Mass spectrometry-based structure elucidation of small molecule impurities and degradation products in pharmaceutical development

Characterization of Pharmaceutical Transformation Products by High-Field Asymmetric Waveform Ion Mobility and Infrared Ion Spectroscopy Coupled to Mass Spectrometry

The identification of drug degradation products is crucial for pharmaceutical development and quality control, as drug transformation products can significantly affect therapeutic efficacy and patient safety. Traditional analytical methods, such as high-performance liquid chromatography (HPLC) and tandem mass spectrometry (MS/MS), often require reference standards for accurate identification and may be unsuitable for resolving isomeric and isobaric degradation products. This study explores the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS) and infrared multiple photon dissociation (IRMPD) spectroscopy coupled with mass spectrometry (MS) as an effective alternative for identifying drug degradation products without the need for previous chromatographic stages or the use of reference standards. Cyclophosphamide, a widely used DNA-alkylating agent in cancer and autoimmune therapies, is employed as a model system for this study. FAIMS enabled the separation of species based on their differential mobility, while IRMPD provided distinctive spectral data, allowing precise reference-standard-free structural elucidation. This integrated approach offers a robust solution for the identification of complex degradation products, advancing stability studies, formulation development, and quality control in pharmaceutical analysis.

Current and future deep learning algorithms for tandem mass spectrometry (MS/MS)-based small molecule structure elucidation

RATIONALE

Structure elucidation of small molecules has been one of the cornerstone applications of mass spectrometry for decades. Despite the increasing availability of software tools, structure elucidation from tandem mass spectrometry (MS/MS) data remains a challenging task, leaving many spectra unidentified. However, as an increasing number of reference MS/MS spectra are being curated at a repository scale and shared on public servers, there is an exciting opportunity to develop powerful new deep learning (DL) models for automated structure elucidation.

ARCHITECTURES

Recent early-stage DL frameworks mostly follow a "two-step approach" that translates MS/MS spectra to database structures after first predicting molecular descriptors. The related architectures could suffer from: (1) computational complexity because of the separate training of descriptor-specific classifiers, (2) the high dimensional nature of mass spectral data and information loss due to data preprocessing, (3) low substructure coverage and class imbalance problem of predefined molecular fingerprints. Inspired by successful DL frameworks employed in drug discovery fields, we have conceptualized and designed hypothetical DL architectures to tackle the above issues. For (1), we recommend multitask learning to achieve better performance with fewer classifiers by grouping structurally related descriptors. For (2) and (3), we introduce feature engineering to extract condensed and higher-order information from spectra and structure data. For instance, encoding spectra with subtrees and pre-calculated spectral patterns add peak interactions to the model input. Encoding structures with graph convolutional networks incorporates connectivity within a molecule. The joint embedding of spectra and structures can enable simultaneous spectral library and molecular database search.

CONCLUSIONS

In principle, given enough training data, adapted DL architectures, optimal hyperparameters and computing power, DL frameworks can predict small molecule structures, completely or at least partially, from MS/MS spectra. However, their performance and general applicability should be fairly evaluated against classical machine learning frameworks.

Prediction of Retention Indices in LC-HRMS for Enhanced Structural Identification of Organic Micropollutants in Water: Selectivity-Based Filtration

