Advancements in practical and scientific bioanalytical approaches to metabolism studies in drug development

Potential of measured relative shifts in collision cross section values for biotransformation studies

Ion mobility spectrometry-mass spectrometry (IMS-MS) separates gas phase ions due to differences in drift time from which reproducible and analyte-specific collision cross section (CCS) values can be derived. Internally conducted in vitro and in vivo metabolism (biotransformation) studies indicated repetitive shifts in measured CCS values (CCSmeas) between parent drugs and their metabolites. Hence, the purpose of the present article was (i) to investigate if such relative shifts in CCSmeas were biotransformation-specific and (ii) to highlight their potential benefits for biotransformation studies. First, mean CCSmeas values of 165 compounds were determined (up to n = 3) using a travelling wave IMS-MS device with nitrogen as drift gas (TWCCSN2, meas). Further comparison with their predicted values (TWCCSN2, pred, Waters CCSonDemand) resulted in a mean absolute error of 5.1%. Second, a reduced data set (n = 139) was utilized to create compound pairs (n = 86) covering eight common types of phase I and II biotransformations. Constant, discriminative, and almost non-overlapping relative shifts in mean TWCCSN2, meas were obtained for demethylation (- 6.5 ± 2.1 Å2), oxygenation (hydroxylation + 3.8 ± 1.4 Å2, N-oxidation + 3.4 ± 3.3 Å2), acetylation (+ 13.5 ± 1.9 Å2), sulfation (+ 17.9 ± 4.4 Å2), glucuronidation (N-linked: + 41.7 ± 7.5 Å2, O-linked: + 38.1 ± 8.9 Å2), and glutathione conjugation (+ 49.2 ± 13.2 Å2). Consequently, we propose to consider such relative shifts in TWCCSN2, meas (rather than absolute values) as well for metabolite assignment/confirmation complementing the conventional approach to associate changes in mass-to-charge (m/z) values between a parent drug and its metabolite(s). Moreover, the comparison of relative shifts in TWCCSN2, meas significantly simplifies the mapping of metabolites into metabolic pathways as demonstrated.

Cutting-edge strategies and critical advancements in characterization and quantification of metabolites concerning translational metabolomics

Despite remarkable progress in drug discovery strategies, significant challenges are still remaining in translating new insights into clinical applications. Scientists are devising creative approaches to bridge the gap between scientific and translational research. Metabolomics is a unique field among other omics techniques for identifying novel metabolites and biomarkers. Fortunately, characterization and quantification of metabolites are becoming faster due to the progress in the field of orthogonal analytical techniques. This review detailed the advancement in the progress of sample preparation, and data processing techniques including data mining tools, database, and their quality control (QC). Advances in data processing tools make it easier to acquire unbiased data that includes a diverse set of metabolites. In addition, novel breakthroughs including, miniaturization as well as their integration with other devices, metabolite array technology, and crystalline sponge-based method have led to faster, more efficient, cost-effective, and holistic metabolomic analysis. The use of cutting-edge techniques to identify the human metabolite, including biomarkers has proven to be advantageous in terms of early disease identification, tracking the progression of illness, and possibility of personalized treatments. This review addressed the constraints of current metabolomics research, which are impeding the facilitation of translation of research from bench to bedside. Nevertheless, the possible way out from such constraints and future direction of translational metabolomics has been conferred.

Implication of metabolomics and transporter modulation based strategies to minimize multidrug resistance and enhance site-specific bioavailability: a needful consideration toward modern anticancer drug discovery

Induction of drug-metabolizing enzymes and efflux transporters (DMET) through activation of pregnane x receptor (PXR) is the primary factor involved in almost all bioavailability and drug resistance-related problems of anticancer drugs. PXR is a transcriptional regulator of many metabolizing enzymes and efflux transporters proteins like p-glycoprotein (p-gp), multidrug resistant protein 1 and 2 (MRP 1 and 2), and breast cancer resistant protein (BCRP), etc. Several anticancer drugs are potent activators of PXR receptors and can modulate the gene expression of DMET proteins. Involvement of anticancer drugs in transcriptional regulation of DMET can prompt increased metabolism and efflux of their own or other co-administered drugs, which leads to poor site-specific bioavailability and increased drug resistance. In this review, we have discussed several novel strategies to evade drug-induced PXR activation and p-gp efflux including assessment of PXR ligand and p-gp substrate at early stages of drug discovery. Additionally, we have critically discussed the chemical structure and drug delivery-based approaches to avoid PXR binding and inhibit the p-gp activity of the drugs at their target sites.

UHPLC-Q-TOF-MS/MS based metabolite profiling of duvelisib and establishment of its metabolism mechanisms

Duvelisib is a dual inhibitor of phosphoinositide 3 kinase that received global approval by USFDA in 2018 to treat follicular lymphoma after at least two prior systemic therapies. An extensive literature search revealed that till date, metabolites of duvelisib are not characterized and information on the same is not available in any literature. Moreover, its metabolism pathway is yet to be established. This study aimed to investigate and characterize the metabolites of duvelisib generated in microsomes and S9 fractions. In this study, five duvelisib metabolites have been identified using UHPLC-Q-TOF-MS/MS technique of analysis. The structural characterisation of the metabolites was performed by comparing the fragmentation pattern of duvelisib and its metabolites through an accurate mass measurement technique. Three metabolites were found to be generated through phase I hydroxylation and dechlorination reaction. The other two metabolites were generated through a phase II glucuronidation reaction. The metabolism mechanism established through this study can be useful to improve the safety profile of the drug of its similar category in the future after establishment their toxicity profile of the identified metabolites.