When herbal drugs and conventional allopathic drugs are used together, they can interact in our body which can lead to the potential for herb-drug interactions. This work was conducted to evaluate the herb-drug interaction potential of caffeic acid and quercetin mediated by cytochrome P450 (CYP) inhibition. Human liver microsomes (HLMs) were added to each selective probe substrates of cytochrome P450 enzymes with or without of caffeic acid and quercetin. IC50 , Ki values, and the types of inhibition were determined. Both caffeic acid and quercetin were potent competitive inhibitors of CYP1A2 (Ki = 1.16 and 0.93 μM, respectively) and CYP2C9 (Ki = 0.95 and 1.67 μM, respectively). Caffeic acid was a potent competitive inhibitor of CYP2D6 (Ki = 1.10 μM) and a weak inhibitor of CYP2C19 and CYP3A4 (IC50 > 100 μM). Quercetin was a potent competitive inhibitor of CYP 2C19 and CYP3A4 (Ki = 1.74 and 4.12 μM, respectively) and a moderate competitive inhibitor of CYP2D6 (Ki = 18.72 μM). These findings might be helpful for safe and effective use of polyphenols in clinical practice. Our data indicated that it is necessary to study the in vivo interactions between drugs and pharmaceuticals with dietary polyphenols.

Phenolic compounds are common ingredients in many dietary supplements and functional foods. However, data concerning physicochemical properties and permeability of polyphenols on the intestinal epithelial cells are scarce. The aims of this study were to determine the experimental partition coefficient (Log P), and parallel artificial membrane permeability assay (PAMPA), to characterize the bi-directional transport of six phenolic compounds viz. caffeic acid, chrysin, gallic acid, quercetin, resveratrol and rutin in Caco-2 cells. The experimental Log P values of six polyphenols were correlated (R (2) = 0.92) well with the calculated Log P values. The apparent permeability (P app) range of all polyphenols in PAMPA for the apical (AP) to basolateral (BL) was 1.18 ± 0.05 × 10(-6) to 5.90 ± 0.16 × 10(-6) cm/s. The apparent Caco-2 permeability (P app) range for the AP-BL was 0.96 ± 0.03 × 10(-6) to 3.80 ± 0.45 × 10(-6) cm/s. The efflux ratio of P app (BL → AP) to P app (AP → BL) for all phenolics was <2, suggesting greater permeability in the absorptive direction. Six compounds exhibited strong correlations between Log P and PAMPA/Caco-2 cell monolayer permeation data. Dietary six polyphenols were poorly absorbed through PAMPA and Caco-2 cells, and their transepithelial transports were mainly by passive diffusion.

We have developed a new type of 2'-hydroxyl protecting group for the automated machine synthesis of RNA oligomers: a 2-hydroxyisophthalate formaldehyde acetal (HIFA). The unique feature of this protecting group is that, as the bis ester, it is relatively stable to the acidic conditions that are used for repeated removal of dimethoxytrityl groups during chain elongation, but the final deprotection step in alkali, which cleaves the chain from the support and removes the base and phosphate protecting groups, converts it to the bis carboxylate and this can be removed relatively rapidly by treatment with mild acid. Conversion of the bis ester to the bis carboxylic acid increases the rate of acid-catalyzed hydrolysis' of the acetal by 42-fold at pH 1, and, possibly, by 1320-fold at pH 3. The bis ester is 112 times more stable than the 1 -(2-fluorophenyl)-4-methoxypiperidin-4-yl group (Fpmp) towards hydrolysis at pH 1, while the bis acid is only 2.35 times more stable than Fpmp at pH 3. In synthesis of the dimers UpU and UpG, with a coupling time of 5 min, the dimethoxytrityl cation assay indicated coupling yields of >98%.

Intensive Biotransformation studies on Gefitinib could play a significant role in designing and synthesizing new drugs around the core structure of Gefitinib. These studies may be useful in developing an entirely new drug by blocking the metabolic spots in Gefitinib. Gefitinib (Iressa) was the first oral epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor. Gefitinib shows toxicity to cancer cells and has the capability to inhibit the growth of cancer cells. Gefitinib is considered as one of the selective EGFR inhibitors to be available in clinical practice. In 2003, FDA had approved Gefitinib for metastatic non-small-cell lung cancer therapy (NSCLC). However, it was observed that NSCLC Patients who responded to treatment developed resistance to Gefitinib. Hence, in the present study Gefitinib was incubated with hepatocytes to identify both phase-I and Phase-II metabolites. Identified Phase -I metabolites were due to oxidative defluorination, N-dealkylation and loss of morpholine ring. One of the phase-II metabolites identified i.e. the glutathione adduct suggests the need to modify the structure of the drug for higher potency and safety.

Discovering a new drug is a complex but sequential process from discovery to preclinical development, followed with clinical drug development. It has been estimated that ∼ 87% of the phase III failures are accounted for either due to lack of efficacy (66%) or due to safety issues (21%). Majority of these failures are for compounds targeted for novel mechanisms of actions with unmet medical need, in particular, oncology and neurodegenerative disorders. Some of the reasons for these failures can be attributed to lack of appropriate preclinical animal models, biomarkers/surrogate markers, and effective pharmacokinetic (PK)–pharmacodynamic (PD) evaluation during early drug discovery. Translational research that integrates computer‐aided drug design (CADD), PK, PD, drug metabolism (DM), and drug transport along with biomarkers and humanized animal models are instrumental in making informed decisions from early drug discovery through clinical development. The ability to correlate drug effect through modeling and simulations starts from early drug discovery and preclinical evaluation, including use of novel biomarkers. Such models validate the PK and PD relationships and provide a basis for their applications and guide the Phase I through Phase III clinical trials more effectively, minimizing the late stage failures. Thus, PK–PD evaluation has become an integral part of drug discovery and provides valuable insights to aid in optimizing the next steps for drug development. This chapter is focused on translational drug discovery research with particular emphasis on selective utilization of CADD; absorption, distribution, metabolism, and excretion; toxicology; PK; and PD evaluations, which identify potential liabilities early so as to minimize late‐stage failures during drug development. This chapter also provides a brief overview on means and measures that can be adopted to integrate early drug discovery research along with efficacy and safety biomarkers for meaningful transition to drug development.