Addressing the global challenge of ensuring access to safe drinking water, especially in developing countries, demands cost-effective, eco-friendly, and readily available technologies. The persistence, toxicity, and bioaccumulation potential of organic pollutants arising from various human activities pose substantial hurdles. While high-performance liquid chromatography coupled with high-resolution mass spectrometry (HPLC-HRMS) is a widely utilized technique for identifying pollutants in water, the multitude of structures for a single elemental composition complicates structural identification. While current HRMS and MS/MS databases often can provide hits for known molecules, these are often erroneous or misleading when authentic standards are unavailable. In this research, a machine-learning algorithm is developed to support the structural elucidation of small organic pollutants in water, with a focus on (carbon, oxygen, and hydrogen-based) molecules weighing less than 500 Da. The approach relies on a comparison of the experimental and predicted retention of the possible structures of unknowns for which an elemental composition was obtained by HRMS. A promising novelty is thereby the improved removal of erroneous structures via the combination of the retention information obtained from two reversed-phase-based stationary phases, depicting different selectivities (octadecylsilica, C18 and pentafluorphenylsilica, F5). The study translates retention times into retention indices for instrument independence and transferability across diverse HPLC-HRMS systems. The predictive algorithm, utilizing retention data and molecular descriptors, accurately predicts retention indices and proves its utility by eliminating incorrect structural formulas through a 2-stationary phase intersection-based filtration. Using a data set of 100 training compounds and 16 external test set compounds, two Multiple Linear Regression (MLR), MLR-C18 and MLR-F5 models were developed, employing the 16 most influential descriptors, out of 5666 screened. MLR-C18 achieves precise RI predictions, R2 = 0.97, RMSE = 36, MAE = 26, while MLR-F5, though slightly less accurate, maintains a performance with R2 = 0.96, RMSE = 44, MAE = 34. The intersection-based filtration (within ±1.5σ) showed the elimination of more than 70% of impossible structures for a given elemental composition. The model was further implemented in the identification of a drinking water sample to prove its potential. This tool holds significant promise for supporting water quality management and sustainable practices, contributing to faster structural identification of unknown organic micropollutants in water.

Exploring the versatility of mass spectrometry: Applications across diverse scientific disciplines

Mass spectrometry (MS) has become a pivotal analytical tool across various scientific disciplines due to its ability to provide detailed molecular information with high sensitivity and specificity. MS plays a crucial role in various fields, including drug discovery and development, proteomics, metabolomics, environmental analysis, and clinical diagnostics and Forensic science. In this article we are discussing the application of MS across the diverse scientific disciplines by focusing on some classical examples from each field of application. As the technology continues to evolve, it promises to unlock new possibilities in scientific research and practical applications, cementing its position as an essential tool in modern analytical science.

Influence of Light Irradiation on the Degradation of Dezocine in Injections

Dezocine, which is well-known as an analgesic, had about 45% share of the Chinese opioid analgesic market. Since drug products containing impurities could bring serious health consequences, it was important to control the generation of impurities and degradation products in the dezocine product. In this study, two kinds of photodegradation products (i.e., degradation product 1 and degradation product 2) in the dezocine injection were isolated using high-performance liquid chromatography. The possible structures of the photodegradation products were identified using both high-resolution mass spectrometry and nuclear magnetic resonance spectroscopy. In addition, the possible generation mechanism showed that degradation product 1 was the oxidation product of dezocine, and degradation product 2 was the coupled dimer of dezocine. Finally, we found that the degradation rate of dezocine increased with the increase in light intensity. Moreover, the degradation of dezocine easily occurred under ultraviolet light in comparison with visible light. A deeper insight into the generation of the photodegradation products in the dezocine injection would directly contribute to the safety of drug therapy based on the dezocine injection by minimizing the degradant/impurity-related adverse effects of drug preparations.

Structure Identification and Risk Assurance of Unknown Impurities in Pramipexole Oral Drug Formulation

Impurities compounds in any pharmaceutical product or drug substance are inevitable from a chemistry point of view. The quality and safety of a pharmaceutical product are also significantly affected by these impurities content; therefore, impurities need to be identified and characterized through the use of appropriate analytical methods. Pramipexole is a nonergot dopamine agonist used to treat various Parkinson's disease symptoms. Two unknown impurities were detected from a pramipexole dihydrochloride solid dosage form. These impurities were identified and characterized using ultra-performance liquid chromatography coupled with high-resolution mass spectroscopy (UPLC-HRMS). These impurities were found to be enriched when mannitol existed in the formulation. The structure and mechanism involved in the existence of the impurities were proposed. Furthermore, observation of the binding affinity potential risk of these impurities to the pramipexole receptor has also been demonstrated through molecular docking and molecular dynamics simulation study. The binding energy result showed that pramipexole interaction with dopamine receptors D2 and D3 was higher than pramipexole mannose adduct and pramipexole ribose adduct.

