol, block glutamate-induced death by suppressing early activation of c-Src kinase (Sen, C. K., Khanna, S., Roy, S., and Packer, L. (2000) J. Biol. Chem. 275, 13049-13055). This study on HT4 and immature primary cortical neurons suggests a central role of 12-lipoxygenase (12-LOX) in executing glutamate-induced neurodegeneration. BL15, an inhibitor of 12-LOX, prevented glutamate-induced neurotoxicity. Moreover, neurons isolated from 12-LOX-deficient mice were observed to be resistant to glutamate-induced death. In the presence of nanomolar alpha-tocotrienol, neurons were resistant to glutamate-, homocysteine-, and l-buthionine sulfoximine-induced toxicity. Long-term time-lapse imaging studies revealed that neurons and their axo-dendritic network are fairly motile under standard culture conditions. Such motility was arrested in response to glutamate challenge. Tocotrienol-treated primary neurons maintained healthy growth and motility even in the presence of excess glutamate. The study of 12-LOX activity and metabolism revealed that this key mediator of glutamate-induced neurodegeneration is subject to control by the nutrient alpha-tocotrienol. In silico docking studies indicated that alpha-tocotrienol may hinder the access of arachidonic acid to the catalytic site of 12-LOX by binding to the opening of a solvent cavity close to the active site. These findings lend further support to alpha-tocotrienol as a potent neuroprotective form of vitamin E.