Advancing PROTAC Characterization: Structural Insights through Adducts and Multimodal Tandem-MS Strategies

Proteolysis targeting chimeras (PROTACs) are specialized molecules that bind to a target protein and a ubiquitin ligase to facilitate protein degradation. Despite their significance, native PROTACs have not undergone tandem mass spectrometry (MS) analysis. To address this gap, we conducted a pioneering investigation on the fragmentation patterns of two PROTACs in development, dBET1 and VZ185. Employing diverse cations (sodium, lithium, and silver) and multiple tandem-MS techniques, we enhanced their structural characterization. Notably, lithium cations facilitated comprehensive positive-mode coverage for dBET1, while negative polarity mode offered richer insights. Employing de novo structure determination on 2DMS data from degradation studies yielded crucial insights. In the case of VZ185, various charge states were observed, with [M + 2H]2+ revealing fewer moieties than [M + H]+ due to charge-related factors. Augmenting structural details through silver adducts suggested both charge-directed and charge-remote fragmentation. This comprehensive investigation identifies frequently dissociated bonds across multiple fragmentation techniques, pinpointing optimal approaches for elucidating PROTAC structures. The findings contribute to advancing our understanding of PROTACs, pivotal for their continued development as promising therapeutic agents.

Facilitating structural elucidation of small environmental solutes in RPLC-HRMS by retention index prediction

Implementing effective environmental management strategies requires a comprehensive understanding of the chemical composition of environmental pollutants, particularly in complex mixtures. Utilizing innovative analytical techniques, such as high-resolution mass spectrometry and predictive retention index models, can provide valuable insights into the molecular structures of environmental contaminants. Liquid Chromatography-High-Resolution Mass Spectrometry is a powerful tool for the identification of isomeric structures in complex samples. However, there are some limitations that can prevent accurate isomeric structure identification, particularly in cases where the isomers have similar mass and fragmentation patterns. Liquid chromatographic retention, determined by the size, shape, and polarity of the analyte and its interactions with the stationary phase, contains valuable 3D structural information that is vastly underutilized. Therefore, a predictive retention index model is developed which is transferrable to LC-HRMS systems and can assist in the structural elucidation of unknowns. The approach is currently restricted to carbon, hydrogen, and oxygen-based molecules <500 g mol-1. The methodology facilitates the acceptance of accurate structural formulas and the exclusion of erroneous hypothetical structural representations by leveraging retention time estimations, thereby providing a permissible tolerance range for a given elemental composition and experimental retention time. This approach serves as a proof of concept for the development of a Quantitative Structure-Retention Relationship model using a generic gradient LC approach. The use of a widely used reversed-phase (U)HPLC column and a relatively large set of training (101) and test compounds (14) demonstrates the feasibility and potential applicability of this approach for predicting the retention behaviour of compounds in complex mixtures. By providing a standard operating procedure, this approach can be easily replicated and applied to various analytical challenges, further supporting its potential for broader implementation.

Hyphenated liquid chromatography - diode array detection - charged aerosol detection - high resolution - multistage mass spectrometry with online hydrogen/deuterium exchange: One stop solution for pharmaceutical impurity profiling

Hyphenation of different analytical techniques has always been advantageous in structural characterization as it saves time, money and resources. In the pharmaceutical sector, chromatography-based impurity profiling, including identification, characterization, and quantification in drug substances or finished products, is of utmost importance to comply with quality, patient safety and regulatory requirements. These impurities are monitored using LC-UV/DAD and identified and/or characterized using HRMS and MS/MS. LC analysis usually yields the area percent purity of the targeted peak, however, this is not sufficient for pharmaceutical purposes; where the regulatory requirement is to report impurities in percent weight by weight. Unfortunately, the non-availability of impurity standards and relative response factors at an early stage of drug development, risks the product quality due to the inability of the method to differentiate percent purity, and percent weight by weight. Hence, there is a need for a distinctive way of determining the relative response factor. In the current study, a unique hyphenation has been employed by integrating LC with DAD, CAD, and HRMSⁿ with hydrogen-deuterium exchange. The LC flow, post-DAD detection has been diverted to CAD with an inverse gradient for relative response factor determination and MS Orbitrap for exact mass, and MSⁿ fragmentation. A separate infusion pump has been incorporated to infuse D₂O on a need basis, which can perform partial hydrogen deuterium exchange for determining the number of labile hydrogens in the impurity structure. This hyphenation has been validated with four model compounds and a total of nineteen chromatographic peaks. The technique provides ample information for their qualitative analysis along with percent weight-by-weight values, which fulfils the regulatory requirements and can be used as one-stop solution for impurity profiling.

Identification of the Major Degradation Pathways of Selumetinib

Selumetinib is administered orally in capsule form and is indicated for the treatment of neurofibromatosis. To facilitate dosage adjustments, liquid preparations, such as solutions or suspensions, are to be developed. This led, first, to determine the stability profile of soluble or dispersed selumetinib and, secondly, to look for ways to stabilize the active substance. The degradation kinetics of selumetinib as a function of stress conditions were determined and compared. The degradation products were detected and identified by LC-HRMSⁿ. In solution, selumetinib is sensitive to oxidation and degrades by photooxidation. In both cases, the side chain represented by the oxoamide group is concerned, leading to the formation of an amide derivative for the first case and an ester derivative for the second. The identification of such degradation mechanisms allowed us to study, in a targeted way, processes aiming at stabilizing the active molecule.

Chemical Characterization and Non-targeted Analysis of Medical Device Extracts: A Review of Current Approaches, Gaps, and Emerging Practices

The developers of medical devices evaluate the biocompatibility of their device prior to FDA's review and subsequent introduction to the market. Chemical characterization, described in ISO 10993-18:2020, can generate information for toxicological risk assessment and is an alternative approach for addressing some biocompatibility end points (e.g., systemic toxicity, genotoxicity, carcinogenicity, reproductive/developmental toxicity) that can reduce the time and cost of testing and the need for animal testing. Additionally, chemical characterization can be used to determine whether modifications to the materials and manufacturing processes alter the chemistry of a patient-contacting device to an extent that could impact device safety. Extractables testing is one approach to chemical characterization that employs combinations of non-targeted analysis, non-targeted screening, and/or targeted analysis to establish the identities and quantities of the various chemical constituents that can be released from a device. Due to the difficulty in obtaining a priori information on all the constituents in finished devices, information generation strategies in the form of analytical chemistry testing are often used. Identified and quantified extractables are then assessed using toxicological risk assessment approaches to determine if reported quantities are sufficiently low to overcome the need for further chemical analysis, biological evaluation of select end points, or risk control. For extractables studies to be useful as a screening tool, comprehensive and reliable non-targeted methods are needed. Although non-targeted methods have been adopted by many laboratories, they are laboratory-specific and require expensive analytical instruments and advanced technical expertise to perform. In this Perspective, we describe the elements of extractables studies and provide an overview of the current practices, identified gaps, and emerging practices that may be adopted on a wider scale in the future. This Perspective is outlined according to the steps of an extractables study: information gathering, extraction, extract sample processing, system selection, qualification, quantification, and identification.

Gas-phase fragmentation of protonated 3-phenoxy imidazo[1,2-a] pyridines using tandem mass spectrometry and computational chemistry

Imidazo[1,2-a] pyridine is one of the pharmaceutically important scaffolds and has been widely studied due to its extensive biological activities. In this work, electrospray ionization tandem mass spectrometry (ESI-MS/MS) in positive mode was used to study the gas-phase fragmentation behavior of a series of 3-phenoxy imidazo[1,2-a] pyridines. Proposed fragmentation pathways were supported by ESI-MS/MS data and computational thermochemistry. Homolytic cleavage of the 3-phenoxy C-O bond was the characteristic fragmentation of 3-phenoxy imidazo [1,2-a] pyridines. The eliminations of the one substituted phenoxy radical and CO produced other diagnostic ions for 3-phenoxy imidazo [1,2-a] pyridines, which were useful to identify the 3-phenoxy group and imidazo [1,2-a] pyridine scaffold. The results contribute to the further understanding of the gas-phase fragmentation of 3-phenoxy imidazo [1,2-a] pyridines and the identification of other analogs using tandem mass spectrometry techniques.

Innate Immunity Modulating Impurities and the Immunotoxicity of Nanobiotechnology-Based Drug Products

Innate immunity can be triggered by the presence of microbial antigens and other contaminants inadvertently introduced during the manufacture and purification of bionanopharmaceutical products. Activation of these innate immune responses, including cytokine secretion, complement, and immune cell activation, can result in unexpected and undesirable host immune responses. These innate modulators can also potentially stimulate the activation of adaptive immune responses, including the formation of anti-drug antibodies which can impact drug effectiveness. To prevent induction of these adverse responses, it is important to detect and quantify levels of these innate immunity modulating impurities (IIMIs) that may be present in drug products. However, while it is universally agreed that removal of IIMIs from drug products is crucial for patient safety and to prevent long-term immunogenicity, there is no single assay capable of directly detecting all potential IIMIs or indirectly quantifying downstream biomarkers. Additionally, there is a lack of agreement as to which of the many analytical assays currently employed should be standardized for general IIMI screening. Herein, we review the available literature to highlight cellular and molecular mechanisms underlying IIMI-mediated inflammation and its relevance to the safety and efficacy of pharmaceutical products. We further discuss methodologies used for direct and indirect IIMI identification and quantification.

A simple and rapid method to simultaneously analyze ciclesonide and its impurities in a ciclesonide metered-dose inhaler using on-line supercritical fluid extraction/supercritical fluid chromatography/quadrupole time-of-flight mass spectrometry

A simple and rapid on-line SFE/SFC/quadrupole TOF-MS method to simultaneously analyze active pharmaceutical ingredients and impurities from metered-dose inhalers (MDIs) was developed using ciclesonide MDI (CIC-MDI) as an example. CIC-MDI, as drug Alvesco®, has been approved for the treatment of bronchial asthma, and its major impurities are listed in the European Pharmacopoeia and in the supplementary package inserts of Alvesco® (called as "Pharmaceutical interview form" in Japan). In the developed method, CIC-MDI was manually sprayed only once on a glass disc prior to the SFE/SFC/quadrupole TOF-MS. In the SFE, CIC and its impurities and other impurities having various polarities and hydrophobicity, were extracted in 3.5 min and subsequently separated on a CHIRALPAK IE-3 column to be detected by quadrupole TOF-MS in 6.5 min. This method would be applicable to the analysis of other inhalable pharmaceutical products whose sample preparation requires complicated procedures, as well as to the analysis of general pharmaceutical products for profiling impurities.

Exploring the phototransformation and assessing the in vitro and in silico toxicity of a mixture of pharmaceuticals susceptible to photolysis

The present study comprehensively investigates the phototransformation and ecotoxicity of a mixture of twelve pharmaceutically active compounds (PhACs) susceptible to photolysis. Namely, three antibiotics (ciprofloxacin, levofloxacin, moxifloxacin), three antidepressants (bupropion, duloxetine, olanzapine), three anti-inflammatory drugs (diclofenac, ketoprofen, nimesulide), two beta-blockers (propranolol, timolol) and the antihistamine ranitidine were treated under simulated solar irradiation in ultra-pure and river water. A total of 166 different transformation products (TPs) were identified by ultra-high performance liquid chromatography coupled with Orbitrap high resolution mass spectrometry (UHPLC-Orbitrap HRMS), revealing the formation of twelve novel TPs and forty-nine not previously described in photolytic studies. The kinetic profiles of the major TPs resulting from a series of chemical reactions involving hydroxylation, cleavage and oxidation, dehalogenation, decarboxylation, dealkylation and photo substitution have been investigated and the transformation pathways have been suggested. Additionally, an in vitro approach to the toxicity assessment of daphnids was contrasted with ecotoxicity data based on the Ecological Structure Activity Relationships (ECOSAR) software comprising the in silico tool to determine the adverse effects of the whole mixture of photolabile parent compounds and TPs. The results demonstrated that photolysis of the target mixture leads to a decrease of the observed toxicity.

Ruxolitinib photodegradation mechanisms by theoretical and experimental chemistry

Ruxolitinib is a Janus Kinase inhibitor currently approved for the treatment of myelofibrosis. It is also a promising drug for the treatment of skin and infectious diseases. In terms of pharmaceutical stability, although ruxolitinib has been established as being sensitive to light, no data on photodegradation processes are available to date, while these may be useful for quality risk management and any potential development of other pharmaceutical forms for other routes of administration. One way to partially fill this gap was to carry out a study that combines a consistent determination of the most sensitive sites of the molecule to photolysis through theoretical calculations based on functional density, with the identification of the main photodegradation products obtained after forced degradation. This integrated approach has shown converging results describing the mechanisms based on photo-oxidation that can lead to the opening of the pyrrole ring. Having access to the structure of the degradation products and intermediates then made it possible to carry out an in silico evaluation of their potential mutagenicity and it appears that some of them feature alert structures.